diff --git a/.gitignore b/.gitignore index 68bc17f..26e5680 100644 --- a/.gitignore +++ b/.gitignore @@ -158,3 +158,6 @@ cython_debug/ # and can be added to the global gitignore or merged into this file. For a more nuclear # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ +.DS_Store +example_files/.DS_Store +example_files/analysis/.DS_Store diff --git a/conphar/Pharmacophores.py b/conphar/Pharmacophores.py index 9145b3b..1b49f4b 100644 --- a/conphar/Pharmacophores.py +++ b/conphar/Pharmacophores.py @@ -271,7 +271,7 @@ def save_pharmacophore_to_json (table:pd.DataFrame,out_file:str='pharmacophore.j f.write(data) -def compute_concensus_pharmacophore (table:pd.DataFrame, save_data_per_descriptor:bool=True, out_folder:str='.', h_dist:float=0.17): +def compute_concensus_pharmacophore (table:pd.DataFrame, save_data_per_descriptor:bool=True, out_folder:str='.', h_dist:float=0.17,cmap_plots:str='binary_r'): """ Computes the concensus pharmacophore from a table of 3D coordinates and features of molecular descriptors. @@ -373,10 +373,8 @@ def __save_pymol_cluster(table:pd.DataFrame,out_file:str='cluster.pse',cluster_c row_colors = descriptor_cluster.cluster.map(lut).to_numpy() - - ax=sns.clustermap (matrix,method='complete',figsize=(6,6),xticklabels=0, yticklabels=0, - cmap='binary_r',cbar_kws=dict(label='Distance',shrink=1,orientation='vertical',spacing='uniform',pad=0.02), + cmap=cmap_plots,cbar_kws=dict(label='Distance',shrink=1,orientation='vertical',spacing='uniform',pad=0.02), row_linkage=linkage, col_linkage=linkage, rasterized=True,row_colors=row_colors,tree_kws=dict(linewidths=1)) x0, _y0, _w, _h = ax.cbar_pos diff --git a/conphar/Structures.py b/conphar/Structures.py index 434f30e..f910d21 100644 --- a/conphar/Structures.py +++ b/conphar/Structures.py @@ -139,8 +139,8 @@ def fetch_structure(target:str,target_chain:str,reference:str, reference_chain:s data=pd.DataFrame(arr.reshape(1,-1), columns=['refined_RMSD','refined_num_atoms','n_cycles','raw_RMSD','raw_num_atoms','aligment_score','n_residues_aligned'],index=[target]) if extract_ligands: - cmd.remove(f"solvent or inorganic or resn DMS or resn GOL or resn FTM or (not alt ''+{target_chain})") - n_lig=cmd.select('Ligand', state=1, selection=(f'byres ((chain {target_chain} and (resi 145 or resi 41) expand 10 and organic and not resn EDO or not chain {target_chain} and not chain B))')) + cmd.remove(f"solvent or inorganic or resn PEG or resn DMS or resn GOL or resn FTM or (not alt ''+{target_chain})") + n_lig=cmd.select('Ligand', state=1, selection=(f'byres chain {target_chain} and (organic or hetatm)')) data.loc[target,'lig_n_atoms']=n_lig diff --git a/example_files/analysis/HydrogenAcceptor_clusters.png b/example_files/analysis/HydrogenAcceptor_clusters.png deleted file mode 100644 index 563c63c..0000000 Binary files a/example_files/analysis/HydrogenAcceptor_clusters.png and /dev/null differ diff --git a/example_files/analysis/HydrogenAcceptor_clusters.pse b/example_files/analysis/HydrogenAcceptor_clusters.pse index 1e68949..ca25909 100644 Binary files a/example_files/analysis/HydrogenAcceptor_clusters.pse and b/example_files/analysis/HydrogenAcceptor_clusters.pse differ diff --git a/example_files/analysis/HydrogenAcceptor_clusters.svg b/example_files/analysis/HydrogenAcceptor_clusters.svg new file mode 100644 index 0000000..329784f --- /dev/null +++ b/example_files/analysis/HydrogenAcceptor_clusters.svg @@ -0,0 +1,554 @@ + + + + + + + + 2024-09-25T10:50:56.463147 + image/svg+xml + + + Matplotlib v3.9.2, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/example_files/analysis/HydrogenDonor_clusters.png b/example_files/analysis/HydrogenDonor_clusters.png deleted file mode 100644 index 0266b92..0000000 Binary files a/example_files/analysis/HydrogenDonor_clusters.png and /dev/null differ diff --git a/example_files/analysis/HydrogenDonor_clusters.pse b/example_files/analysis/HydrogenDonor_clusters.pse index f6c7e42..9965c1a 100644 Binary files a/example_files/analysis/HydrogenDonor_clusters.pse and b/example_files/analysis/HydrogenDonor_clusters.pse differ diff --git a/example_files/analysis/HydrogenDonor_clusters.svg b/example_files/analysis/HydrogenDonor_clusters.svg new file mode 100644 index 0000000..90f0be0 --- /dev/null +++ b/example_files/analysis/HydrogenDonor_clusters.svg @@ -0,0 +1,464 @@ + + + + + + + + 2024-09-25T10:50:56.658272 + image/svg+xml + + + Matplotlib v3.9.2, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/example_files/analysis/Hydrophobic_clusters.png b/example_files/analysis/Hydrophobic_clusters.png deleted file mode 100644 index f8afb9b..0000000 Binary files a/example_files/analysis/Hydrophobic_clusters.png and /dev/null differ diff --git a/example_files/analysis/Hydrophobic_clusters.pse b/example_files/analysis/Hydrophobic_clusters.pse index 3fc6551..f0b48e4 100644 Binary files a/example_files/analysis/Hydrophobic_clusters.pse and b/example_files/analysis/Hydrophobic_clusters.pse differ diff --git a/example_files/analysis/Hydrophobic_clusters.svg b/example_files/analysis/Hydrophobic_clusters.svg new file mode 100644 index 0000000..44422a0 --- /dev/null +++ b/example_files/analysis/Hydrophobic_clusters.svg @@ -0,0 +1,477 @@ + + + + + + + + 2024-09-25T10:50:56.825706 + image/svg+xml + + + Matplotlib v3.9.2, https://matplotlib.org/ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/example_files/analysis/pharmacophore_all_descriptors.json b/example_files/analysis/pharmacophore_all_descriptors.json index 3be68b2..ae181e5 100644 --- a/example_files/analysis/pharmacophore_all_descriptors.json +++ b/example_files/analysis/pharmacophore_all_descriptors.json @@ -1 +1 @@ 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\ No newline at end of file diff --git a/example_files/analysis/pharmacophore_concensus.pse b/example_files/analysis/pharmacophore_concensus.pse index d6b3916..96b6ba1 100644 Binary files a/example_files/analysis/pharmacophore_concensus.pse and b/example_files/analysis/pharmacophore_concensus.pse differ diff --git a/example_files/ligand/5R7Y_lig.sdf b/example_files/ligand/5R7Y_lig.sdf index 315fb39..836f7ab 100644 --- a/example_files/ligand/5R7Y_lig.sdf +++ b/example_files/ligand/5R7Y_lig.sdf @@ -1,5 +1,5 @@ target - PyMOL2.1 3D 0 + PyMOL3.0 3D 0 13 13 0 0 0 0 0 0 0 0999 V2000 9.9480 -5.5000 26.1430 C 0 0 0 0 0 0 0 0 0 0 0 0 @@ -29,4 +29,101 @@ target 8 13 4 0 0 0 0 12 13 4 0 0 0 0 M END +> +HEADER HYDROLASE/HYDROLASE INHIBITOR 03-MAR-20 XXXX +TITLE PANDDA ANALYSIS GROUP DEPOSITION -- CRYSTAL STRUCTURE OF COVID-19 MAIN +TITLE 2 PROTEASE IN COMPLEX WITH Z45617795 +KEYWDS SGC - DIAMOND I04-1 FRAGMENT SCREENING, PANDDA, XCHEMEXPLORER, +KEYWDS 2 HYDROLASE-HYDROLASE INHIBITOR COMPLEX +EXPDTA X-RAY DIFFRACTION +AUTHOR D.FEARON,A.J.POWELL,A.DOUANGAMATH,C.D.OWEN,C.WILD,T.KROJER,P.LUKACIK, +AUTHOR 2 C.M.STRAIN-DAMERELL,M.A.WALSH,F.VON DELFT +JRNL AUTH A.DOUANGAMATH,D.FEARON,P.GEHRTZ,T.KROJER,P.LUKACIK,C.D.OWEN, +JRNL AUTH 2 E.RESNICK,C.STRAIN-DAMERELL,A.AIMON,P.ABRANYI-BALOGH, +JRNL AUTH 3 J.BRANDAO-NETO,A.CARBERY,G.DAVISON,A.DIAS,T.D.DOWNES, +JRNL AUTH 4 L.DUNNETT,M.FAIRHEAD,J.D.FIRTH,S.P.JONES,A.KEELEY, +JRNL AUTH 5 G.M.KESERU,H.F.KLEIN,M.P.MARTIN,M.E.M.NOBLE,P.O'BRIEN, +JRNL AUTH 6 A.POWELL,R.N.REDDI,R.SKYNER,M.SNEE,M.J.WARING,C.WILD, +JRNL AUTH 7 N.LONDON,F.VON DELFT,M.A.WALSH +JRNL TITL CRYSTALLOGRAPHIC AND ELECTROPHILIC FRAGMENT SCREENING OF THE +JRNL TITL 2 SARS-COV-2 MAIN PROTEASE. +JRNL REF NAT COMMUN V. 11 5047 2020 +JRNL REFN ESSN 2041-1723 +JRNL PMID 33028810 +JRNL DOI 10.1038/S41467-020-18709-W +SEQRES 1 A 306 SER GLY PHE ARG LYS MET ALA PHE PRO SER GLY LYS VAL +SEQRES 2 A 306 GLU GLY CYS MET VAL GLN VAL THR CYS GLY THR THR THR +SEQRES 3 A 306 LEU ASN GLY LEU TRP LEU ASP ASP VAL VAL TYR CYS PRO +SEQRES 4 A 306 ARG HIS VAL ILE CYS THR SER GLU ASP MET LEU ASN PRO +SEQRES 5 A 306 ASN TYR GLU ASP LEU LEU ILE ARG LYS SER ASN HIS ASN +SEQRES 6 A 306 PHE LEU VAL GLN ALA GLY ASN VAL GLN LEU ARG VAL ILE +SEQRES 7 A 306 GLY HIS SER MET GLN ASN CYS VAL LEU LYS LEU LYS VAL +SEQRES 8 A 306 ASP THR ALA ASN PRO LYS THR PRO LYS TYR LYS PHE VAL +SEQRES 9 A 306 ARG ILE GLN PRO GLY GLN THR PHE SER VAL LEU ALA CYS +SEQRES 10 A 306 TYR ASN GLY SER PRO SER GLY VAL TYR GLN CYS ALA MET +SEQRES 11 A 306 ARG PRO ASN PHE THR ILE LYS GLY SER PHE LEU ASN GLY +SEQRES 12 A 306 SER CYS GLY SER VAL GLY PHE ASN ILE ASP TYR ASP CYS +SEQRES 13 A 306 VAL SER PHE CYS TYR MET HIS HIS MET GLU LEU PRO THR +SEQRES 14 A 306 GLY VAL HIS ALA GLY THR ASP LEU GLU GLY ASN PHE TYR +SEQRES 15 A 306 GLY PRO PHE VAL ASP ARG GLN THR ALA GLN ALA ALA GLY +SEQRES 16 A 306 THR ASP THR THR ILE THR VAL ASN VAL LEU ALA TRP LEU +SEQRES 17 A 306 TYR ALA ALA VAL ILE ASN GLY ASP ARG TRP PHE LEU ASN +SEQRES 18 A 306 ARG PHE THR THR THR LEU ASN ASP PHE ASN LEU VAL ALA +SEQRES 19 A 306 MET LYS TYR ASN TYR GLU PRO LEU THR GLN ASP HIS VAL +SEQRES 20 A 306 ASP ILE LEU GLY PRO LEU SER ALA GLN THR GLY ILE ALA +SEQRES 21 A 306 VAL LEU ASP MET CYS ALA SER LEU LYS GLU LEU LEU GLN +SEQRES 22 A 306 ASN GLY MET ASN GLY ARG THR ILE LEU GLY SER ALA LEU +SEQRES 23 A 306 LEU GLU ASP GLU PHE THR PRO PHE ASP VAL VAL ARG GLN +SEQRES 24 A 306 CYS SER GLY VAL THR PHE GLN +HETNAM JFM N-(2-PHENYLETHYL)METHANESULFONAMIDE +HETNAM DMS DIMETHYL SULFOXIDE +HETNAM CL CHLORIDE ION +FORMUL 2 JFM C9 H13 N O2 S +FORMUL 3 DMS 4(C2 H6 O S) +FORMUL 7 CL CL 1- +FORMUL 8 HOH *321(H2 O) +HELIX 1 AA1 SER A 10 GLY A 15 1 6 +HELIX 2 AA2 HIS A 41 CYS A 44 5 4 +HELIX 3 AA3 GLU A 47 ASN A 51 5 5 +HELIX 4 AA4 ASN A 53 ARG A 60 1 8 +HELIX 5 AA5 LYS A 61 HIS A 64 5 4 +HELIX 6 AA6 ILE A 200 ASN A 214 1 15 +HELIX 7 AA7 THR A 226 TYR A 237 1 12 +HELIX 8 AA8 THR A 243 LEU A 250 1 8 +HELIX 9 AA9 LEU A 250 GLY A 258 1 9 +HELIX 10 AB1 ALA A 260 GLY A 275 1 16 +HELIX 11 AB2 THR A 292 GLY A 302 1 11 +SHEET 1 AA1 7 VAL A 73 LEU A 75 0 +SHEET 2 AA1 7 PHE A 66 ALA A 70 -1 N VAL A 68 O LEU A 75 +SHEET 3 AA1 7 MET A 17 CYS A 22 -1 N THR A 21 O LEU A 67 +SHEET 4 AA1 7 THR A 25 LEU A 32 -1 O LEU A 27 N VAL A 20 +SHEET 5 AA1 7 VAL A 35 PRO A 39 -1 O TYR A 37 N LEU A 30 +SHEET 6 AA1 7 VAL A 86 VAL A 91 -1 O LEU A 89 N VAL A 36 +SHEET 7 AA1 7 VAL A 77 GLN A 83 -1 N GLN A 83 O VAL A 86 +SHEET 1 AA2 5 LYS A 100 PHE A 103 0 +SHEET 2 AA2 5 CYS A 156 GLU A 166 1 O VAL A 157 N LYS A 100 +SHEET 3 AA2 5 VAL A 148 ASP A 153 -1 N ASN A 151 O SER A 158 +SHEET 4 AA2 5 THR A 111 TYR A 118 -1 N SER A 113 O PHE A 150 +SHEET 5 AA2 5 SER A 121 ALA A 129 -1 O SER A 123 N ALA A 116 +SHEET 1 AA3 3 LYS A 100 PHE A 103 0 +SHEET 2 AA3 3 CYS A 156 GLU A 166 1 O VAL A 157 N LYS A 100 +SHEET 3 AA3 3 HIS A 172 THR A 175 -1 O THR A 175 N MET A 162 +SITE 1 AC1 8 HIS A 41 CYS A 44 SER A 46 MET A 49 +SITE 2 AC1 8 HIS A 164 MET A 165 ARG A 188 GLN A 189 +SITE 1 AC2 6 GLN A 74 LEU A 75 ARG A 76 THR A 224 +SITE 2 AC2 6 ASP A 263 HOH A1196 +SITE 1 AC3 4 MET A 6 SER A 123 GLN A 127 ARG A 298 +SITE 1 AC4 2 GLY A 15 MET A 17 +SITE 1 AC5 5 PHE A 140 LEU A 141 HIS A 163 MET A 165 +SITE 2 AC5 5 GLU A 166 +SITE 1 AC6 4 GLY A 143 SER A 144 CYS A 145 HOH A1319 +CRYST1 112.463 52.731 44.299 90.00 102.81 90.00 C 1 2 1 4 +ORIGX1 1.000000 0.000000 0.000000 0.00000 +ORIGX2 0.000000 1.000000 0.000000 0.00000 +ORIGX3 0.000000 0.000000 1.000000 0.00000 +SCALE1 0.008892 0.000000 0.002022 0.00000 +SCALE2 0.000000 0.018964 0.000000 0.00000 +SCALE3 0.000000 0.000000 0.023150 0.00000 + + $$$$ diff --git a/example_files/ligand/5R7Z_lig.sdf b/example_files/ligand/5R7Z_lig.sdf index ff75d80..3470824 100644 --- a/example_files/ligand/5R7Z_lig.sdf +++ b/example_files/ligand/5R7Z_lig.sdf @@ -1,5 +1,5 @@ target - PyMOL2.1 3D 0 + PyMOL3.0 3D 0 16 17 0 0 0 0 0 0 0 0999 V2000 9.1852 6.1013 22.6414 C 0 0 0 0 0 0 0 0 0 0 0 0 @@ -13,7 +13,7 @@ target 11.1312 2.5927 24.1987 C 0 0 0 0 0 0 0 0 0 0 0 0 11.2295 0.4437 23.6963 C 0 0 0 0 0 0 0 0 0 0 0 0 12.3103 1.0362 23.0881 C 0 0 0 0 0 0 0 0 0 0 0 0 - 13.2023 0.2372 22.3230 C 0 0 0 0 0 0 0 0 0 0 0 0 + 13.2022 0.2372 22.3230 C 0 0 0 0 0 0 0 0 0 0 0 0 12.9775 -1.1322 22.1896 C 0 0 0 0 0 0 0 0 0 0 0 0 11.8767 -1.7277 22.8149 C 0 0 0 0 0 0 0 0 0 0 0 0 10.9997 -0.9517 23.5678 C 0 0 0 0 0 0 0 0 0 0 0 0 @@ -36,4 +36,100 @@ target 13 16 1 0 0 0 0 14 15 4 0 0 0 0 M END +> +HEADER HYDROLASE/HYDROLASE INHIBITOR 03-MAR-20 XXXX +TITLE PANDDA ANALYSIS GROUP DEPOSITION -- CRYSTAL STRUCTURE OF SARS-COV-2 +TITLE 2 MAIN PROTEASE IN COMPLEX WITH Z1220452176 +KEYWDS SGC - DIAMOND I04-1 FRAGMENT SCREENING, PANDDA, XCHEMEXPLORER, +KEYWDS 2 HYDROLASE-HYDROLASE INHIBITOR COMPLEX +EXPDTA X-RAY DIFFRACTION +AUTHOR D.FEARON,A.J.POWELL,A.DOUANGAMATH,C.D.OWEN,C.WILD,T.KROJER,P.LUKACIK, +AUTHOR 2 C.M.STRAIN-DAMERELL,M.A.WALSH,F.VON DELFT +JRNL AUTH A.DOUANGAMATH,D.FEARON,P.GEHRTZ,T.KROJER,P.LUKACIK,C.D.OWEN, +JRNL AUTH 2 E.RESNICK,C.STRAIN-DAMERELL,A.AIMON,P.ABRANYI-BALOGH, +JRNL AUTH 3 J.BRANDAO-NETO,A.CARBERY,G.DAVISON,A.DIAS,T.D.DOWNES, +JRNL AUTH 4 L.DUNNETT,M.FAIRHEAD,J.D.FIRTH,S.P.JONES,A.KEELEY, +JRNL AUTH 5 G.M.KESERU,H.F.KLEIN,M.P.MARTIN,M.E.M.NOBLE,P.O'BRIEN, +JRNL AUTH 6 A.POWELL,R.N.REDDI,R.SKYNER,M.SNEE,M.J.WARING,C.WILD, +JRNL AUTH 7 N.LONDON,F.VON DELFT,M.A.WALSH +JRNL TITL CRYSTALLOGRAPHIC AND ELECTROPHILIC FRAGMENT SCREENING OF THE +JRNL TITL 2 SARS-COV-2 MAIN PROTEASE. +JRNL REF NAT COMMUN V. 11 5047 2020 +JRNL REFN ESSN 2041-1723 +JRNL PMID 33028810 +JRNL DOI 10.1038/S41467-020-18709-W +SEQRES 1 A 306 SER GLY PHE ARG LYS MET ALA PHE PRO SER GLY LYS VAL +SEQRES 2 A 306 GLU GLY CYS MET VAL GLN VAL THR CYS GLY THR THR THR +SEQRES 3 A 306 LEU ASN GLY LEU TRP LEU ASP ASP VAL VAL TYR CYS PRO +SEQRES 4 A 306 ARG HIS VAL ILE CYS THR SER GLU ASP MET LEU ASN PRO +SEQRES 5 A 306 ASN TYR GLU ASP LEU LEU ILE ARG LYS SER ASN HIS ASN +SEQRES 6 A 306 PHE LEU VAL GLN ALA GLY ASN VAL GLN LEU ARG VAL ILE +SEQRES 7 A 306 GLY HIS SER MET GLN ASN CYS VAL LEU LYS LEU LYS VAL +SEQRES 8 A 306 ASP THR ALA ASN PRO LYS THR PRO LYS TYR LYS PHE VAL +SEQRES 9 A 306 ARG ILE GLN PRO GLY GLN THR PHE SER VAL LEU ALA CYS +SEQRES 10 A 306 TYR ASN GLY SER PRO SER GLY VAL TYR GLN CYS ALA MET +SEQRES 11 A 306 ARG PRO ASN PHE THR ILE LYS GLY SER PHE LEU ASN GLY +SEQRES 12 A 306 SER CYS GLY SER VAL GLY PHE ASN ILE ASP TYR ASP CYS +SEQRES 13 A 306 VAL SER PHE CYS TYR MET HIS HIS MET GLU LEU PRO THR +SEQRES 14 A 306 GLY VAL HIS ALA GLY THR ASP LEU GLU GLY ASN PHE TYR +SEQRES 15 A 306 GLY PRO PHE VAL ASP ARG GLN THR ALA GLN ALA ALA GLY +SEQRES 16 A 306 THR ASP THR THR ILE THR VAL ASN VAL LEU ALA TRP LEU +SEQRES 17 A 306 TYR ALA ALA VAL ILE ASN GLY ASP ARG TRP PHE LEU ASN +SEQRES 18 A 306 ARG PHE THR THR THR LEU ASN ASP PHE ASN LEU VAL ALA +SEQRES 19 A 306 MET LYS TYR ASN TYR GLU PRO LEU THR GLN ASP HIS VAL +SEQRES 20 A 306 ASP ILE LEU GLY PRO LEU SER ALA GLN THR GLY ILE ALA +SEQRES 21 A 306 VAL LEU ASP MET CYS ALA SER LEU LYS GLU LEU LEU GLN +SEQRES 22 A 306 ASN GLY MET ASN GLY ARG THR ILE LEU GLY SER ALA LEU +SEQRES 23 A 306 LEU GLU ASP GLU PHE THR PRO PHE ASP VAL VAL ARG GLN +SEQRES 24 A 306 CYS SER GLY VAL THR PHE GLN +HETNAM DMS DIMETHYL SULFOXIDE +HETNAM HWH ~{N}-[2-(5-FLUORANYL-1~{H}-INDOL-3-YL)ETHYL]ETHANAMIDE +FORMUL 2 DMS 4(C2 H6 O S) +FORMUL 5 HWH C12 H13 F N2 O +FORMUL 7 HOH *328(H2 O) +HELIX 1 AA1 SER A 10 GLY A 15 1 6 +HELIX 2 AA2 HIS A 41 CYS A 44 5 4 +HELIX 3 AA3 GLU A 47 ASN A 51 5 5 +HELIX 4 AA4 ASN A 53 ARG A 60 1 8 +HELIX 5 AA5 LYS A 61 HIS A 64 5 4 +HELIX 6 AA6 ILE A 200 ASN A 214 1 15 +HELIX 7 AA7 THR A 226 TYR A 237 1 12 +HELIX 8 AA8 THR A 243 GLY A 258 1 16 +HELIX 9 AA9 ALA A 260 GLY A 275 1 16 +HELIX 10 AB1 THR A 292 GLY A 302 1 11 +SHEET 1 AA1 7 VAL A 73 LEU A 75 0 +SHEET 2 AA1 7 PHE A 66 ALA A 70 -1 N VAL A 68 O LEU A 75 +SHEET 3 AA1 7 MET A 17 CYS A 22 -1 N THR A 21 O LEU A 67 +SHEET 4 AA1 7 THR A 25 LEU A 32 -1 O LEU A 27 N VAL A 20 +SHEET 5 AA1 7 VAL A 35 PRO A 39 -1 O TYR A 37 N LEU A 30 +SHEET 6 AA1 7 VAL A 86 VAL A 91 -1 O LEU A 87 N CYS A 38 +SHEET 7 AA1 7 VAL A 77 GLN A 83 -1 N SER A 81 O LYS A 88 +SHEET 1 AA2 5 LYS A 100 PHE A 103 0 +SHEET 2 AA2 5 CYS A 156 GLU A 166 1 O PHE A 159 N LYS A 102 +SHEET 3 AA2 5 VAL A 148 ASP A 153 -1 N GLY A 149 O TYR A 161 +SHEET 4 AA2 5 THR A 111 TYR A 118 -1 N SER A 113 O PHE A 150 +SHEET 5 AA2 5 SER A 121 ALA A 129 -1 O SER A 123 N ALA A 116 +SHEET 1 AA3 3 LYS A 100 PHE A 103 0 +SHEET 2 AA3 3 CYS A 156 GLU A 166 1 O PHE A 159 N LYS A 102 +SHEET 3 AA3 3 HIS A 172 THR A 175 -1 O ALA A 173 N MET A 165 +SITE 1 AC1 8 GLN A 74 LEU A 75 ARG A 76 PHE A 223 +SITE 2 AC1 8 THR A 224 ASP A 263 HOH A 516 HOH A 564 +SITE 1 AC2 5 MET A 6 PHE A 8 SER A 123 GLN A 127 +SITE 2 AC2 5 ARG A 298 +SITE 1 AC3 3 GLY A 15 MET A 17 LYS A 97 +SITE 1 AC4 13 HIS A 41 MET A 49 MET A 165 GLU A 166 +SITE 2 AC4 13 LEU A 167 PRO A 168 ASP A 187 ARG A 188 +SITE 3 AC4 13 GLN A 189 THR A 190 GLY A 251 PRO A 252 +SITE 4 AC4 13 HOH A 627 +SITE 1 AC5 6 PHE A 140 LEU A 141 CYS A 145 HIS A 163 +SITE 2 AC5 6 MET A 165 GLU A 166 +CRYST1 112.090 52.513 44.384 90.00 102.94 90.00 C 1 2 1 4 +ORIGX1 1.000000 0.000000 0.000000 0.00000 +ORIGX2 0.000000 1.000000 0.000000 0.00000 +ORIGX3 0.000000 0.000000 1.000000 0.00000 +SCALE1 0.008921 0.000000 0.002049 0.00000 +SCALE2 0.000000 0.019043 0.000000 0.00000 +SCALE3 0.000000 0.000000 0.023117 0.00000 + + $$$$ diff --git a/example_files/ligand/5R80_lig.sdf b/example_files/ligand/5R80_lig.sdf index 18c4ca4..794b976 100644 --- a/example_files/ligand/5R80_lig.sdf +++ b/example_files/ligand/5R80_lig.sdf @@ -1,5 +1,5 @@ target - PyMOL2.1 3D 0 + PyMOL3.0 3D 0 14 14 0 0 0 0 0 0 0 0999 V2000 13.7965 -2.5469 24.2454 C 0 0 0 0 0 0 0 0 0 0 0 0 @@ -31,4 +31,96 @@ target 11 13 2 0 0 0 0 11 14 1 0 0 0 0 M END +> +HEADER HYDROLASE/HYDROLASE INHIBITOR 03-MAR-20 XXXX +TITLE PANDDA ANALYSIS GROUP DEPOSITION -- CRYSTAL STRUCTURE OF SARS-COV-2 +TITLE 2 MAIN PROTEASE IN COMPLEX WITH Z18197050 +KEYWDS SGC - DIAMOND I04-1 FRAGMENT SCREENING, PANDDA, XCHEMEXPLORER, +KEYWDS 2 HYDROLASE-HYDROLASE INHIBITOR COMPLEX +EXPDTA X-RAY DIFFRACTION +AUTHOR D.FEARON,A.J.POWELL,A.DOUANGAMATH,C.D.OWEN,C.WILD,T.KROJER,P.LUKACIK, +AUTHOR 2 C.M.STRAIN-DAMERELL,M.A.WALSH,F.VON DELFT +JRNL AUTH A.DOUANGAMATH,D.FEARON,P.GEHRTZ,T.KROJER,P.LUKACIK,C.D.OWEN, +JRNL AUTH 2 E.RESNICK,C.STRAIN-DAMERELL,A.AIMON,P.ABRANYI-BALOGH, +JRNL AUTH 3 J.BRANDAO-NETO,A.CARBERY,G.DAVISON,A.DIAS,T.D.DOWNES, +JRNL AUTH 4 L.DUNNETT,M.FAIRHEAD,J.D.FIRTH,S.P.JONES,A.KEELEY, +JRNL AUTH 5 G.M.KESERU,H.F.KLEIN,M.P.MARTIN,M.E.M.NOBLE,P.O'BRIEN, +JRNL AUTH 6 A.POWELL,R.N.REDDI,R.SKYNER,M.SNEE,M.J.WARING,C.WILD, +JRNL AUTH 7 N.LONDON,F.VON DELFT,M.A.WALSH +JRNL TITL CRYSTALLOGRAPHIC AND ELECTROPHILIC FRAGMENT SCREENING OF THE +JRNL TITL 2 SARS-COV-2 MAIN PROTEASE. +JRNL REF NAT COMMUN V. 11 5047 2020 +JRNL REFN ESSN 2041-1723 +JRNL PMID 33028810 +JRNL DOI 10.1038/S41467-020-18709-W +SEQRES 1 A 306 SER GLY PHE ARG LYS MET ALA PHE PRO SER GLY LYS VAL +SEQRES 2 A 306 GLU GLY CYS MET VAL GLN VAL THR CYS GLY THR THR THR +SEQRES 3 A 306 LEU ASN GLY LEU TRP LEU ASP ASP VAL VAL TYR CYS PRO +SEQRES 4 A 306 ARG HIS VAL ILE CYS THR SER GLU ASP MET LEU ASN PRO +SEQRES 5 A 306 ASN TYR GLU ASP LEU LEU ILE ARG LYS SER ASN HIS ASN +SEQRES 6 A 306 PHE LEU VAL GLN ALA GLY ASN VAL GLN LEU ARG VAL ILE +SEQRES 7 A 306 GLY HIS SER MET GLN ASN CYS VAL LEU LYS LEU LYS VAL +SEQRES 8 A 306 ASP THR ALA ASN PRO LYS THR PRO LYS TYR LYS PHE VAL +SEQRES 9 A 306 ARG ILE GLN PRO GLY GLN THR PHE SER VAL LEU ALA CYS +SEQRES 10 A 306 TYR ASN GLY SER PRO SER GLY VAL TYR GLN CYS ALA MET +SEQRES 11 A 306 ARG PRO ASN PHE THR ILE LYS GLY SER PHE LEU ASN GLY +SEQRES 12 A 306 SER CYS GLY SER VAL GLY PHE ASN ILE ASP TYR ASP CYS +SEQRES 13 A 306 VAL SER PHE CYS TYR MET HIS HIS MET GLU LEU PRO THR +SEQRES 14 A 306 GLY VAL HIS ALA GLY THR ASP LEU GLU GLY ASN PHE TYR +SEQRES 15 A 306 GLY PRO PHE VAL ASP ARG GLN THR ALA GLN ALA ALA GLY +SEQRES 16 A 306 THR ASP THR THR ILE THR VAL ASN VAL LEU ALA TRP LEU +SEQRES 17 A 306 TYR ALA ALA VAL ILE ASN GLY ASP ARG TRP PHE LEU ASN +SEQRES 18 A 306 ARG PHE THR THR THR LEU ASN ASP PHE ASN LEU VAL ALA +SEQRES 19 A 306 MET LYS TYR ASN TYR GLU PRO LEU THR GLN ASP HIS VAL +SEQRES 20 A 306 ASP ILE LEU GLY PRO LEU SER ALA GLN THR GLY ILE ALA +SEQRES 21 A 306 VAL LEU ASP MET CYS ALA SER LEU LYS GLU LEU LEU GLN +SEQRES 22 A 306 ASN GLY MET ASN GLY ARG THR ILE LEU GLY SER ALA LEU +SEQRES 23 A 306 LEU GLU ASP GLU PHE THR PRO PHE ASP VAL VAL ARG GLN +SEQRES 24 A 306 CYS SER GLY VAL THR PHE GLN +HETNAM DMS DIMETHYL SULFOXIDE +HETNAM RZG METHYL 4-SULFAMOYLBENZOATE +FORMUL 2 DMS 3(C2 H6 O S) +FORMUL 5 RZG C8 H9 N O4 S +FORMUL 6 HOH *330(H2 O) +HELIX 1 AA1 SER A 10 GLY A 15 1 6 +HELIX 2 AA2 HIS A 41 CYS A 44 5 4 +HELIX 3 AA3 ASN A 53 ARG A 60 1 8 +HELIX 4 AA4 LYS A 61 HIS A 64 5 4 +HELIX 5 AA5 ILE A 200 ASN A 214 1 15 +HELIX 6 AA6 THR A 226 TYR A 237 1 12 +HELIX 7 AA7 THR A 243 GLY A 258 1 16 +HELIX 8 AA8 ALA A 260 GLY A 275 1 16 +HELIX 9 AA9 THR A 292 CYS A 300 1 9 +SHEET 1 AA1 7 VAL A 73 LEU A 75 0 +SHEET 2 AA1 7 PHE A 66 ALA A 70 -1 N VAL A 68 O LEU A 75 +SHEET 3 AA1 7 MET A 17 CYS A 22 -1 N GLN A 19 O GLN A 69 +SHEET 4 AA1 7 THR A 25 LEU A 32 -1 O LEU A 27 N VAL A 20 +SHEET 5 AA1 7 VAL A 35 PRO A 39 -1 O TYR A 37 N LEU A 30 +SHEET 6 AA1 7 VAL A 86 VAL A 91 -1 O LEU A 89 N VAL A 36 +SHEET 7 AA1 7 VAL A 77 GLN A 83 -1 N GLN A 83 O VAL A 86 +SHEET 1 AA2 5 LYS A 100 PHE A 103 0 +SHEET 2 AA2 5 CYS A 156 GLU A 166 1 O VAL A 157 N LYS A 100 +SHEET 3 AA2 5 VAL A 148 ASP A 153 -1 N ASN A 151 O SER A 158 +SHEET 4 AA2 5 THR A 111 TYR A 118 -1 N SER A 113 O PHE A 150 +SHEET 5 AA2 5 SER A 121 ALA A 129 -1 O CYS A 128 N PHE A 112 +SHEET 1 AA3 3 LYS A 100 PHE A 103 0 +SHEET 2 AA3 3 CYS A 156 GLU A 166 1 O VAL A 157 N LYS A 100 +SHEET 3 AA3 3 HIS A 172 THR A 175 -1 O ALA A 173 N MET A 165 +SITE 1 AC1 8 GLN A 74 ARG A 76 PHE A 223 THR A 224 +SITE 2 AC1 8 ASP A 263 HOH A 587 HOH A 637 HOH A 798 +SITE 1 AC2 5 MET A 6 PHE A 8 SER A 123 GLN A 127 +SITE 2 AC2 5 ARG A 298 +SITE 1 AC3 3 GLY A 15 MET A 17 HOH A 681 +SITE 1 AC4 12 HIS A 41 TYR A 54 GLU A 166 PRO A 168 +SITE 2 AC4 12 ASP A 187 ARG A 188 GLN A 189 ASP A 248 +SITE 3 AC4 12 GLY A 251 PRO A 252 HOH A 518 HOH A 675 +CRYST1 112.891 53.030 44.352 90.00 102.46 90.00 C 1 2 1 4 +ORIGX1 1.000000 0.000000 0.000000 0.00000 +ORIGX2 0.000000 1.000000 0.000000 0.00000 +ORIGX3 0.000000 0.000000 1.000000 0.00000 +SCALE1 0.008858 0.000000 0.001957 0.00000 +SCALE2 0.000000 0.018857 0.000000 0.00000 +SCALE3 0.000000 0.000000 0.023090 0.00000 + + $$$$ diff --git a/example_files/ligand/5R81_lig.sdf b/example_files/ligand/5R81_lig.sdf index 965fed3..a0ad582 100644 --- a/example_files/ligand/5R81_lig.sdf +++ b/example_files/ligand/5R81_lig.sdf @@ -1,5 +1,5 @@ target - PyMOL2.1 3D 0 + PyMOL3.0 3D 0 15 16 0 0 0 0 0 0 0 0999 V2000 10.0015 -0.5220 25.0692 C 0 0 0 0 0 0 0 0 0 0 0 0 @@ -34,4 +34,100 @@ target 12 14 2 0 0 0 0 12 15 1 0 0 0 0 M END +> +HEADER HYDROLASE/HYDROLASE INHIBITOR 03-MAR-20 XXXX +TITLE PANDDA ANALYSIS GROUP DEPOSITION -- CRYSTAL STRUCTURE OF COVID-19 MAIN +TITLE 2 PROTEASE IN COMPLEX WITH Z1367324110 +KEYWDS SGC - DIAMOND I04-1 FRAGMENT SCREENING, PANDDA, XCHEMEXPLORER, +KEYWDS 2 HYDROLASE-HYDROLASE INHIBITOR COMPLEX +EXPDTA X-RAY DIFFRACTION +AUTHOR D.FEARON,A.J.POWELL,A.DOUANGAMATH,C.D.OWEN,C.WILD,T.KROJER,P.LUKACIK, +AUTHOR 2 C.M.STRAIN-DAMERELL,M.A.WALSH,F.VON DELFT +JRNL AUTH A.DOUANGAMATH,D.FEARON,P.GEHRTZ,T.KROJER,P.LUKACIK,C.D.OWEN, +JRNL AUTH 2 E.RESNICK,C.STRAIN-DAMERELL,A.AIMON,P.ABRANYI-BALOGH, +JRNL AUTH 3 J.BRANDAO-NETO,A.CARBERY,G.DAVISON,A.DIAS,T.D.DOWNES, +JRNL AUTH 4 L.DUNNETT,M.FAIRHEAD,J.D.FIRTH,S.P.JONES,A.KEELEY, +JRNL AUTH 5 G.M.KESERU,H.F.KLEIN,M.P.MARTIN,M.E.M.NOBLE,P.O'BRIEN, +JRNL AUTH 6 A.POWELL,R.N.REDDI,R.SKYNER,M.SNEE,M.J.WARING,C.WILD, +JRNL AUTH 7 N.LONDON,F.VON DELFT,M.A.WALSH +JRNL TITL CRYSTALLOGRAPHIC AND ELECTROPHILIC FRAGMENT SCREENING OF THE +JRNL TITL 2 SARS-COV-2 MAIN PROTEASE. +JRNL REF NAT COMMUN V. 11 5047 2020 +JRNL REFN ESSN 2041-1723 +JRNL PMID 33028810 +JRNL DOI 10.1038/S41467-020-18709-W +SEQRES 1 A 306 SER GLY PHE ARG LYS MET ALA PHE PRO SER GLY LYS VAL +SEQRES 2 A 306 GLU GLY CYS MET VAL GLN VAL THR CYS GLY THR THR THR +SEQRES 3 A 306 LEU ASN GLY LEU TRP LEU ASP ASP VAL VAL TYR CYS PRO +SEQRES 4 A 306 ARG HIS VAL ILE CYS THR SER GLU ASP MET LEU ASN PRO +SEQRES 5 A 306 ASN TYR GLU ASP LEU LEU ILE ARG LYS SER ASN HIS ASN +SEQRES 6 A 306 PHE LEU VAL GLN ALA GLY ASN VAL GLN LEU ARG VAL ILE +SEQRES 7 A 306 GLY HIS SER MET GLN ASN CYS VAL LEU LYS LEU LYS VAL +SEQRES 8 A 306 ASP THR ALA ASN PRO LYS THR PRO LYS TYR LYS PHE VAL +SEQRES 9 A 306 ARG ILE GLN PRO GLY GLN THR PHE SER VAL LEU ALA CYS +SEQRES 10 A 306 TYR ASN GLY SER PRO SER GLY VAL TYR GLN CYS ALA MET +SEQRES 11 A 306 ARG PRO ASN PHE THR ILE LYS GLY SER PHE LEU ASN GLY +SEQRES 12 A 306 SER CYS GLY SER VAL GLY PHE ASN ILE ASP TYR ASP CYS +SEQRES 13 A 306 VAL SER PHE CYS TYR MET HIS HIS MET GLU LEU PRO THR +SEQRES 14 A 306 GLY VAL HIS ALA GLY THR ASP LEU GLU GLY ASN PHE TYR +SEQRES 15 A 306 GLY PRO PHE VAL ASP ARG GLN THR ALA GLN ALA ALA GLY +SEQRES 16 A 306 THR ASP THR THR ILE THR VAL ASN VAL LEU ALA TRP LEU +SEQRES 17 A 306 TYR ALA ALA VAL ILE ASN GLY ASP ARG TRP PHE LEU ASN +SEQRES 18 A 306 ARG PHE THR THR THR LEU ASN ASP PHE ASN LEU VAL ALA +SEQRES 19 A 306 MET LYS TYR ASN TYR GLU PRO LEU THR GLN ASP HIS VAL +SEQRES 20 A 306 ASP ILE LEU GLY PRO LEU SER ALA GLN THR GLY ILE ALA +SEQRES 21 A 306 VAL LEU ASP MET CYS ALA SER LEU LYS GLU LEU LEU GLN +SEQRES 22 A 306 ASN GLY MET ASN GLY ARG THR ILE LEU GLY SER ALA LEU +SEQRES 23 A 306 LEU GLU ASP GLU PHE THR PRO PHE ASP VAL VAL ARG GLN +SEQRES 24 A 306 CYS SER GLY VAL THR PHE GLN +HETNAM RZJ 1-METHYL-3,4-DIHYDRO-2~{H}-QUINOLINE-7-SULFONAMIDE +HETNAM DMS DIMETHYL SULFOXIDE +FORMUL 2 RZJ C10 H14 N2 O2 S +FORMUL 3 DMS 4(C2 H6 O S) +FORMUL 7 HOH *334(H2 O) +HELIX 1 AA1 SER A 10 GLY A 15 1 6 +HELIX 2 AA2 HIS A 41 CYS A 44 5 4 +HELIX 3 AA3 ASN A 53 ILE A 59 1 7 +HELIX 4 AA4 ARG A 60 LYS A 61 5 2 +HELIX 5 AA5 SER A 62 HIS A 64 5 3 +HELIX 6 AA6 ILE A 200 ASN A 214 1 15 +HELIX 7 AA7 THR A 226 TYR A 237 1 12 +HELIX 8 AA8 THR A 243 LEU A 250 1 8 +HELIX 9 AA9 LEU A 250 GLY A 258 1 9 +HELIX 10 AB1 ALA A 260 GLY A 275 1 16 +HELIX 11 AB2 THR A 292 GLY A 302 1 11 +SHEET 1 AA1 7 VAL A 73 LEU A 75 0 +SHEET 2 AA1 7 PHE A 66 ALA A 70 -1 N VAL A 68 O LEU A 75 +SHEET 3 AA1 7 MET A 17 CYS A 22 -1 N GLN A 19 O GLN A 69 +SHEET 4 AA1 7 THR A 25 LEU A 32 -1 O LEU A 27 N VAL A 20 +SHEET 5 AA1 7 VAL A 35 PRO A 39 -1 O TYR A 37 N LEU A 30 +SHEET 6 AA1 7 VAL A 86 VAL A 91 -1 O LEU A 89 N VAL A 36 +SHEET 7 AA1 7 VAL A 77 GLN A 83 -1 N SER A 81 O LYS A 88 +SHEET 1 AA2 5 LYS A 100 PHE A 103 0 +SHEET 2 AA2 5 CYS A 156 GLU A 166 1 O PHE A 159 N LYS A 102 +SHEET 3 AA2 5 VAL A 148 ASP A 153 -1 N ASN A 151 O SER A 158 +SHEET 4 AA2 5 THR A 111 TYR A 118 -1 N SER A 113 O PHE A 150 +SHEET 5 AA2 5 SER A 121 ALA A 129 -1 O CYS A 128 N PHE A 112 +SHEET 1 AA3 3 LYS A 100 PHE A 103 0 +SHEET 2 AA3 3 CYS A 156 GLU A 166 1 O PHE A 159 N LYS A 102 +SHEET 3 AA3 3 HIS A 172 THR A 175 -1 O ALA A 173 N MET A 165 +SITE 1 AC1 10 HIS A 41 MET A 49 GLU A 166 PRO A 168 +SITE 2 AC1 10 ASP A 187 ARG A 188 GLN A 189 PRO A 252 +SITE 3 AC1 10 HOH A1159 HOH A1259 +SITE 1 AC2 8 GLN A 74 ARG A 76 ARG A 222 PHE A 223 +SITE 2 AC2 8 THR A 224 ASP A 263 HOH A1158 HOH A1283 +SITE 1 AC3 6 MET A 6 PHE A 8 SER A 123 GLN A 127 +SITE 2 AC3 6 ARG A 298 HOH A1235 +SITE 1 AC4 2 GLY A 15 MET A 17 +SITE 1 AC5 5 PHE A 140 LEU A 141 HIS A 163 MET A 165 +SITE 2 AC5 5 GLU A 166 +CRYST1 113.780 53.490 44.450 90.00 101.70 90.00 C 1 2 1 4 +ORIGX1 1.000000 0.000000 0.000000 0.00000 +ORIGX2 0.000000 1.000000 0.000000 0.00000 +ORIGX3 0.000000 0.000000 1.000000 0.00000 +SCALE1 0.008789 0.000000 0.001820 0.00000 +SCALE2 0.000000 0.018695 0.000000 0.00000 +SCALE3 0.000000 0.000000 0.022975 0.00000 + + $$$$ diff --git a/example_files/ligand/5R82_lig.sdf b/example_files/ligand/5R82_lig.sdf index 15735bc..ba4261c 100644 --- a/example_files/ligand/5R82_lig.sdf +++ b/example_files/ligand/5R82_lig.sdf @@ -1,5 +1,5 @@ target - PyMOL2.1 3D 0 + PyMOL3.0 3D 0 11 11 0 0 0 0 0 0 0 0999 V2000 9.0161 -0.0370 27.7721 C 0 0 0 0 0 0 0 0 0 0 0 0 @@ -25,4 +25,99 @@ target 7 10 4 0 0 0 0 10 11 4 0 0 0 0 M END +> +HEADER HYDROLASE/HYDROLASE INHIBITOR 03-MAR-20 XXXX +TITLE PANDDA ANALYSIS GROUP DEPOSITION -- CRYSTAL STRUCTURE OF COVID-19 MAIN +TITLE 2 PROTEASE IN COMPLEX WITH Z219104216 +KEYWDS SGC - DIAMOND I04-1 FRAGMENT SCREENING, PANDDA, XCHEMEXPLORER, +KEYWDS 2 HYDROLASE-HYDROLASE INHIBITOR COMPLEX +EXPDTA X-RAY DIFFRACTION +AUTHOR D.FEARON,A.J.POWELL,A.DOUANGAMATH,C.D.OWEN,C.WILD,T.KROJER,P.LUKACIK, +AUTHOR 2 C.M.STRAIN-DAMERELL,M.A.WALSH,F.VON DELFT +JRNL AUTH A.DOUANGAMATH,D.FEARON,P.GEHRTZ,T.KROJER,P.LUKACIK,C.D.OWEN, +JRNL AUTH 2 E.RESNICK,C.STRAIN-DAMERELL,A.AIMON,P.ABRANYI-BALOGH, +JRNL AUTH 3 J.BRANDAO-NETO,A.CARBERY,G.DAVISON,A.DIAS,T.D.DOWNES, +JRNL AUTH 4 L.DUNNETT,M.FAIRHEAD,J.D.FIRTH,S.P.JONES,A.KEELEY, +JRNL AUTH 5 G.M.KESERU,H.F.KLEIN,M.P.MARTIN,M.E.M.NOBLE,P.O'BRIEN, +JRNL AUTH 6 A.POWELL,R.N.REDDI,R.SKYNER,M.SNEE,M.J.WARING,C.WILD, +JRNL AUTH 7 N.LONDON,F.VON DELFT,M.A.WALSH +JRNL TITL CRYSTALLOGRAPHIC AND ELECTROPHILIC FRAGMENT SCREENING OF THE +JRNL TITL 2 SARS-COV-2 MAIN PROTEASE. +JRNL REF NAT COMMUN V. 11 5047 2020 +JRNL REFN ESSN 2041-1723 +JRNL PMID 33028810 +JRNL DOI 10.1038/S41467-020-18709-W +SEQRES 1 A 306 SER GLY PHE ARG LYS MET ALA PHE PRO SER GLY LYS VAL +SEQRES 2 A 306 GLU GLY CYS MET VAL GLN VAL THR CYS GLY THR THR THR +SEQRES 3 A 306 LEU ASN GLY LEU TRP LEU ASP ASP VAL VAL TYR CYS PRO +SEQRES 4 A 306 ARG HIS VAL ILE CYS THR SER GLU ASP MET LEU ASN PRO +SEQRES 5 A 306 ASN TYR GLU ASP LEU LEU ILE ARG LYS SER ASN HIS ASN +SEQRES 6 A 306 PHE LEU VAL GLN ALA GLY ASN VAL GLN LEU ARG VAL ILE +SEQRES 7 A 306 GLY HIS SER MET GLN ASN CYS VAL LEU LYS LEU LYS VAL +SEQRES 8 A 306 ASP THR ALA ASN PRO LYS THR PRO LYS TYR LYS PHE VAL +SEQRES 9 A 306 ARG ILE GLN PRO GLY GLN THR PHE SER VAL LEU ALA CYS +SEQRES 10 A 306 TYR ASN GLY SER PRO SER GLY VAL TYR GLN CYS ALA MET +SEQRES 11 A 306 ARG PRO ASN PHE THR ILE LYS GLY SER PHE LEU ASN GLY +SEQRES 12 A 306 SER CYS GLY SER VAL GLY PHE ASN ILE ASP TYR ASP CYS +SEQRES 13 A 306 VAL SER PHE CYS TYR MET HIS HIS MET GLU LEU PRO THR +SEQRES 14 A 306 GLY VAL HIS ALA GLY THR ASP LEU GLU GLY ASN PHE TYR +SEQRES 15 A 306 GLY PRO PHE VAL ASP ARG GLN THR ALA GLN ALA ALA GLY +SEQRES 16 A 306 THR ASP THR THR ILE THR VAL ASN VAL LEU ALA TRP LEU +SEQRES 17 A 306 TYR ALA ALA VAL ILE ASN GLY ASP ARG TRP PHE LEU ASN +SEQRES 18 A 306 ARG PHE THR THR THR LEU ASN ASP PHE ASN LEU VAL ALA +SEQRES 19 A 306 MET LYS TYR ASN TYR GLU PRO LEU THR GLN ASP HIS VAL +SEQRES 20 A 306 ASP ILE LEU GLY PRO LEU SER ALA GLN THR GLY ILE ALA +SEQRES 21 A 306 VAL LEU ASP MET CYS ALA SER LEU LYS GLU LEU LEU GLN +SEQRES 22 A 306 ASN GLY MET ASN GLY ARG THR ILE LEU GLY SER ALA LEU +SEQRES 23 A 306 LEU GLU ASP GLU PHE THR PRO PHE ASP VAL VAL ARG GLN +SEQRES 24 A 306 CYS SER GLY VAL THR PHE GLN +HETNAM RZS 6-(ETHYLAMINO)PYRIDINE-3-CARBONITRILE +HETNAM DMS DIMETHYL SULFOXIDE +FORMUL 2 RZS C8 H9 N3 +FORMUL 3 DMS 4(C2 H6 O S) +FORMUL 7 HOH *332(H2 O) +HELIX 1 AA1 SER A 10 GLY A 15 1 6 +HELIX 2 AA2 HIS A 41 CYS A 44 5 4 +HELIX 3 AA3 GLU A 47 ASN A 51 5 5 +HELIX 4 AA4 ASN A 53 ARG A 60 1 8 +HELIX 5 AA5 LYS A 61 HIS A 64 5 4 +HELIX 6 AA6 ILE A 200 ASN A 214 1 15 +HELIX 7 AA7 THR A 226 TYR A 237 1 12 +HELIX 8 AA8 THR A 243 LEU A 250 1 8 +HELIX 9 AA9 LEU A 250 GLY A 258 1 9 +HELIX 10 AB1 ALA A 260 GLY A 275 1 16 +HELIX 11 AB2 THR A 292 GLY A 302 1 11 +SHEET 1 AA1 7 VAL A 73 LEU A 75 0 +SHEET 2 AA1 7 PHE A 66 ALA A 70 -1 N ALA A 70 O VAL A 73 +SHEET 3 AA1 7 MET A 17 CYS A 22 -1 N THR A 21 O LEU A 67 +SHEET 4 AA1 7 THR A 25 LEU A 32 -1 O LEU A 27 N VAL A 20 +SHEET 5 AA1 7 VAL A 35 PRO A 39 -1 O TYR A 37 N LEU A 30 +SHEET 6 AA1 7 VAL A 86 VAL A 91 -1 O LEU A 89 N VAL A 36 +SHEET 7 AA1 7 VAL A 77 GLN A 83 -1 N GLN A 83 O VAL A 86 +SHEET 1 AA2 5 LYS A 100 PHE A 103 0 +SHEET 2 AA2 5 CYS A 156 GLU A 166 1 O VAL A 157 N LYS A 100 +SHEET 3 AA2 5 VAL A 148 ASP A 153 -1 N ASN A 151 O SER A 158 +SHEET 4 AA2 5 THR A 111 TYR A 118 -1 N SER A 113 O PHE A 150 +SHEET 5 AA2 5 SER A 121 ALA A 129 -1 O SER A 123 N ALA A 116 +SHEET 1 AA3 3 LYS A 100 PHE A 103 0 +SHEET 2 AA3 3 CYS A 156 GLU A 166 1 O VAL A 157 N LYS A 100 +SHEET 3 AA3 3 HIS A 172 THR A 175 -1 O ALA A 173 N MET A 165 +SITE 1 AC1 8 HIS A 41 MET A 49 HIS A 164 MET A 165 +SITE 2 AC1 8 ASP A 187 GLN A 189 DMS A1005 HOH A1171 +SITE 1 AC2 7 GLN A 74 LEU A 75 ARG A 76 THR A 224 +SITE 2 AC2 7 ASP A 263 HOH A1182 HOH A1257 +SITE 1 AC3 5 MET A 6 PHE A 8 SER A 123 GLN A 127 +SITE 2 AC3 5 ARG A 298 +SITE 1 AC4 4 GLY A 15 MET A 17 LYS A 97 HOH A1256 +SITE 1 AC5 8 GLU A 166 PRO A 168 ARG A 188 GLN A 189 +SITE 2 AC5 8 THR A 190 GLN A 192 RZS A1001 HOH A1175 +CRYST1 112.665 52.848 44.468 90.00 102.97 90.00 C 1 2 1 4 +ORIGX1 1.000000 0.000000 0.000000 0.00000 +ORIGX2 0.000000 1.000000 0.000000 0.00000 +ORIGX3 0.000000 0.000000 1.000000 0.00000 +SCALE1 0.008876 0.000000 0.002044 0.00000 +SCALE2 0.000000 0.018922 0.000000 0.00000 +SCALE3 0.000000 0.000000 0.023076 0.00000 + + $$$$ diff --git a/example_files/ligand/5R83_lig.sdf b/example_files/ligand/5R83_lig.sdf index 3651b91..9918bb8 100644 --- a/example_files/ligand/5R83_lig.sdf +++ b/example_files/ligand/5R83_lig.sdf @@ -1,5 +1,5 @@ target - PyMOL2.1 3D 0 + PyMOL3.0 3D 0 16 17 0 0 0 0 0 0 0 0999 V2000 9.4094 -1.0606 22.3873 N 0 0 0 0 0 0 0 0 0 0 0 0 @@ -36,4 +36,97 @@ target 14 15 4 0 0 0 0 7 16 4 0 0 0 0 M END +> +HEADER HYDROLASE/HYDROLASE INHIBITOR 03-MAR-20 XXXX +TITLE PANDDA ANALYSIS GROUP DEPOSITION -- CRYSTAL STRUCTURE OF SARS-COV-2 +TITLE 2 MAIN PROTEASE IN COMPLEX WITH Z44592329 +KEYWDS SGC - DIAMOND I04-1 FRAGMENT SCREENING, PANDDA, XCHEMEXPLORER, +KEYWDS 2 HYDROLASE-HYDROLASE INHIBITOR COMPLEX +EXPDTA X-RAY DIFFRACTION +AUTHOR D.FEARON,A.J.POWELL,A.DOUANGAMATH,C.D.OWEN,C.WILD,T.KROJER,P.LUKACIK, +AUTHOR 2 C.M.STRAIN-DAMERELL,M.A.WALSH,F.VON DELFT +JRNL AUTH A.DOUANGAMATH,D.FEARON,P.GEHRTZ,T.KROJER,P.LUKACIK,C.D.OWEN, +JRNL AUTH 2 E.RESNICK,C.STRAIN-DAMERELL,A.AIMON,P.ABRANYI-BALOGH, +JRNL AUTH 3 J.BRANDAO-NETO,A.CARBERY,G.DAVISON,A.DIAS,T.D.DOWNES, +JRNL AUTH 4 L.DUNNETT,M.FAIRHEAD,J.D.FIRTH,S.P.JONES,A.KEELEY, +JRNL AUTH 5 G.M.KESERU,H.F.KLEIN,M.P.MARTIN,M.E.M.NOBLE,P.O'BRIEN, +JRNL AUTH 6 A.POWELL,R.N.REDDI,R.SKYNER,M.SNEE,M.J.WARING,C.WILD, +JRNL AUTH 7 N.LONDON,F.VON DELFT,M.A.WALSH +JRNL TITL CRYSTALLOGRAPHIC AND ELECTROPHILIC FRAGMENT SCREENING OF THE +JRNL TITL 2 SARS-COV-2 MAIN PROTEASE. +JRNL REF NAT COMMUN V. 11 5047 2020 +JRNL REFN ESSN 2041-1723 +JRNL PMID 33028810 +JRNL DOI 10.1038/S41467-020-18709-W +SEQRES 1 A 306 SER GLY PHE ARG LYS MET ALA PHE PRO SER GLY LYS VAL +SEQRES 2 A 306 GLU GLY CYS MET VAL GLN VAL THR CYS GLY THR THR THR +SEQRES 3 A 306 LEU ASN GLY LEU TRP LEU ASP ASP VAL VAL TYR CYS PRO +SEQRES 4 A 306 ARG HIS VAL ILE CYS THR SER GLU ASP MET LEU ASN PRO +SEQRES 5 A 306 ASN TYR GLU ASP LEU LEU ILE ARG LYS SER ASN HIS ASN +SEQRES 6 A 306 PHE LEU VAL GLN ALA GLY ASN VAL GLN LEU ARG VAL ILE +SEQRES 7 A 306 GLY HIS SER MET GLN ASN CYS VAL LEU LYS LEU LYS VAL +SEQRES 8 A 306 ASP THR ALA ASN PRO LYS THR PRO LYS TYR LYS PHE VAL +SEQRES 9 A 306 ARG ILE GLN PRO GLY GLN THR PHE SER VAL LEU ALA CYS +SEQRES 10 A 306 TYR ASN GLY SER PRO SER GLY VAL TYR GLN CYS ALA MET +SEQRES 11 A 306 ARG PRO ASN PHE THR ILE LYS GLY SER PHE LEU ASN GLY +SEQRES 12 A 306 SER CYS GLY SER VAL GLY PHE ASN ILE ASP TYR ASP CYS +SEQRES 13 A 306 VAL SER PHE CYS TYR MET HIS HIS MET GLU LEU PRO THR +SEQRES 14 A 306 GLY VAL HIS ALA GLY THR ASP LEU GLU GLY ASN PHE TYR +SEQRES 15 A 306 GLY PRO PHE VAL ASP ARG GLN THR ALA GLN ALA ALA GLY +SEQRES 16 A 306 THR ASP THR THR ILE THR VAL ASN VAL LEU ALA TRP LEU +SEQRES 17 A 306 TYR ALA ALA VAL ILE ASN GLY ASP ARG TRP PHE LEU ASN +SEQRES 18 A 306 ARG PHE THR THR THR LEU ASN ASP PHE ASN LEU VAL ALA +SEQRES 19 A 306 MET LYS TYR ASN TYR GLU PRO LEU THR GLN ASP HIS VAL +SEQRES 20 A 306 ASP ILE LEU GLY PRO LEU SER ALA GLN THR GLY ILE ALA +SEQRES 21 A 306 VAL LEU ASP MET CYS ALA SER LEU LYS GLU LEU LEU GLN +SEQRES 22 A 306 ASN GLY MET ASN GLY ARG THR ILE LEU GLY SER ALA LEU +SEQRES 23 A 306 LEU GLU ASP GLU PHE THR PRO PHE ASP VAL VAL ARG GLN +SEQRES 24 A 306 CYS SER GLY VAL THR PHE GLN +HETNAM DMS DIMETHYL SULFOXIDE +HETNAM K0G N-PHENYL-N'-PYRIDIN-3-YLUREA +FORMUL 2 DMS 3(C2 H6 O S) +FORMUL 5 K0G C12 H11 N3 O +FORMUL 6 HOH *328(H2 O) +HELIX 1 AA1 SER A 10 GLY A 15 1 6 +HELIX 2 AA2 HIS A 41 CYS A 44 5 4 +HELIX 3 AA3 GLU A 47 ASN A 51 5 5 +HELIX 4 AA4 ASN A 53 ARG A 60 1 8 +HELIX 5 AA5 LYS A 61 HIS A 64 5 4 +HELIX 6 AA6 ILE A 200 ASN A 214 1 15 +HELIX 7 AA7 THR A 226 TYR A 237 1 12 +HELIX 8 AA8 THR A 243 LEU A 250 1 8 +HELIX 9 AA9 LEU A 250 GLY A 258 1 9 +HELIX 10 AB1 ALA A 260 GLY A 275 1 16 +HELIX 11 AB2 THR A 292 GLY A 302 1 11 +SHEET 1 AA1 7 VAL A 73 LEU A 75 0 +SHEET 2 AA1 7 PHE A 66 ALA A 70 -1 N VAL A 68 O LEU A 75 +SHEET 3 AA1 7 MET A 17 CYS A 22 -1 N THR A 21 O LEU A 67 +SHEET 4 AA1 7 THR A 25 LEU A 32 -1 O LEU A 27 N VAL A 20 +SHEET 5 AA1 7 VAL A 35 PRO A 39 -1 O TYR A 37 N LEU A 30 +SHEET 6 AA1 7 VAL A 86 VAL A 91 -1 O LEU A 89 N VAL A 36 +SHEET 7 AA1 7 VAL A 77 GLN A 83 -1 N GLN A 83 O VAL A 86 +SHEET 1 AA2 5 LYS A 100 PHE A 103 0 +SHEET 2 AA2 5 CYS A 156 GLU A 166 1 O PHE A 159 N LYS A 102 +SHEET 3 AA2 5 VAL A 148 ASP A 153 -1 N ASN A 151 O SER A 158 +SHEET 4 AA2 5 THR A 111 TYR A 118 -1 N SER A 113 O PHE A 150 +SHEET 5 AA2 5 SER A 121 ALA A 129 -1 O SER A 123 N ALA A 116 +SHEET 1 AA3 3 LYS A 100 PHE A 103 0 +SHEET 2 AA3 3 CYS A 156 GLU A 166 1 O PHE A 159 N LYS A 102 +SHEET 3 AA3 3 HIS A 172 THR A 175 -1 O ALA A 173 N MET A 165 +SITE 1 AC1 8 GLN A 74 LEU A 75 ARG A 76 PHE A 223 +SITE 2 AC1 8 THR A 224 ASP A 263 HOH A 528 HOH A 608 +SITE 1 AC2 4 MET A 6 SER A 123 GLN A 127 ARG A 298 +SITE 1 AC3 4 GLY A 15 MET A 17 LYS A 97 HOH A 647 +SITE 1 AC4 11 MET A 49 PHE A 140 LEU A 141 ASN A 142 +SITE 2 AC4 11 HIS A 163 HIS A 164 MET A 165 GLU A 166 +SITE 3 AC4 11 ARG A 188 GLN A 189 HOH A 547 +CRYST1 112.267 52.583 44.535 90.00 102.95 90.00 C 1 2 1 4 +ORIGX1 1.000000 0.000000 0.000000 0.00000 +ORIGX2 0.000000 1.000000 0.000000 0.00000 +ORIGX3 0.000000 0.000000 1.000000 0.00000 +SCALE1 0.008907 0.000000 0.002048 0.00000 +SCALE2 0.000000 0.019018 0.000000 0.00000 +SCALE3 0.000000 0.000000 0.023040 0.00000 + + $$$$ diff --git a/example_files/ligand/5R84_lig.sdf b/example_files/ligand/5R84_lig.sdf index 1cd8b46..66379cd 100644 --- a/example_files/ligand/5R84_lig.sdf +++ b/example_files/ligand/5R84_lig.sdf @@ -1,5 +1,5 @@ target - PyMOL2.1 3D 0 + PyMOL3.0 3D 0 16 17 0 0 0 0 0 0 0 0999 V2000 7.5974 -0.3658 21.3429 N 0 0 0 0 0 0 0 0 0 0 0 0 @@ -36,4 +36,97 @@ target 13 14 4 0 0 0 0 14 15 4 0 0 0 0 M END +> +HEADER HYDROLASE/HYDROLASE INHIBITOR 03-MAR-20 XXXX +TITLE PANDDA ANALYSIS GROUP DEPOSITION -- CRYSTAL STRUCTURE OF COVID-19 MAIN +TITLE 2 PROTEASE IN COMPLEX WITH Z31792168 +KEYWDS SGC - DIAMOND I04-1 FRAGMENT SCREENING, PANDDA, XCHEMEXPLORER, +KEYWDS 2 HYDROLASE-HYDROLASE INHIBITOR COMPLEX +EXPDTA X-RAY DIFFRACTION +AUTHOR D.FEARON,A.J.POWELL,A.DOUANGAMATH,C.D.OWEN,C.WILD,T.KROJER,P.LUKACIK, +AUTHOR 2 C.M.STRAIN-DAMERELL,M.A.WALSH,F.VON DELFT +JRNL AUTH A.DOUANGAMATH,D.FEARON,P.GEHRTZ,T.KROJER,P.LUKACIK,C.D.OWEN, +JRNL AUTH 2 E.RESNICK,C.STRAIN-DAMERELL,A.AIMON,P.ABRANYI-BALOGH, +JRNL AUTH 3 J.BRANDAO-NETO,A.CARBERY,G.DAVISON,A.DIAS,T.D.DOWNES, +JRNL AUTH 4 L.DUNNETT,M.FAIRHEAD,J.D.FIRTH,S.P.JONES,A.KEELEY, +JRNL AUTH 5 G.M.KESERU,H.F.KLEIN,M.P.MARTIN,M.E.M.NOBLE,P.O'BRIEN, +JRNL AUTH 6 A.POWELL,R.N.REDDI,R.SKYNER,M.SNEE,M.J.WARING,C.WILD, +JRNL AUTH 7 N.LONDON,F.VON DELFT,M.A.WALSH +JRNL TITL CRYSTALLOGRAPHIC AND ELECTROPHILIC FRAGMENT SCREENING OF THE +JRNL TITL 2 SARS-COV-2 MAIN PROTEASE. +JRNL REF NAT COMMUN V. 11 5047 2020 +JRNL REFN ESSN 2041-1723 +JRNL PMID 33028810 +JRNL DOI 10.1038/S41467-020-18709-W +SEQRES 1 A 306 SER GLY PHE ARG LYS MET ALA PHE PRO SER GLY LYS VAL +SEQRES 2 A 306 GLU GLY CYS MET VAL GLN VAL THR CYS GLY THR THR THR +SEQRES 3 A 306 LEU ASN GLY LEU TRP LEU ASP ASP VAL VAL TYR CYS PRO +SEQRES 4 A 306 ARG HIS VAL ILE CYS THR SER GLU ASP MET LEU ASN PRO +SEQRES 5 A 306 ASN TYR GLU ASP LEU LEU ILE ARG LYS SER ASN HIS ASN +SEQRES 6 A 306 PHE LEU VAL GLN ALA GLY ASN VAL GLN LEU ARG VAL ILE +SEQRES 7 A 306 GLY HIS SER MET GLN ASN CYS VAL LEU LYS LEU LYS VAL +SEQRES 8 A 306 ASP THR ALA ASN PRO LYS THR PRO LYS TYR LYS PHE VAL +SEQRES 9 A 306 ARG ILE GLN PRO GLY GLN THR PHE SER VAL LEU ALA CYS +SEQRES 10 A 306 TYR ASN GLY SER PRO SER GLY VAL TYR GLN CYS ALA MET +SEQRES 11 A 306 ARG PRO ASN PHE THR ILE LYS GLY SER PHE LEU ASN GLY +SEQRES 12 A 306 SER CYS GLY SER VAL GLY PHE ASN ILE ASP TYR ASP CYS +SEQRES 13 A 306 VAL SER PHE CYS TYR MET HIS HIS MET GLU LEU PRO THR +SEQRES 14 A 306 GLY VAL HIS ALA GLY THR ASP LEU GLU GLY ASN PHE TYR +SEQRES 15 A 306 GLY PRO PHE VAL ASP ARG GLN THR ALA GLN ALA ALA GLY +SEQRES 16 A 306 THR ASP THR THR ILE THR VAL ASN VAL LEU ALA TRP LEU +SEQRES 17 A 306 TYR ALA ALA VAL ILE ASN GLY ASP ARG TRP PHE LEU ASN +SEQRES 18 A 306 ARG PHE THR THR THR LEU ASN ASP PHE ASN LEU VAL ALA +SEQRES 19 A 306 MET LYS TYR ASN TYR GLU PRO LEU THR GLN ASP HIS VAL +SEQRES 20 A 306 ASP ILE LEU GLY PRO LEU SER ALA GLN THR GLY ILE ALA +SEQRES 21 A 306 VAL LEU ASP MET CYS ALA SER LEU LYS GLU LEU LEU GLN +SEQRES 22 A 306 ASN GLY MET ASN GLY ARG THR ILE LEU GLY SER ALA LEU +SEQRES 23 A 306 LEU GLU ASP GLU PHE THR PRO PHE ASP VAL VAL ARG GLN +SEQRES 24 A 306 CYS SER GLY VAL THR PHE GLN +HETNAM GWS 2-CYCLOHEXYL-~{N}-PYRIDIN-3-YL-ETHANAMIDE +HETNAM DMS DIMETHYL SULFOXIDE +FORMUL 2 GWS C13 H18 N2 O +FORMUL 3 DMS 3(C2 H6 O S) +FORMUL 6 HOH *324(H2 O) +HELIX 1 AA1 SER A 10 GLY A 15 1 6 +HELIX 2 AA2 HIS A 41 CYS A 44 5 4 +HELIX 3 AA3 ASN A 53 ARG A 60 1 8 +HELIX 4 AA4 LYS A 61 PHE A 66 5 6 +HELIX 5 AA5 ILE A 200 ASN A 214 1 15 +HELIX 6 AA6 THR A 226 TYR A 237 1 12 +HELIX 7 AA7 THR A 243 LEU A 250 1 8 +HELIX 8 AA8 LEU A 250 GLY A 258 1 9 +HELIX 9 AA9 ALA A 260 GLY A 275 1 16 +HELIX 10 AB1 THR A 292 GLY A 302 1 11 +SHEET 1 AA1 7 VAL A 73 LEU A 75 0 +SHEET 2 AA1 7 LEU A 67 ALA A 70 -1 N VAL A 68 O LEU A 75 +SHEET 3 AA1 7 MET A 17 CYS A 22 -1 N GLN A 19 O GLN A 69 +SHEET 4 AA1 7 THR A 25 LEU A 32 -1 O LEU A 27 N VAL A 20 +SHEET 5 AA1 7 VAL A 35 PRO A 39 -1 O TYR A 37 N LEU A 30 +SHEET 6 AA1 7 VAL A 86 VAL A 91 -1 O LEU A 89 N VAL A 36 +SHEET 7 AA1 7 VAL A 77 GLN A 83 -1 N SER A 81 O LYS A 88 +SHEET 1 AA2 5 LYS A 100 PHE A 103 0 +SHEET 2 AA2 5 CYS A 156 GLU A 166 1 O VAL A 157 N LYS A 100 +SHEET 3 AA2 5 VAL A 148 ASP A 153 -1 N ASP A 153 O CYS A 156 +SHEET 4 AA2 5 THR A 111 TYR A 118 -1 N SER A 113 O PHE A 150 +SHEET 5 AA2 5 SER A 121 ALA A 129 -1 O TYR A 126 N VAL A 114 +SHEET 1 AA3 3 LYS A 100 PHE A 103 0 +SHEET 2 AA3 3 CYS A 156 GLU A 166 1 O VAL A 157 N LYS A 100 +SHEET 3 AA3 3 HIS A 172 THR A 175 -1 O THR A 175 N MET A 162 +SITE 1 AC1 11 HIS A 41 PHE A 140 LEU A 141 ASN A 142 +SITE 2 AC1 11 CYS A 145 HIS A 163 HIS A 164 MET A 165 +SITE 3 AC1 11 GLU A 166 ARG A 188 GLN A 189 +SITE 1 AC2 8 GLN A 74 LEU A 75 ARG A 76 THR A 224 +SITE 2 AC2 8 ASP A 263 HOH A1225 HOH A1254 HOH A1410 +SITE 1 AC3 5 MET A 6 PHE A 8 SER A 123 GLN A 127 +SITE 2 AC3 5 ARG A 298 +SITE 1 AC4 3 GLY A 15 MET A 17 LYS A 97 +CRYST1 113.146 53.167 44.267 90.00 101.66 90.00 C 1 2 1 4 +ORIGX1 1.000000 0.000000 0.000000 0.00000 +ORIGX2 0.000000 1.000000 0.000000 0.00000 +ORIGX3 0.000000 0.000000 1.000000 0.00000 +SCALE1 0.008838 0.000000 0.001824 0.00000 +SCALE2 0.000000 0.018809 0.000000 0.00000 +SCALE3 0.000000 0.000000 0.023066 0.00000 + + $$$$ diff --git a/example_files/ligand/5RE4_lig.sdf b/example_files/ligand/5RE4_lig.sdf index 1f7b3c6..370d801 100644 --- a/example_files/ligand/5RE4_lig.sdf +++ b/example_files/ligand/5RE4_lig.sdf @@ -1,5 +1,5 @@ target - PyMOL2.1 3D 0 + PyMOL3.0 3D 0 11 11 0 0 0 0 0 0 0 0999 V2000 10.2243 -0.7737 22.5041 C 0 0 0 0 0 0 0 0 0 0 0 0 @@ -25,4 +25,98 @@ target 9 10 4 0 0 0 0 10 11 1 0 0 0 0 M END +> +HEADER HYDROLASE/HYDROLASE INHIBITOR 15-MAR-20 XXXX +TITLE PANDDA ANALYSIS GROUP DEPOSITION -- CRYSTAL STRUCTURE OF SARS-COV-2 +TITLE 2 MAIN PROTEASE IN COMPLEX WITH Z1129283193 +KEYWDS SGC - DIAMOND I04-1 FRAGMENT SCREENING, PANDDA, XCHEMEXPLORER, +KEYWDS 2 HYDROLASE-HYDROLASE INHIBITOR COMPLEX +EXPDTA X-RAY DIFFRACTION +AUTHOR D.FEARON,C.D.OWEN,A.DOUANGAMATH,P.LUKACIK,A.J.POWELL,C.M.STRAIN- +AUTHOR 2 DAMERELL,E.RESNICK,T.KROJER,P.GEHRTZ,C.WILD,A.AIMON,J.BRANDAO-NETO, +AUTHOR 3 A.CARBERY,L.DUNNETT,R.SKYNER,M.SNEE,N.LONDON,M.A.WALSH,F.VON DELFT +JRNL AUTH A.DOUANGAMATH,D.FEARON,P.GEHRTZ,T.KROJER,P.LUKACIK,C.D.OWEN, +JRNL AUTH 2 E.RESNICK,C.STRAIN-DAMERELL,A.AIMON,P.ABRANYI-BALOGH, +JRNL AUTH 3 J.BRANDAO-NETO,A.CARBERY,G.DAVISON,A.DIAS,T.D.DOWNES, +JRNL AUTH 4 L.DUNNETT,M.FAIRHEAD,J.D.FIRTH,S.P.JONES,A.KEELEY, +JRNL AUTH 5 G.M.KESERU,H.F.KLEIN,M.P.MARTIN,M.E.M.NOBLE,P.O'BRIEN, +JRNL AUTH 6 A.POWELL,R.N.REDDI,R.SKYNER,M.SNEE,M.J.WARING,C.WILD, +JRNL AUTH 7 N.LONDON,F.VON DELFT,M.A.WALSH +JRNL TITL CRYSTALLOGRAPHIC AND ELECTROPHILIC FRAGMENT SCREENING OF THE +JRNL TITL 2 SARS-COV-2 MAIN PROTEASE. +JRNL REF NAT COMMUN V. 11 5047 2020 +JRNL REFN ESSN 2041-1723 +JRNL PMID 33028810 +JRNL DOI 10.1038/S41467-020-18709-W +SEQRES 1 A 306 SER GLY PHE ARG LYS MET ALA PHE PRO SER GLY LYS VAL +SEQRES 2 A 306 GLU GLY CYS MET VAL GLN VAL THR CYS GLY THR THR THR +SEQRES 3 A 306 LEU ASN GLY LEU TRP LEU ASP ASP VAL VAL TYR CYS PRO +SEQRES 4 A 306 ARG HIS VAL ILE CYS THR SER GLU ASP MET LEU ASN PRO +SEQRES 5 A 306 ASN TYR GLU ASP LEU LEU ILE ARG LYS SER ASN HIS ASN +SEQRES 6 A 306 PHE LEU VAL GLN ALA GLY ASN VAL GLN LEU ARG VAL ILE +SEQRES 7 A 306 GLY HIS SER MET GLN ASN CYS VAL LEU LYS LEU LYS VAL +SEQRES 8 A 306 ASP THR ALA ASN PRO LYS THR PRO LYS TYR LYS PHE VAL +SEQRES 9 A 306 ARG ILE GLN PRO GLY GLN THR PHE SER VAL LEU ALA CYS +SEQRES 10 A 306 TYR ASN GLY SER PRO SER GLY VAL TYR GLN CYS ALA MET +SEQRES 11 A 306 ARG PRO ASN PHE THR ILE LYS GLY SER PHE LEU ASN GLY +SEQRES 12 A 306 SER CYS GLY SER VAL GLY PHE ASN ILE ASP TYR ASP CYS +SEQRES 13 A 306 VAL SER PHE CYS TYR MET HIS HIS MET GLU LEU PRO THR +SEQRES 14 A 306 GLY VAL HIS ALA GLY THR ASP LEU GLU GLY ASN PHE TYR +SEQRES 15 A 306 GLY PRO PHE VAL ASP ARG GLN THR ALA GLN ALA ALA GLY +SEQRES 16 A 306 THR ASP THR THR ILE THR VAL ASN VAL LEU ALA TRP LEU +SEQRES 17 A 306 TYR ALA ALA VAL ILE ASN GLY ASP ARG TRP PHE LEU ASN +SEQRES 18 A 306 ARG PHE THR THR THR LEU ASN ASP PHE ASN LEU VAL ALA +SEQRES 19 A 306 MET LYS TYR ASN TYR GLU PRO LEU THR GLN ASP HIS VAL +SEQRES 20 A 306 ASP ILE LEU GLY PRO LEU SER ALA GLN THR GLY ILE ALA +SEQRES 21 A 306 VAL LEU ASP MET CYS ALA SER LEU LYS GLU LEU LEU GLN +SEQRES 22 A 306 ASN GLY MET ASN GLY ARG THR ILE LEU GLY SER ALA LEU +SEQRES 23 A 306 LEU GLU ASP GLU PHE THR PRO PHE ASP VAL VAL ARG GLN +SEQRES 24 A 306 CYS SER GLY VAL THR PHE GLN +HETNAM DMS DIMETHYL SULFOXIDE +HETNAM SZY N-(4-METHYLPYRIDIN-3-YL)ACETAMIDE +FORMUL 2 DMS 3(C2 H6 O S) +FORMUL 5 SZY C8 H10 N2 O +FORMUL 6 HOH *335(H2 O) +HELIX 1 AA1 SER A 10 GLY A 15 1 6 +HELIX 2 AA2 HIS A 41 CYS A 44 5 4 +HELIX 3 AA3 GLU A 47 ASN A 51 5 5 +HELIX 4 AA4 ASN A 53 ARG A 60 1 8 +HELIX 5 AA5 LYS A 61 HIS A 64 5 4 +HELIX 6 AA6 ILE A 200 ASN A 214 1 15 +HELIX 7 AA7 THR A 226 TYR A 237 1 12 +HELIX 8 AA8 THR A 243 GLY A 258 1 16 +HELIX 9 AA9 ALA A 260 GLY A 275 1 16 +HELIX 10 AB1 THR A 292 GLY A 302 1 11 +SHEET 1 AA1 7 VAL A 73 LEU A 75 0 +SHEET 2 AA1 7 PHE A 66 ALA A 70 -1 N VAL A 68 O LEU A 75 +SHEET 3 AA1 7 MET A 17 CYS A 22 -1 N THR A 21 O LEU A 67 +SHEET 4 AA1 7 THR A 25 LEU A 32 -1 O LEU A 27 N VAL A 20 +SHEET 5 AA1 7 VAL A 35 PRO A 39 -1 O TYR A 37 N LEU A 30 +SHEET 6 AA1 7 VAL A 86 VAL A 91 -1 O LEU A 89 N VAL A 36 +SHEET 7 AA1 7 VAL A 77 GLN A 83 -1 N GLN A 83 O VAL A 86 +SHEET 1 AA2 5 LYS A 100 PHE A 103 0 +SHEET 2 AA2 5 CYS A 156 GLU A 166 1 O VAL A 157 N LYS A 100 +SHEET 3 AA2 5 VAL A 148 ASP A 153 -1 N ASN A 151 O SER A 158 +SHEET 4 AA2 5 THR A 111 TYR A 118 -1 N SER A 113 O PHE A 150 +SHEET 5 AA2 5 SER A 121 ALA A 129 -1 O SER A 123 N ALA A 116 +SHEET 1 AA3 3 LYS A 100 PHE A 103 0 +SHEET 2 AA3 3 CYS A 156 GLU A 166 1 O VAL A 157 N LYS A 100 +SHEET 3 AA3 3 HIS A 172 THR A 175 -1 O ALA A 173 N MET A 165 +SITE 1 AC1 10 GLN A 74 LEU A 75 ARG A 76 ARG A 222 +SITE 2 AC1 10 PHE A 223 THR A 224 ASP A 263 HOH A 567 +SITE 3 AC1 10 HOH A 575 HOH A 773 +SITE 1 AC2 6 MET A 6 PHE A 8 SER A 123 GLN A 127 +SITE 2 AC2 6 ARG A 298 HOH A 662 +SITE 1 AC3 4 GLY A 15 MET A 17 LYS A 97 HOH A 612 +SITE 1 AC4 7 PHE A 140 LEU A 141 ASN A 142 CYS A 145 +SITE 2 AC4 7 HIS A 163 MET A 165 GLU A 166 +CRYST1 111.643 52.352 44.369 90.00 103.08 90.00 C 1 2 1 4 +ORIGX1 1.000000 0.000000 0.000000 0.00000 +ORIGX2 0.000000 1.000000 0.000000 0.00000 +ORIGX3 0.000000 0.000000 1.000000 0.00000 +SCALE1 0.008957 0.000000 0.002082 0.00000 +SCALE2 0.000000 0.019101 0.000000 0.00000 +SCALE3 0.000000 0.000000 0.023139 0.00000 + + $$$$ diff --git a/example_files/ligand/5RE5_lig.sdf b/example_files/ligand/5RE5_lig.sdf index e69de29..00f3c9f 100644 --- a/example_files/ligand/5RE5_lig.sdf +++ b/example_files/ligand/5RE5_lig.sdf @@ -0,0 +1,138 @@ +target + PyMOL3.0 3D 0 + + 18 19 0 0 0 0 0 0 0 0999 V2000 + 23.8838 -16.7138 25.7799 N 0 0 0 0 0 0 0 0 0 0 0 0 + 24.6744 -17.8396 25.2968 C 0 0 0 0 0 0 0 0 0 0 0 0 + 25.7632 -17.9821 25.7329 O 0 0 0 0 0 0 0 0 0 0 0 0 + 24.1564 -18.8778 24.2895 C 0 0 0 0 0 0 0 0 0 0 0 0 + 24.8987 -18.9081 23.0096 C 0 0 0 0 0 0 0 0 0 0 0 0 + 24.4988 -20.1279 22.1720 C 0 0 0 0 0 0 0 0 0 0 0 0 + 23.0970 -20.6876 22.3578 N 0 0 0 0 0 0 0 0 0 0 0 0 + 22.2822 -20.0907 23.4673 C 0 0 0 0 0 0 0 0 0 0 0 0 + 22.7343 -18.7273 23.9612 C 0 0 0 0 0 0 0 0 0 0 0 0 + 22.4883 -21.7609 21.5722 C 0 0 0 0 0 0 0 0 0 0 0 0 + 21.3834 -22.1166 21.8297 O 0 0 0 0 0 0 0 0 0 0 0 0 + 23.1970 -22.3911 20.4762 N 0 0 0 0 0 0 0 0 0 0 0 0 + 22.5921 -23.4454 19.6948 C 0 0 0 0 0 0 0 0 0 0 0 0 + 22.4911 -23.2674 18.3282 C 0 0 0 0 0 0 0 0 0 0 0 0 + 21.9273 -24.2607 17.5396 C 0 0 0 0 0 0 0 0 0 0 0 0 + 21.4674 -25.4339 18.1276 C 0 0 0 0 0 0 0 0 0 0 0 0 + 21.5703 -25.6119 19.5022 C 0 0 0 0 0 0 0 0 0 0 0 0 + 22.1332 -24.6177 20.2868 C 0 0 0 0 0 0 0 0 0 0 0 0 + 1 2 1 0 0 0 0 + 2 3 2 0 0 0 0 + 2 4 1 0 0 0 0 + 4 5 1 0 0 0 0 + 4 9 1 0 0 0 0 + 5 6 1 0 0 0 0 + 6 7 1 0 0 0 0 + 7 8 1 0 0 0 0 + 8 9 1 0 0 0 0 + 7 10 1 0 0 0 0 + 10 11 2 0 0 0 0 + 10 12 1 0 0 0 0 + 12 13 1 0 0 0 0 + 13 14 4 0 0 0 0 + 13 18 4 0 0 0 0 + 14 15 4 0 0 0 0 + 15 16 4 0 0 0 0 + 16 17 4 0 0 0 0 + 17 18 4 0 0 0 0 +M END +> +HEADER HYDROLASE/HYDROLASE INHIBITOR 15-MAR-20 XXXX +TITLE PANDDA ANALYSIS GROUP DEPOSITION -- CRYSTAL STRUCTURE OF SARS-COV-2 +TITLE 2 MAIN PROTEASE IN COMPLEX WITH Z33545544 +KEYWDS SGC - DIAMOND I04-1 FRAGMENT SCREENING, PANDDA, XCHEMEXPLORER, +KEYWDS 2 HYDROLASE-HYDROLASE INHIBITOR COMPLEX +EXPDTA X-RAY DIFFRACTION +AUTHOR D.FEARON,C.D.OWEN,A.DOUANGAMATH,P.LUKACIK,A.J.POWELL,C.M.STRAIN- +AUTHOR 2 DAMERELL,E.RESNICK,T.KROJER,P.GEHRTZ,C.WILD,A.AIMON,J.BRANDAO-NETO, +AUTHOR 3 A.CARBERY,L.DUNNETT,R.SKYNER,M.SNEE,N.LONDON,M.A.WALSH,F.VON DELFT +JRNL AUTH A.DOUANGAMATH,D.FEARON,P.GEHRTZ,T.KROJER,P.LUKACIK,C.D.OWEN, +JRNL AUTH 2 E.RESNICK,C.STRAIN-DAMERELL,A.AIMON,P.ABRANYI-BALOGH, +JRNL AUTH 3 J.BRANDAO-NETO,A.CARBERY,G.DAVISON,A.DIAS,T.D.DOWNES, +JRNL AUTH 4 L.DUNNETT,M.FAIRHEAD,J.D.FIRTH,S.P.JONES,A.KEELEY, +JRNL AUTH 5 G.M.KESERU,H.F.KLEIN,M.P.MARTIN,M.E.M.NOBLE,P.O'BRIEN, +JRNL AUTH 6 A.POWELL,R.N.REDDI,R.SKYNER,M.SNEE,M.J.WARING,C.WILD, +JRNL AUTH 7 N.LONDON,F.VON DELFT,M.A.WALSH +JRNL TITL CRYSTALLOGRAPHIC AND ELECTROPHILIC FRAGMENT SCREENING OF THE +JRNL TITL 2 SARS-COV-2 MAIN PROTEASE. +JRNL REF NAT COMMUN V. 11 5047 2020 +JRNL REFN ESSN 2041-1723 +JRNL PMID 33028810 +JRNL DOI 10.1038/S41467-020-18709-W +SEQRES 1 A 306 SER GLY PHE ARG LYS MET ALA PHE PRO SER GLY LYS VAL +SEQRES 2 A 306 GLU GLY CYS MET VAL GLN VAL THR CYS GLY THR THR THR +SEQRES 3 A 306 LEU ASN GLY LEU TRP LEU ASP ASP VAL VAL TYR CYS PRO +SEQRES 4 A 306 ARG HIS VAL ILE CYS THR SER GLU ASP MET LEU ASN PRO +SEQRES 5 A 306 ASN TYR GLU ASP LEU LEU ILE ARG LYS SER ASN HIS ASN +SEQRES 6 A 306 PHE LEU VAL GLN ALA GLY ASN VAL GLN LEU ARG VAL ILE +SEQRES 7 A 306 GLY HIS SER MET GLN ASN CYS VAL LEU LYS LEU LYS VAL +SEQRES 8 A 306 ASP THR ALA ASN PRO LYS THR PRO LYS TYR LYS PHE VAL +SEQRES 9 A 306 ARG ILE GLN PRO GLY GLN THR PHE SER VAL LEU ALA CYS +SEQRES 10 A 306 TYR ASN GLY SER PRO SER GLY VAL TYR GLN CYS ALA MET +SEQRES 11 A 306 ARG PRO ASN PHE THR ILE LYS GLY SER PHE LEU ASN GLY +SEQRES 12 A 306 SER CYS GLY SER VAL GLY PHE ASN ILE ASP TYR ASP CYS +SEQRES 13 A 306 VAL SER PHE CYS TYR MET HIS HIS MET GLU LEU PRO THR +SEQRES 14 A 306 GLY VAL HIS ALA GLY THR ASP LEU GLU GLY ASN PHE TYR +SEQRES 15 A 306 GLY PRO PHE VAL ASP ARG GLN THR ALA GLN ALA ALA GLY +SEQRES 16 A 306 THR ASP THR THR ILE THR VAL ASN VAL LEU ALA TRP LEU +SEQRES 17 A 306 TYR ALA ALA VAL ILE ASN GLY ASP ARG TRP PHE LEU ASN +SEQRES 18 A 306 ARG PHE THR THR THR LEU ASN ASP PHE ASN LEU VAL ALA +SEQRES 19 A 306 MET LYS TYR ASN TYR GLU PRO LEU THR GLN ASP HIS VAL +SEQRES 20 A 306 ASP ILE LEU GLY PRO LEU SER ALA GLN THR GLY ILE ALA +SEQRES 21 A 306 VAL LEU ASP MET CYS ALA SER LEU LYS GLU LEU LEU GLN +SEQRES 22 A 306 ASN GLY MET ASN GLY ARG THR ILE LEU GLY SER ALA LEU +SEQRES 23 A 306 LEU GLU ASP GLU PHE THR PRO PHE ASP VAL VAL ARG GLN +SEQRES 24 A 306 CYS SER GLY VAL THR PHE GLN +HETNAM DMS DIMETHYL SULFOXIDE +HETNAM T0J N~1~-PHENYLPIPERIDINE-1,4-DICARBOXAMIDE +FORMUL 2 DMS 3(C2 H6 O S) +FORMUL 5 T0J C13 H17 N3 O2 +FORMUL 6 HOH *330(H2 O) +HELIX 1 AA1 SER A 10 GLY A 15 1 6 +HELIX 2 AA2 HIS A 41 CYS A 44 5 4 +HELIX 3 AA3 GLU A 47 ASN A 51 5 5 +HELIX 4 AA4 ASN A 53 ARG A 60 1 8 +HELIX 5 AA5 LYS A 61 HIS A 64 5 4 +HELIX 6 AA6 ILE A 200 ASN A 214 1 15 +HELIX 7 AA7 THR A 226 TYR A 237 1 12 +HELIX 8 AA8 THR A 243 GLY A 258 1 16 +HELIX 9 AA9 ALA A 260 GLY A 275 1 16 +HELIX 10 AB1 THR A 292 GLY A 302 1 11 +SHEET 1 AA1 7 VAL A 73 LEU A 75 0 +SHEET 2 AA1 7 PHE A 66 ALA A 70 -1 N VAL A 68 O LEU A 75 +SHEET 3 AA1 7 MET A 17 CYS A 22 -1 N GLN A 19 O GLN A 69 +SHEET 4 AA1 7 THR A 25 LEU A 32 -1 O LEU A 27 N VAL A 20 +SHEET 5 AA1 7 VAL A 35 PRO A 39 -1 O TYR A 37 N LEU A 30 +SHEET 6 AA1 7 VAL A 86 VAL A 91 -1 O LEU A 89 N VAL A 36 +SHEET 7 AA1 7 VAL A 77 GLN A 83 -1 N ILE A 78 O LYS A 90 +SHEET 1 AA2 5 LYS A 100 PHE A 103 0 +SHEET 2 AA2 5 CYS A 156 GLU A 166 1 O PHE A 159 N LYS A 102 +SHEET 3 AA2 5 VAL A 148 ASP A 153 -1 N GLY A 149 O TYR A 161 +SHEET 4 AA2 5 THR A 111 TYR A 118 -1 N SER A 113 O PHE A 150 +SHEET 5 AA2 5 SER A 121 ALA A 129 -1 O CYS A 128 N PHE A 112 +SHEET 1 AA3 3 LYS A 100 PHE A 103 0 +SHEET 2 AA3 3 CYS A 156 GLU A 166 1 O PHE A 159 N LYS A 102 +SHEET 3 AA3 3 HIS A 172 THR A 175 -1 O ALA A 173 N MET A 165 +SITE 1 AC1 9 GLN A 74 ARG A 76 ARG A 222 PHE A 223 +SITE 2 AC1 9 THR A 224 ASP A 263 HOH A 514 HOH A 581 +SITE 3 AC1 9 HOH A 809 +SITE 1 AC2 6 MET A 6 PHE A 8 SER A 123 GLN A 127 +SITE 2 AC2 6 ARG A 298 HOH A 668 +SITE 1 AC3 4 GLY A 15 MET A 17 LYS A 97 HOH A 614 +SITE 1 AC4 10 ILE A 78 HIS A 80 PRO A 184 VAL A 186 +SITE 2 AC4 10 ARG A 188 ALA A 193 HOH A 508 HOH A 529 +SITE 3 AC4 10 HOH A 568 HOH A 658 +CRYST1 112.530 52.810 44.520 90.00 102.15 90.00 C 1 2 1 4 +ORIGX1 1.000000 0.000000 0.000000 0.00000 +ORIGX2 0.000000 1.000000 0.000000 0.00000 +ORIGX3 0.000000 0.000000 1.000000 0.00000 +SCALE1 0.008887 0.000000 0.001913 0.00000 +SCALE2 0.000000 0.018936 0.000000 0.00000 +SCALE3 0.000000 0.000000 0.022976 0.00000 + + +$$$$ diff --git a/example_files/receptor/5R7Y_A.pdb b/example_files/receptor/5R7Y_A.pdb index aeea056..6b551b3 100644 --- a/example_files/receptor/5R7Y_A.pdb +++ b/example_files/receptor/5R7Y_A.pdb @@ -1,3 +1,4 @@ +CRYST1 112.463 52.731 44.299 90.00 102.81 90.00 C 1 2 1 1 ATOM 1 N SER A 1 -2.551 4.208 -17.081 1.00 31.04 N ATOM 2 CA SER A 1 -2.151 5.509 -16.492 1.00 30.79 C ATOM 3 C SER A 1 -2.458 5.531 -14.988 1.00 29.60 C @@ -2345,4 +2346,5 @@ ATOM 2344 O THR A 304 5.965 -10.009 -10.128 1.00 50.10 O ATOM 2345 CB THR A 304 4.391 -9.282 -12.698 1.00 50.75 C ATOM 2346 CG2 THR A 304 3.299 -8.384 -13.235 1.00 48.40 C ATOM 2347 OG1 THR A 304 5.086 -9.911 -13.775 1.00 51.21 O +TER END diff --git a/example_files/receptor/5R7Z_A.pdb b/example_files/receptor/5R7Z_A.pdb index fc672b5..153544f 100644 --- a/example_files/receptor/5R7Z_A.pdb +++ b/example_files/receptor/5R7Z_A.pdb @@ -1,3 +1,4 @@ +CRYST1 112.090 52.513 44.384 90.00 102.94 90.00 C 1 2 1 1 ATOM 1 N SER A 1 -2.253 4.513 -16.964 1.00 36.71 N ATOM 2 CA SER A 1 -2.036 5.839 -16.336 1.00 38.02 C ATOM 3 C SER A 1 -2.457 5.782 -14.858 1.00 34.86 C @@ -2269,7 +2270,7 @@ ATOM 2268 O PHE A 294 11.405 1.243 -10.604 1.00 21.72 O ATOM 2269 CB PHE A 294 14.458 1.108 -9.105 1.00 27.55 C ATOM 2270 CG PHE A 294 15.925 1.216 -9.471 1.00 36.34 C ATOM 2271 CD1 PHE A 294 16.366 0.960 -10.766 1.00 40.69 C -ATOM 2272 CD2 PHE A 294 16.885 1.573 -8.527 1.00 42.51 C +ATOM 2272 CD2 PHE A 294 16.885 1.573 -8.526 1.00 42.51 C ATOM 2273 CE1 PHE A 294 17.712 1.058 -11.107 1.00 39.89 C ATOM 2274 CE2 PHE A 294 18.228 1.681 -8.877 1.00 42.66 C ATOM 2275 CZ PHE A 294 18.641 1.409 -10.163 1.00 38.68 C @@ -2345,4 +2346,5 @@ ATOM 2344 O THR A 304 6.280 -10.020 -10.296 1.00 48.15 O ATOM 2345 CB THR A 304 4.411 -9.142 -12.655 1.00 52.70 C ATOM 2346 CG2 THR A 304 3.273 -8.250 -13.102 1.00 52.97 C ATOM 2347 OG1 THR A 304 4.979 -9.756 -13.812 1.00 52.97 O +TER END diff --git a/example_files/receptor/5R80_A.pdb b/example_files/receptor/5R80_A.pdb index f6bf877..390fa8e 100644 --- a/example_files/receptor/5R80_A.pdb +++ b/example_files/receptor/5R80_A.pdb @@ -1,3 +1,4 @@ +CRYST1 112.891 53.030 44.352 90.00 102.46 90.00 C 1 2 1 1 ATOM 1 N SER A 1 -2.200 4.307 -16.794 1.00 46.95 N ATOM 2 CA SER A 1 -1.990 5.656 -16.222 1.00 45.24 C ATOM 3 C SER A 1 -2.444 5.678 -14.758 1.00 44.79 C @@ -346,7 +347,7 @@ ATOM 345 CB SER A 46 7.389 -3.660 30.829 0.64 66.87 C ATOM 346 OG SER A 46 7.200 -2.252 30.822 0.64 68.89 O ATOM 347 N GLU A 47 10.627 -3.070 32.427 0.64 72.65 N ATOM 348 CA GLU A 47 11.447 -2.700 33.620 0.64 74.91 C -ATOM 349 C GLU A 47 12.921 -3.039 33.346 0.64 72.02 C +ATOM 349 C GLU A 47 12.921 -3.039 33.345 0.64 72.02 C ATOM 350 O GLU A 47 13.795 -2.389 33.949 0.64 75.08 O ATOM 351 CB GLU A 47 10.988 -3.410 34.897 0.64 77.65 C ATOM 352 CG GLU A 47 11.105 -4.922 34.827 0.64 79.97 C @@ -1170,7 +1171,7 @@ ATOM 1169 N ASP A 153 12.132 -9.029 -6.100 1.00 55.73 N ATOM 1170 CA ASP A 153 12.664 -9.101 -7.491 1.00 58.61 C ATOM 1171 C ASP A 153 12.233 -10.442 -8.109 1.00 57.78 C ATOM 1172 O ASP A 153 12.830 -11.497 -7.766 1.00 55.79 O -ATOM 1173 CB ASP A 153 14.183 -8.902 -7.511 1.00 66.34 C +ATOM 1173 CB ASP A 153 14.183 -8.902 -7.512 1.00 66.34 C ATOM 1174 CG ASP A 153 14.783 -8.732 -8.901 1.00 74.79 C ATOM 1175 OD1 ASP A 153 15.599 -7.793 -9.086 1.00 76.74 O ATOM 1176 OD2 ASP A 153 14.454 -9.552 -9.786 1.00 82.51 O1- @@ -1869,7 +1870,7 @@ ATOM 1868 C GLU A 240 20.765 16.238 -1.328 1.00 38.46 C ATOM 1869 O GLU A 240 20.129 16.503 -2.348 1.00 31.92 O ATOM 1870 CB GLU A 240 19.798 14.173 -0.292 1.00 46.94 C ATOM 1871 CG GLU A 240 19.285 13.478 0.954 1.00 53.56 C -ATOM 1872 CD GLU A 240 20.346 13.216 2.016 1.00 63.84 C +ATOM 1872 CD GLU A 240 20.345 13.216 2.016 1.00 63.84 C ATOM 1873 OE1 GLU A 240 21.321 12.495 1.701 1.00 69.51 O ATOM 1874 OE2 GLU A 240 20.205 13.739 3.153 1.00 63.01 O1- ATOM 1875 N PRO A 241 22.106 16.414 -1.287 1.00 40.92 N @@ -1879,7 +1880,7 @@ ATOM 1878 O PRO A 241 22.571 14.652 -3.247 1.00 40.94 O ATOM 1879 CB PRO A 241 24.286 17.013 -1.977 1.00 43.30 C ATOM 1880 CG PRO A 241 24.172 17.023 -0.465 1.00 42.08 C ATOM 1881 CD PRO A 241 23.008 16.104 -0.168 1.00 42.20 C -ATOM 1882 N LEU A 242 22.497 16.301 -4.792 1.00 35.46 N +ATOM 1882 N LEU A 242 22.498 16.301 -4.792 1.00 35.46 N ATOM 1883 CA LEU A 242 22.388 15.460 -6.012 1.00 37.69 C ATOM 1884 C LEU A 242 23.791 15.275 -6.609 1.00 35.64 C ATOM 1885 O LEU A 242 24.514 16.261 -6.746 1.00 32.62 O @@ -2273,7 +2274,7 @@ ATOM 2272 CD2 PHE A 294 16.875 1.363 -8.714 1.00 81.42 C ATOM 2273 CE1 PHE A 294 17.594 1.231 -11.371 1.00 76.06 C ATOM 2274 CE2 PHE A 294 18.214 1.439 -9.088 1.00 82.38 C ATOM 2275 CZ PHE A 294 18.573 1.368 -10.415 1.00 76.40 C -ATOM 2276 N ASP A 295 11.418 2.508 -8.725 1.00 35.15 N +ATOM 2276 N ASP A 295 11.418 2.508 -8.724 1.00 35.15 N ATOM 2277 CA ASP A 295 9.964 2.406 -8.429 1.00 36.27 C ATOM 2278 C ASP A 295 9.177 3.058 -9.566 1.00 36.79 C ATOM 2279 O ASP A 295 8.138 2.499 -9.981 1.00 34.74 O @@ -2345,4 +2346,5 @@ ATOM 2344 O THR A 304 6.516 -9.859 -10.406 1.00 69.72 O ATOM 2345 CB THR A 304 4.475 -9.064 -12.612 1.00 60.95 C ATOM 2346 CG2 THR A 304 3.390 -8.217 -13.244 1.00 54.96 C ATOM 2347 OG1 THR A 304 5.048 -9.901 -13.617 1.00 57.55 O +TER END diff --git a/example_files/receptor/5R81_A.pdb b/example_files/receptor/5R81_A.pdb index b0d302e..ed4935d 100644 --- a/example_files/receptor/5R81_A.pdb +++ b/example_files/receptor/5R81_A.pdb @@ -1,3 +1,4 @@ +CRYST1 113.780 53.490 44.450 90.00 101.70 90.00 C 1 2 1 1 ATOM 1 N SER A 1 -2.486 4.326 -16.804 1.00 47.25 N ATOM 2 CA SER A 1 -2.096 5.622 -16.223 1.00 47.20 C ATOM 3 C SER A 1 -2.520 5.679 -14.752 1.00 47.41 C @@ -1454,7 +1455,7 @@ ATOM 1453 NE ARG A 188 19.737 2.599 28.590 1.00 67.65 N ATOM 1454 CZ ARG A 188 20.434 3.606 29.103 1.00 68.10 C ATOM 1455 NH1 ARG A 188 21.282 4.295 28.355 1.00 73.70 N1+ ATOM 1456 NH2 ARG A 188 20.260 3.923 30.374 1.00 68.85 N -ATOM 1457 N GLN A 189 15.099 1.580 26.095 1.00 44.54 N +ATOM 1457 N GLN A 189 15.100 1.580 26.095 1.00 44.54 N ATOM 1458 CA GLN A 189 14.096 2.641 26.374 1.00 46.16 C ATOM 1459 C GLN A 189 14.823 3.842 26.990 1.00 47.11 C ATOM 1460 O GLN A 189 14.860 3.965 28.233 1.00 45.49 O @@ -2289,7 +2290,7 @@ ATOM 2288 CB VAL A 296 9.382 6.393 -11.402 1.00 37.03 C ATOM 2289 CG1 VAL A 296 8.614 7.130 -12.498 1.00 41.75 C ATOM 2290 CG2 VAL A 296 9.374 7.182 -10.110 1.00 37.30 C ATOM 2291 N VAL A 297 10.067 3.617 -12.819 1.00 39.87 N -ATOM 2292 CA VAL A 297 10.233 2.758 -14.031 1.00 43.37 C +ATOM 2292 CA VAL A 297 10.233 2.758 -14.030 1.00 43.37 C ATOM 2293 C VAL A 297 9.330 1.524 -13.887 1.00 44.82 C ATOM 2294 O VAL A 297 8.592 1.223 -14.825 1.00 43.13 O ATOM 2295 CB VAL A 297 11.692 2.316 -14.231 1.00 43.52 C @@ -2345,4 +2346,5 @@ ATOM 2344 O THR A 304 6.385 -9.895 -10.613 1.00 86.68 O ATOM 2345 CB THR A 304 4.377 -9.001 -12.801 1.00 81.99 C ATOM 2346 CG2 THR A 304 3.354 -8.159 -13.532 1.00 73.88 C ATOM 2347 OG1 THR A 304 4.956 -9.905 -13.743 1.00 80.19 O +TER END diff --git a/example_files/receptor/5R82_A.pdb b/example_files/receptor/5R82_A.pdb index 4e795bd..69ec974 100644 --- a/example_files/receptor/5R82_A.pdb +++ b/example_files/receptor/5R82_A.pdb @@ -1,3 +1,4 @@ +CRYST1 112.665 52.848 44.468 90.00 102.97 90.00 C 1 2 1 1 ATOM 1 N SER A 1 -2.425 4.371 -16.996 1.00 27.76 N ATOM 2 CA SER A 1 -2.098 5.674 -16.363 1.00 27.12 C ATOM 3 C SER A 1 -2.423 5.635 -14.866 1.00 26.29 C @@ -44,7 +45,7 @@ ATOM 43 CA MET A 6 2.341 0.845 -4.237 1.00 18.37 C ATOM 44 C MET A 6 3.307 0.029 -3.388 1.00 16.52 C ATOM 45 O MET A 6 4.515 0.249 -3.524 1.00 16.69 O ATOM 46 CB MET A 6 2.537 0.509 -5.719 1.00 22.51 C -ATOM 47 CG MET A 6 1.985 -0.802 -6.100 1.00 29.50 C +ATOM 47 CG MET A 6 1.985 -0.802 -6.099 1.00 29.50 C ATOM 48 SD MET A 6 2.217 -0.953 -7.883 1.00 35.52 S ATOM 49 CE MET A 6 0.869 0.062 -8.460 1.00 31.18 C ATOM 50 N ALA A 7 2.772 -0.930 -2.635 1.00 16.51 N @@ -2345,4 +2346,5 @@ ATOM 2344 O THR A 304 5.996 -10.120 -10.203 1.00 38.46 O ATOM 2345 CB THR A 304 4.313 -9.340 -12.683 1.00 38.12 C ATOM 2346 CG2 THR A 304 3.324 -8.444 -13.393 1.00 34.89 C ATOM 2347 OG1 THR A 304 5.036 -10.136 -13.628 1.00 36.00 O +TER END diff --git a/example_files/receptor/5R83_A.pdb b/example_files/receptor/5R83_A.pdb index 0b41ce9..fb4a07e 100644 --- a/example_files/receptor/5R83_A.pdb +++ b/example_files/receptor/5R83_A.pdb @@ -1,3 +1,4 @@ +CRYST1 112.267 52.583 44.535 90.00 102.95 90.00 C 1 2 1 1 ATOM 1 N SER A 1 -2.364 4.464 -16.840 1.00 28.73 N ATOM 2 CA SER A 1 -2.150 5.799 -16.280 1.00 30.74 C ATOM 3 C SER A 1 -2.493 5.810 -14.782 1.00 28.33 C @@ -1474,7 +1475,7 @@ ATOM 1473 N ALA A 191 16.144 8.320 25.839 1.00 41.53 N ATOM 1474 CA ALA A 191 16.214 9.507 24.954 1.00 44.62 C ATOM 1475 C ALA A 191 17.118 9.194 23.773 1.00 38.69 C ATOM 1476 O ALA A 191 18.341 9.094 23.959 1.00 44.00 O -ATOM 1477 CB ALA A 191 16.749 10.717 25.697 1.00 46.61 C +ATOM 1477 CB ALA A 191 16.749 10.717 25.698 1.00 46.61 C ATOM 1478 N GLN A 192 16.518 9.056 22.600 1.00 34.69 N ATOM 1479 CA GLN A 192 17.261 9.010 21.324 1.00 31.02 C ATOM 1480 C GLN A 192 16.565 9.955 20.348 1.00 32.39 C @@ -1799,7 +1800,7 @@ ATOM 1798 CA LEU A 232 23.092 25.370 -3.229 1.00 24.22 C ATOM 1799 C LEU A 232 21.648 25.563 -2.760 1.00 24.79 C ATOM 1800 O LEU A 232 21.421 25.715 -1.534 1.00 23.19 O ATOM 1801 CB LEU A 232 23.546 26.624 -3.973 1.00 28.36 C -ATOM 1802 CG LEU A 232 25.031 26.747 -4.285 1.00 31.18 C +ATOM 1802 CG LEU A 232 25.030 26.747 -4.285 1.00 31.18 C ATOM 1803 CD1 LEU A 232 25.292 28.145 -4.843 1.00 34.80 C ATOM 1804 CD2 LEU A 232 25.886 26.475 -3.054 1.00 31.94 C ATOM 1805 N VAL A 233 20.699 25.544 -3.700 1.00 25.72 N @@ -2345,4 +2346,5 @@ ATOM 2344 O THR A 304 6.239 -10.045 -10.478 1.00 48.62 O ATOM 2345 CB THR A 304 4.333 -9.166 -12.740 1.00 43.23 C ATOM 2346 CG2 THR A 304 3.264 -8.286 -13.347 1.00 40.12 C ATOM 2347 OG1 THR A 304 4.962 -9.915 -13.782 1.00 42.40 O +TER END diff --git a/example_files/receptor/5R84_A.pdb b/example_files/receptor/5R84_A.pdb index db63b4e..eae6e86 100644 --- a/example_files/receptor/5R84_A.pdb +++ b/example_files/receptor/5R84_A.pdb @@ -1,3 +1,4 @@ +CRYST1 113.146 53.167 44.267 90.00 101.66 90.00 C 1 2 1 1 ATOM 1 N SER A 1 -2.317 4.286 -16.861 1.00 45.33 N ATOM 2 CA SER A 1 -2.008 5.592 -16.274 1.00 43.61 C ATOM 3 C SER A 1 -2.396 5.608 -14.795 1.00 43.25 C @@ -471,7 +472,7 @@ ATOM 470 O LYS A 61 18.023 -19.635 27.839 1.00 35.49 O ATOM 471 CB LYS A 61 16.041 -17.156 27.808 1.00 36.26 C ATOM 472 CG LYS A 61 15.438 -15.889 28.381 1.00 39.16 C ATOM 473 CD LYS A 61 13.993 -16.011 28.770 1.00 38.62 C -ATOM 474 CE LYS A 61 13.586 -14.963 29.778 1.00 40.98 C +ATOM 474 CE LYS A 61 13.586 -14.963 29.777 1.00 40.98 C ATOM 475 NZ LYS A 61 12.114 -14.811 29.835 1.00 44.46 N1+ ATOM 476 N SER A 62 15.902 -20.460 27.993 1.00 36.41 N ATOM 477 CA SER A 62 16.121 -21.791 27.401 1.00 36.48 C @@ -881,7 +882,7 @@ ATOM 880 CZ PHE A 112 12.010 0.062 5.590 1.00 37.91 C ATOM 881 N SER A 113 8.550 -2.297 1.093 1.00 30.41 N ATOM 882 CA SER A 113 7.209 -2.634 1.618 1.00 31.63 C ATOM 883 C SER A 113 7.339 -3.169 3.051 1.00 33.39 C -ATOM 884 O SER A 113 8.281 -3.980 3.337 1.00 32.47 O +ATOM 884 O SER A 113 8.281 -3.981 3.337 1.00 32.47 O ATOM 885 CB SER A 113 6.527 -3.570 0.721 1.00 32.58 C ATOM 886 OG SER A 113 6.280 -2.923 -0.507 1.00 37.14 O ATOM 887 N VAL A 114 6.479 -2.652 3.929 1.00 29.79 N @@ -1487,7 +1488,7 @@ ATOM 1486 OE1 GLN A 192 18.680 4.917 20.345 1.00 39.21 O ATOM 1487 N ALA A 193 17.332 11.122 19.963 1.00 55.71 N ATOM 1488 CA ALA A 193 16.889 12.084 18.935 1.00 59.01 C ATOM 1489 C ALA A 193 17.383 11.549 17.586 1.00 56.40 C -ATOM 1490 O ALA A 193 18.478 10.957 17.551 1.00 50.74 O +ATOM 1490 O ALA A 193 18.479 10.957 17.551 1.00 50.74 O ATOM 1491 CB ALA A 193 17.391 13.471 19.266 1.00 66.38 C ATOM 1492 N ALA A 194 16.547 11.641 16.553 1.00 54.69 N ATOM 1493 CA ALA A 194 16.917 11.369 15.144 1.00 55.38 C @@ -2345,4 +2346,5 @@ ATOM 2344 O THR A 304 6.656 -10.084 -10.471 1.00 81.27 O ATOM 2345 CB THR A 304 4.638 -9.043 -12.588 1.00 65.59 C ATOM 2346 CG2 THR A 304 3.549 -8.097 -13.046 1.00 64.47 C ATOM 2347 OG1 THR A 304 5.125 -9.758 -13.727 1.00 66.86 O +TER END diff --git a/example_files/receptor/5R8T_A.pdb b/example_files/receptor/5R8T_A.pdb index 5c67d7f..efc2876 100644 --- a/example_files/receptor/5R8T_A.pdb +++ b/example_files/receptor/5R8T_A.pdb @@ -1,3 +1,4 @@ +CRYST1 112.207 52.596 44.631 90.00 102.99 90.00 C 1 2 1 1 ATOM 1 N SER A 1 -2.449 4.397 -16.868 1.00 27.40 N ATOM 2 CA SER A 1 -2.136 5.703 -16.309 1.00 26.70 C ATOM 3 C SER A 1 -2.457 5.701 -14.811 1.00 24.24 C @@ -2345,4 +2346,5 @@ ATOM 2344 O THR A 304 6.246 -10.030 -10.356 1.00 42.41 O ATOM 2345 CB THR A 304 4.370 -9.297 -12.783 1.00 36.28 C ATOM 2346 CG2 THR A 304 3.272 -8.414 -13.332 1.00 33.34 C ATOM 2347 OG1 THR A 304 5.026 -9.963 -13.865 1.00 36.52 O +TER END diff --git a/example_files/receptor/5RE4_A.pdb b/example_files/receptor/5RE4_A.pdb index 7dfd6eb..c43c538 100644 --- a/example_files/receptor/5RE4_A.pdb +++ b/example_files/receptor/5RE4_A.pdb @@ -1,3 +1,4 @@ +CRYST1 111.643 52.352 44.369 90.00 103.08 90.00 C 1 2 1 1 ATOM 1 N SER A 1 -2.271 4.450 -16.793 1.00 45.33 N ATOM 2 CA SER A 1 -1.992 5.778 -16.186 1.00 45.41 C ATOM 3 C SER A 1 -2.492 5.815 -14.737 1.00 42.53 C @@ -512,7 +513,7 @@ ATOM 511 O PHE A 66 9.731 -20.877 22.271 1.00 30.37 O ATOM 512 CB PHE A 66 11.868 -18.870 22.381 1.00 25.60 C ATOM 513 CG PHE A 66 12.987 -18.078 22.986 1.00 24.51 C ATOM 514 CD1 PHE A 66 12.934 -16.689 22.993 1.00 24.30 C -ATOM 515 CD2 PHE A 66 14.075 -18.715 23.560 1.00 24.29 C +ATOM 515 CD2 PHE A 66 14.075 -18.715 23.559 1.00 24.29 C ATOM 516 CE1 PHE A 66 13.971 -15.943 23.532 1.00 24.12 C ATOM 517 CE2 PHE A 66 15.097 -17.967 24.130 1.00 24.83 C ATOM 518 CZ PHE A 66 15.043 -16.586 24.106 1.00 24.76 C @@ -2345,4 +2346,5 @@ ATOM 2344 O THR A 304 6.432 -9.925 -10.150 1.00 59.34 O ATOM 2345 CB THR A 304 4.530 -9.026 -12.404 1.00 64.99 C ATOM 2346 CG2 THR A 304 3.494 -8.147 -13.071 1.00 66.19 C ATOM 2347 OG1 THR A 304 5.095 -9.886 -13.391 1.00 69.62 O +TER END diff --git a/example_files/receptor/5RE5_A.pdb b/example_files/receptor/5RE5_A.pdb index 64b0708..984facd 100644 --- a/example_files/receptor/5RE5_A.pdb +++ b/example_files/receptor/5RE5_A.pdb @@ -1,3 +1,4 @@ +CRYST1 112.530 52.810 44.520 90.00 102.15 90.00 C 1 2 1 1 ATOM 1 N SER A 1 -2.155 4.211 -16.970 1.00 50.34 N ATOM 2 CA SER A 1 -1.965 5.570 -16.400 1.00 51.09 C ATOM 3 C SER A 1 -2.379 5.581 -14.921 1.00 48.55 C @@ -1499,7 +1500,7 @@ ATOM 1498 CA GLY A 195 19.233 13.985 12.935 1.00 44.59 C ATOM 1499 C GLY A 195 18.179 14.654 12.078 1.00 39.02 C ATOM 1500 O GLY A 195 16.999 14.285 12.178 1.00 36.31 O ATOM 1501 N THR A 196 18.611 15.617 11.272 1.00 36.27 N -ATOM 1502 CA THR A 196 17.794 16.314 10.257 1.00 34.69 C +ATOM 1502 CA THR A 196 17.795 16.314 10.257 1.00 34.69 C ATOM 1503 C THR A 196 17.157 15.277 9.325 1.00 34.93 C ATOM 1504 O THR A 196 17.902 14.434 8.805 1.00 32.97 O ATOM 1505 CB THR A 196 18.663 17.282 9.446 1.00 33.97 C @@ -2345,4 +2346,5 @@ ATOM 2344 O THR A 304 6.898 -9.514 -10.309 1.00 85.19 O ATOM 2345 CB THR A 304 4.382 -9.062 -12.625 1.00 85.85 C ATOM 2346 CG2 THR A 304 3.504 -8.205 -13.517 1.00 79.27 C ATOM 2347 OG1 THR A 304 4.920 -10.144 -13.388 1.00 89.83 O +TER END diff --git a/setup.py b/setup.py index 11f39b2..3c8f64f 100644 --- a/setup.py +++ b/setup.py @@ -7,8 +7,8 @@ with codecs.open(os.path.join(here, "README.md"), encoding="utf-8") as fh: long_description = "\n" + fh.read() -VERSION = 'v0.1.1' -DESCRIPTION = 'PyPharmer' +VERSION = 'v0.1.2' +DESCRIPTION = 'ConPhar' #LONG_DESCRIPTION = '' # Setting up diff --git a/tutorials/ConsensusPharmacophore.ipynb b/tutorials/ConsensusPharmacophore.ipynb index 9404680..b9cc7ed 100644 --- a/tutorials/ConsensusPharmacophore.ipynb +++ b/tutorials/ConsensusPharmacophore.ipynb @@ -7,7 +7,15 @@ "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ConPhar tools imported successfully\n" + ] + } + ], "source": [ "from conphar.Pharmacophores import parse_json_pharmacophore, show_pharmacophoric_descriptors, save_pharmacophore_to_pymol, save_pharmacophore_to_json, compute_concensus_pharmacophore\n", "\n", @@ -111,13 +119,13 @@ } ], "source": [ - "t,l,r=parse_json_pharmacophore(\"Example/pharmacophores/5R7Y.json\")\n", + "t,l,r=parse_json_pharmacophore(\"example_files/pharmacophores/5R7Y.json\")\n", "t" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "3d2d4f63-8aa3-4ded-9ec2-be47afab1d40", "metadata": { "tags": [] @@ -125,10 +133,10 @@ "outputs": [], "source": [ "p4_table=pd.DataFrame()\n", - "for file in os.listdir('Example/pharmacophores/'):\n", + "for file in os.listdir('example_files/pharmacophores/'):\n", " if '.json' in file:\n", " try:\n", - " p4,lig,rec=parse_json_pharmacophore(f\"Example/pharmacophores/{file}\")\n", + " p4,lig,rec=parse_json_pharmacophore(f\"example_files/pharmacophores/{file}\")\n", " p4['ligand']=file.replace('.json','')\n", " p4_table=pd.concat([p4_table,p4],ignore_index=True)\n", " except Exception:\n", @@ -137,7 +145,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "221142e3-acc1-4665-8b10-0c862313f95c", "metadata": { "tags": [] @@ -181,6 +189,48 @@ " \n", " 0\n", " True\n", + " HydrogenDonor\n", + " 0.5\n", + " 1\n", + " {'x': -0.8127595970206084, 'y': -0.11323624186...\n", + " [{'x': -3.1086, 'y': -0.4330999999999999, 'z':...\n", + " 7.4526\n", + " -0.7409\n", + " 20.9042\n", + " white\n", + " 5R83\n", + " \n", + " \n", + " 1\n", + " True\n", + " HydrogenAcceptor\n", + " 0.5\n", + " 1\n", + " {'x': 0.8401167956002942, 'y': 0.4831898238218...\n", + " [{'x': 3.270300000000001, 'y': 1.8809, 'z': 0....\n", + " 6.6617\n", + " 0.6271\n", + " 17.6257\n", + " orange\n", + " 5R83\n", + " \n", + " \n", + " 2\n", + " True\n", + " HydrogenAcceptor\n", + " 0.5\n", + " 1\n", + " {'x': 0.2047406876959268, 'y': 0.6360206896223...\n", + " [{'x': 0.6151999999999997, 'y': 1.9111, 'z': -...\n", + " 9.3168\n", + " 0.5969\n", + " 20.8206\n", + " orange\n", + " 5R83\n", + " \n", + " \n", + " 3\n", + " True\n", " HydrogenAcceptor\n", " 0.5\n", " 1\n", @@ -193,7 +243,7 @@ " 5R7Y\n", " \n", " \n", - " 1\n", + " 4\n", " True\n", " Hydrophobic\n", " 1.0\n", @@ -207,77 +257,105 @@ " 5R7Y\n", " \n", " \n", - " 2\n", + " 5\n", " True\n", " HydrogenDonor\n", " 0.5\n", " 1\n", - " {'x': -0.3557676211088673, 'y': -0.25418650835...\n", - " [{'x': -0.9893999999999998, 'y': -0.7069000000...\n", - " 11.6174\n", - " 5.2669\n", - " 22.6831\n", + " {'x': 0.2251563148335858, 'y': 0.9712168385092...\n", + " [{'x': 0.5990000000000002, 'y': 2.5838, 'z': 0...\n", + " 10.2030\n", + " 0.2472\n", + " 25.7112\n", " white\n", - " 5R7Z\n", + " 5R82\n", " \n", " \n", - " 3\n", + " 6\n", " True\n", - " HydrogenDonor\n", + " HydrogenAcceptor\n", " 0.5\n", " 1\n", - " {'x': 0.3889030718388793, 'y': -0.084705598098...\n", - " [{'x': 1.1625, 'y': -0.2531999999999996, 'z': ...\n", - " 9.0505\n", - " 5.0012\n", - " 22.9142\n", - " white\n", - " 5R80\n", + " {'x': 0.7773989379612142, 'y': 0.3513900658938...\n", + " [{'x': 2.9765, 'y': 1.3454, 'z': 1.99750000000...\n", + " 12.0815\n", + " 0.4206\n", + " 24.2915\n", + " orange\n", + " 5R82\n", " \n", " \n", - " 4\n", + " 7\n", " True\n", " HydrogenAcceptor\n", " 0.5\n", " 1\n", - " {'x': 0.9212933640355093, 'y': 0.2247289069833...\n", - " [{'x': 2.8078, 'y': 0.6849000000000001, 'z': 0...\n", - " 14.1192\n", - " -0.5219\n", - " 22.5378\n", + " {'x': 0.7578753536900245, 'y': 0.6238569658281...\n", + " [{'x': 2.765299999999999, 'y': 2.2763, 'z': 0....\n", + " 7.1817\n", + " 0.3027\n", + " 17.8106\n", " orange\n", - " 5R80\n", + " 5R84\n", " \n", " \n", - " 5\n", + " 8\n", " True\n", " HydrogenAcceptor\n", " 0.5\n", " 1\n", - " {'x': -0.1009322475401949, 'y': -0.37401262070...\n", - " [{'x': -0.3709000000000007, 'y': -1.3744, 'z':...\n", - " 10.1989\n", - " 5.3444\n", - " 25.2512\n", + " {'x': 0.1644883932557122, 'y': 0.5587550249448...\n", + " [{'x': 0.5010999999999992, 'y': 1.7022, 'z': -...\n", + " 9.4459\n", + " 0.8768\n", + " 20.9833\n", " orange\n", - " 5R80\n", + " 5R84\n", " \n", " \n", - " 6\n", + " 9\n", + " True\n", + " HydrogenAcceptor\n", + " 0.5\n", + " 1\n", + " {'x': 0.8058199880978917, 'y': 0.5635066943969...\n", + " [{'x': 3.125, 'y': 2.1853, 'z': 0.705700000000...\n", + " 6.8170\n", + " 0.2747\n", + " 17.7783\n", + " orange\n", + " 5RE4\n", + " \n", + " \n", + " 10\n", + " True\n", + " HydrogenAcceptor\n", + " 0.5\n", + " 1\n", + " {'x': 0.1011082635694374, 'y': 0.5416635825534...\n", + " [{'x': 0.2966999999999995, 'y': 1.5895, 'z': -...\n", + " 9.6453\n", + " 0.8705\n", + " 20.9328\n", + " orange\n", + " 5RE4\n", + " \n", + " \n", + " 11\n", " True\n", " Hydrophobic\n", " 1.0\n", " 1\n", " NaN\n", " NaN\n", - " 13.7965\n", - " -2.5469\n", - " 24.2454\n", + " 10.2243\n", + " -0.7737\n", + " 22.5041\n", " green\n", - " 5R80\n", + " 5RE4\n", " \n", " \n", - " 7\n", + " 12\n", " True\n", " HydrogenDonor\n", " 0.5\n", @@ -291,7 +369,7 @@ " 5R81\n", " \n", " \n", - " 8\n", + " 13\n", " True\n", " HydrogenAcceptor\n", " 0.5\n", @@ -305,102 +383,32 @@ " 5R81\n", " \n", " \n", - " 9\n", + " 14\n", " True\n", " HydrogenDonor\n", " 0.5\n", " 1\n", - " {'x': 0.2251563148335858, 'y': 0.9712168385092...\n", - " [{'x': 0.5990000000000002, 'y': 2.5838, 'z': 0...\n", - " 10.2030\n", - " 0.2472\n", - " 25.7112\n", + " {'x': -0.3557676211088673, 'y': -0.25418650835...\n", + " [{'x': -0.9893999999999998, 'y': -0.7069000000...\n", + " 11.6174\n", + " 5.2669\n", + " 22.6831\n", " white\n", - " 5R82\n", - " \n", - " \n", - " 10\n", - " True\n", - " HydrogenAcceptor\n", - " 0.5\n", - " 1\n", - " {'x': 0.7773989379612142, 'y': 0.3513900658938...\n", - " [{'x': 2.9765, 'y': 1.3454, 'z': 1.99750000000...\n", - " 12.0815\n", - " 0.4206\n", - " 24.2915\n", - " orange\n", - " 5R82\n", + " 5R7Z\n", " \n", " \n", - " 11\n", + " 15\n", " True\n", " HydrogenDonor\n", " 0.5\n", " 1\n", - " {'x': -0.8127595970206084, 'y': -0.11323624186...\n", - " [{'x': -3.1086, 'y': -0.4330999999999999, 'z':...\n", - " 7.4526\n", - " -0.7409\n", - " 20.9042\n", + " {'x': 0.3889030718388793, 'y': -0.084705598098...\n", + " [{'x': 1.1625, 'y': -0.2531999999999996, 'z': ...\n", + " 9.0505\n", + " 5.0012\n", + " 22.9142\n", " white\n", - " 5R83\n", - " \n", - " \n", - " 12\n", - " True\n", - " HydrogenAcceptor\n", - " 0.5\n", - " 1\n", - " {'x': 0.8401167956002942, 'y': 0.4831898238218...\n", - " [{'x': 3.270300000000001, 'y': 1.8809, 'z': 0....\n", - " 6.6617\n", - " 0.6271\n", - " 17.6257\n", - " orange\n", - " 5R83\n", - " \n", - " \n", - " 13\n", - " True\n", - " HydrogenAcceptor\n", - " 0.5\n", - " 1\n", - " {'x': 0.2047406876959268, 'y': 0.6360206896223...\n", - " [{'x': 0.6151999999999997, 'y': 1.9111, 'z': -...\n", - " 9.3168\n", - " 0.5969\n", - " 20.8206\n", - " orange\n", - " 5R83\n", - " \n", - " \n", - " 14\n", - " True\n", - " HydrogenAcceptor\n", - " 0.5\n", - " 1\n", - " {'x': 0.7578753536900245, 'y': 0.6238569658281...\n", - " [{'x': 2.765299999999999, 'y': 2.2763, 'z': 0....\n", - " 7.1817\n", - " 0.3027\n", - " 17.8106\n", - " orange\n", - " 5R84\n", - " \n", - " \n", - " 15\n", - " True\n", - " HydrogenAcceptor\n", - " 0.5\n", - " 1\n", - " {'x': 0.1644883932557122, 'y': 0.5587550249448...\n", - " [{'x': 0.5010999999999992, 'y': 1.7022, 'z': -...\n", - " 9.4459\n", - " 0.8768\n", - " 20.9833\n", - " orange\n", - " 5R84\n", + " 5R80\n", " \n", " \n", " 16\n", @@ -408,13 +416,13 @@ " HydrogenAcceptor\n", " 0.5\n", " 1\n", - " {'x': 0.8058199880978917, 'y': 0.5635066943969...\n", - " [{'x': 3.125, 'y': 2.1853, 'z': 0.705700000000...\n", - " 6.8170\n", - " 0.2747\n", - " 17.7783\n", + " {'x': 0.9212933640355093, 'y': 0.2247289069833...\n", + " [{'x': 2.8078, 'y': 0.6849000000000001, 'z': 0...\n", + " 14.1192\n", + " -0.5219\n", + " 22.5378\n", " orange\n", - " 5RE4\n", + " 5R80\n", " \n", " \n", " 17\n", @@ -422,13 +430,13 @@ " HydrogenAcceptor\n", " 0.5\n", " 1\n", - " {'x': 0.1011082635694374, 'y': 0.5416635825534...\n", - " [{'x': 0.2966999999999995, 'y': 1.5895, 'z': -...\n", - " 9.6453\n", - " 0.8705\n", - " 20.9328\n", + " {'x': -0.1009322475401949, 'y': -0.37401262070...\n", + " [{'x': -0.3709000000000007, 'y': -1.3744, 'z':...\n", + " 10.1989\n", + " 5.3444\n", + " 25.2512\n", " orange\n", - " 5RE4\n", + " 5R80\n", " \n", " \n", " 18\n", @@ -438,11 +446,11 @@ " 1\n", " NaN\n", " NaN\n", - " 10.2243\n", - " -0.7737\n", - " 22.5041\n", + " 13.7965\n", + " -2.5469\n", + " 24.2454\n", " green\n", - " 5RE4\n", + " 5R80\n", " \n", " \n", "\n", @@ -450,91 +458,91 @@ ], "text/plain": [ " enabled name radius size \\\n", - "0 True HydrogenAcceptor 0.5 1 \n", - "1 True Hydrophobic 1.0 1 \n", - "2 True HydrogenDonor 0.5 1 \n", - "3 True HydrogenDonor 0.5 1 \n", - "4 True HydrogenAcceptor 0.5 1 \n", - "5 True HydrogenAcceptor 0.5 1 \n", - "6 True Hydrophobic 1.0 1 \n", - "7 True HydrogenDonor 0.5 1 \n", + "0 True HydrogenDonor 0.5 1 \n", + "1 True HydrogenAcceptor 0.5 1 \n", + "2 True HydrogenAcceptor 0.5 1 \n", + "3 True HydrogenAcceptor 0.5 1 \n", + "4 True Hydrophobic 1.0 1 \n", + "5 True HydrogenDonor 0.5 1 \n", + "6 True HydrogenAcceptor 0.5 1 \n", + "7 True HydrogenAcceptor 0.5 1 \n", "8 True HydrogenAcceptor 0.5 1 \n", - "9 True HydrogenDonor 0.5 1 \n", + "9 True HydrogenAcceptor 0.5 1 \n", "10 True HydrogenAcceptor 0.5 1 \n", - "11 True HydrogenDonor 0.5 1 \n", - "12 True HydrogenAcceptor 0.5 1 \n", + "11 True Hydrophobic 1.0 1 \n", + "12 True HydrogenDonor 0.5 1 \n", "13 True HydrogenAcceptor 0.5 1 \n", - "14 True HydrogenAcceptor 0.5 1 \n", - "15 True HydrogenAcceptor 0.5 1 \n", + "14 True HydrogenDonor 0.5 1 \n", + "15 True HydrogenDonor 0.5 1 \n", "16 True HydrogenAcceptor 0.5 1 \n", "17 True HydrogenAcceptor 0.5 1 \n", "18 True Hydrophobic 1.0 1 \n", "\n", " svector \\\n", - "0 {'x': 0.2347041032504655, 'y': -0.303889268014... \n", - "1 NaN \n", - "2 {'x': -0.3557676211088673, 'y': -0.25418650835... \n", - "3 {'x': 0.3889030718388793, 'y': -0.084705598098... \n", - "4 {'x': 0.9212933640355093, 'y': 0.2247289069833... \n", - "5 {'x': -0.1009322475401949, 'y': -0.37401262070... \n", - "6 NaN \n", - "7 {'x': 0.973809020185767, 'y': 0.11351554342795... \n", - "8 {'x': -0.07483648642620724, 'y': -0.3374237647... \n", - "9 {'x': 0.2251563148335858, 'y': 0.9712168385092... \n", - "10 {'x': 0.7773989379612142, 'y': 0.3513900658938... \n", - "11 {'x': -0.8127595970206084, 'y': -0.11323624186... \n", - "12 {'x': 0.8401167956002942, 'y': 0.4831898238218... \n", - "13 {'x': 0.2047406876959268, 'y': 0.6360206896223... \n", - "14 {'x': 0.7578753536900245, 'y': 0.6238569658281... \n", - "15 {'x': 0.1644883932557122, 'y': 0.5587550249448... \n", - "16 {'x': 0.8058199880978917, 'y': 0.5635066943969... \n", - "17 {'x': 0.1011082635694374, 'y': 0.5416635825534... \n", + "0 {'x': -0.8127595970206084, 'y': -0.11323624186... \n", + "1 {'x': 0.8401167956002942, 'y': 0.4831898238218... \n", + "2 {'x': 0.2047406876959268, 'y': 0.6360206896223... \n", + "3 {'x': 0.2347041032504655, 'y': -0.303889268014... \n", + "4 NaN \n", + "5 {'x': 0.2251563148335858, 'y': 0.9712168385092... \n", + "6 {'x': 0.7773989379612142, 'y': 0.3513900658938... \n", + "7 {'x': 0.7578753536900245, 'y': 0.6238569658281... \n", + "8 {'x': 0.1644883932557122, 'y': 0.5587550249448... \n", + "9 {'x': 0.8058199880978917, 'y': 0.5635066943969... \n", + "10 {'x': 0.1011082635694374, 'y': 0.5416635825534... \n", + "11 NaN \n", + "12 {'x': 0.973809020185767, 'y': 0.11351554342795... \n", + "13 {'x': -0.07483648642620724, 'y': -0.3374237647... \n", + "14 {'x': -0.3557676211088673, 'y': -0.25418650835... \n", + "15 {'x': 0.3889030718388793, 'y': -0.084705598098... \n", + "16 {'x': 0.9212933640355093, 'y': 0.2247289069833... \n", + "17 {'x': -0.1009322475401949, 'y': -0.37401262070... \n", "18 NaN \n", "\n", " vector x y \\\n", - "0 [{'x': 0.8040000000000003, 'y': -1.041, 'z': 3... 8.5070 -3.4460 \n", - "1 NaN 9.9480 -5.5000 \n", - "2 [{'x': -0.9893999999999998, 'y': -0.7069000000... 11.6174 5.2669 \n", - "3 [{'x': 1.1625, 'y': -0.2531999999999996, 'z': ... 9.0505 5.0012 \n", - "4 [{'x': 2.8078, 'y': 0.6849000000000001, 'z': 0... 14.1192 -0.5219 \n", - "5 [{'x': -0.3709000000000007, 'y': -1.3744, 'z':... 10.1989 5.3444 \n", - "6 NaN 13.7965 -2.5469 \n", - "7 [{'x': 3.823499999999999, 'y': 0.4457000000000... 11.6325 6.0783 \n", - "8 [{'x': -0.2949999999999999, 'y': -1.3300999999... 10.2320 4.6831 \n", - "9 [{'x': 0.5990000000000002, 'y': 2.5838, 'z': 0... 10.2030 0.2472 \n", - "10 [{'x': 2.9765, 'y': 1.3454, 'z': 1.99750000000... 12.0815 0.4206 \n", - "11 [{'x': -3.1086, 'y': -0.4330999999999999, 'z':... 7.4526 -0.7409 \n", - "12 [{'x': 3.270300000000001, 'y': 1.8809, 'z': 0.... 6.6617 0.6271 \n", - "13 [{'x': 0.6151999999999997, 'y': 1.9111, 'z': -... 9.3168 0.5969 \n", - "14 [{'x': 2.765299999999999, 'y': 2.2763, 'z': 0.... 7.1817 0.3027 \n", - "15 [{'x': 0.5010999999999992, 'y': 1.7022, 'z': -... 9.4459 0.8768 \n", - "16 [{'x': 3.125, 'y': 2.1853, 'z': 0.705700000000... 6.8170 0.2747 \n", - "17 [{'x': 0.2966999999999995, 'y': 1.5895, 'z': -... 9.6453 0.8705 \n", - "18 NaN 10.2243 -0.7737 \n", + "0 [{'x': -3.1086, 'y': -0.4330999999999999, 'z':... 7.4526 -0.7409 \n", + "1 [{'x': 3.270300000000001, 'y': 1.8809, 'z': 0.... 6.6617 0.6271 \n", + "2 [{'x': 0.6151999999999997, 'y': 1.9111, 'z': -... 9.3168 0.5969 \n", + "3 [{'x': 0.8040000000000003, 'y': -1.041, 'z': 3... 8.5070 -3.4460 \n", + "4 NaN 9.9480 -5.5000 \n", + "5 [{'x': 0.5990000000000002, 'y': 2.5838, 'z': 0... 10.2030 0.2472 \n", + "6 [{'x': 2.9765, 'y': 1.3454, 'z': 1.99750000000... 12.0815 0.4206 \n", + "7 [{'x': 2.765299999999999, 'y': 2.2763, 'z': 0.... 7.1817 0.3027 \n", + "8 [{'x': 0.5010999999999992, 'y': 1.7022, 'z': -... 9.4459 0.8768 \n", + "9 [{'x': 3.125, 'y': 2.1853, 'z': 0.705700000000... 6.8170 0.2747 \n", + "10 [{'x': 0.2966999999999995, 'y': 1.5895, 'z': -... 9.6453 0.8705 \n", + "11 NaN 10.2243 -0.7737 \n", + "12 [{'x': 3.823499999999999, 'y': 0.4457000000000... 11.6325 6.0783 \n", + "13 [{'x': -0.2949999999999999, 'y': -1.3300999999... 10.2320 4.6831 \n", + "14 [{'x': -0.9893999999999998, 'y': -0.7069000000... 11.6174 5.2669 \n", + "15 [{'x': 1.1625, 'y': -0.2531999999999996, 'z': ... 9.0505 5.0012 \n", + "16 [{'x': 2.8078, 'y': 0.6849000000000001, 'z': 0... 14.1192 -0.5219 \n", + "17 [{'x': -0.3709000000000007, 'y': -1.3744, 'z':... 10.1989 5.3444 \n", + "18 NaN 13.7965 -2.5469 \n", "\n", " z color ligand \n", - "0 27.1870 orange 5R7Y \n", - "1 26.1430 green 5R7Y \n", - "2 22.6831 white 5R7Z \n", - "3 22.9142 white 5R80 \n", - "4 22.5378 orange 5R80 \n", - "5 25.2512 orange 5R80 \n", - "6 24.2454 green 5R80 \n", - "7 23.5055 white 5R81 \n", - "8 25.2750 orange 5R81 \n", - "9 25.7112 white 5R82 \n", - "10 24.2915 orange 5R82 \n", - "11 20.9042 white 5R83 \n", - "12 17.6257 orange 5R83 \n", - "13 20.8206 orange 5R83 \n", - "14 17.8106 orange 5R84 \n", - "15 20.9833 orange 5R84 \n", - "16 17.7783 orange 5RE4 \n", - "17 20.9328 orange 5RE4 \n", - "18 22.5041 green 5RE4 " + "0 20.9042 white 5R83 \n", + "1 17.6257 orange 5R83 \n", + "2 20.8206 orange 5R83 \n", + "3 27.1870 orange 5R7Y \n", + "4 26.1430 green 5R7Y \n", + "5 25.7112 white 5R82 \n", + "6 24.2915 orange 5R82 \n", + "7 17.8106 orange 5R84 \n", + "8 20.9833 orange 5R84 \n", + "9 17.7783 orange 5RE4 \n", + "10 20.9328 orange 5RE4 \n", + "11 22.5041 green 5RE4 \n", + "12 23.5055 white 5R81 \n", + "13 25.2750 orange 5R81 \n", + "14 22.6831 white 5R7Z \n", + "15 22.9142 white 5R80 \n", + "16 22.5378 orange 5R80 \n", + "17 25.2512 orange 5R80 \n", + "18 24.2454 green 5R80 " ] }, - "execution_count": 5, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -545,1228 +553,43 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "db0b2e29-b884-417b-8a37-f766b8170698", "metadata": { "tags": [] }, - "outputs": [ - { - "data": { - "application/vnd.plotly.v1+json": { - "config": { - "plotlyServerURL": "https://plot.ly" - }, - "data": [ - { - "hovertemplate": "%{hovertext}

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z=%{z}
radius=%{marker.size}", - "hovertext": [ - "5R7Y", - "5R80", - "5R80", - "5R81", - "5R82", - "5R83", - "5R83", - "5R84", - "5R84", - "5RE4", - "5RE4" - ], - "legendgroup": "HydrogenAcceptor", - "marker": { - "color": "orange", - "line": { - "color": "DarkSlateGrey", - "width": 2 - }, - "size": 12, - "sizemode": "area", - "sizeref": 0.0025, - "symbol": "circle" - }, - "mode": "markers", - "name": "HydrogenAcceptor", - "scene": "scene", - "showlegend": true, - "type": "scatter3d", - "x": [ - 8.507, - 14.1192, - 10.1989, - 10.232, - 12.0815, - 6.6617, - 9.3168, - 7.1817, - 9.4459, - 6.817, - 9.6453 - ], - "y": [ - -3.446, - -0.5219, - 5.3444, - 4.6831, - 0.4206, - 0.6271, - 0.5969, - 0.3027, - 0.8768, - 0.2747, - 0.8705 - ], - "z": [ - 27.187, - 22.5378, - 25.2512, - 25.275, - 24.2915, - 17.6257, - 20.8206, - 17.8106, - 20.9833, - 17.7783, - 20.9328 - ] - }, - { - "hovertemplate": "%{hovertext}

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name=HydrogenDonor
x=%{x}
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NOgSC0YQSaSAAAQhAAAIQgAAEIOAIgUNOPlk0SuqPj/iRbDOlr26tHnttGznz4Q/KfvvsI1+5/PLYLTBZYdSgN774uuy8k+S6W+70RJGu+FWLMlPB6K8KaoVVFPormCoYfQGo9w0TjNXi1he2UYJRhV/wvmEren67giCr8wUFo++mGkyvK5xhgrGeuPW5Be8fZItgjN21yQABCEAAAhCAAAQgAIHmJPCZz31OHnniiVh7GE8+6ig551Ofig3EVDBqwSqcfvv8SumZMW18z2EeK4xhok7rV+3mGeYiGtxnqXn8/Yi+a23YcSD1VhiD4jYIv9qVtrp+rDDG7qpkgAAEIAABCEAAAhCAAASUwKNPPilnXXGFzOrsl3/58wdkdtdAKJjnenvkkz8+QFraOuX7X/6y55Ya94ojGP3AL35AG71XdX4/YM1ZJ31sQtCb4PEcWk5wT2DYHkbfldO/p78vsXqfod7/rh/8RI4+/MC6Lqn/78U/THB19TkFVw+ry/7RQz+Xd+76x5P2MGqd9PJXEf39lvq36t/8dlQLyGp3Vl9Q+vszu7u6JuwNzTKqKi6pcZ8a0kMAAhCAAAQgAAEIQCBnAhdcfbX8+NFHZZvuzXLF//eUfHD7VeM1Gh0VufP5OXLDM++W9YMdctbxx8sZxx2XqMZxBGO1+6l/w2BU0/0/sJf3548c+L6agtEXR7WipAYjkqq7qR6B4Qfcqc6r/18dkdUXp8H63vadH3r1qo6KGnQTVRfYYJTSYPTSYPTUelFS/Tx6r1qRY4NCW91r40RJjXsupkmnQDCaUCINBCAAAQhAAAIQgAAEHCLwxpo1cuqSJbLilVe8Wu04bZPM3XaVbBzqkJ+v2lrW9Hd5f//A3nvLTZdeKu1tbZnX3j+SQqOX2rpqiVRb9096nzCX1KRlZZ0PwZg1YcqHAAQgAAEIQAACEIBABgT0aI1ly5fLbXfdJcMjIxPuMLW7W85dsECOnTcvgztPLjIYmEajoWZ5BVf5gqt5Wd4z7bIRjGkTpTwIQAACEIAABCAAAQhAIJTApr4+efb55+V3L74onZ2dstuuu8q75syRzo4OiEGgYQKsMDaMkAIgAAEIQAACEIAABCAAAQg0JwEEY3PalVZBAAIQgAAEIAABCEAAAhBomACCsWGEFAABCEAAAhCAAAQgAAEIQKA5CSAYm9OutAoCEIAABCAAAQhAAAIQgEDDBBCMDSOkAAhAAAIQgAAEIAABCEAAAs1JAMHYnHalVRCAAAQgAAEIQAACEIAABBomgGBsGCEFQAACEIAABCAAAQhAAAIQaE4CCMbmtCutggAEIAABCEAAAhCAAAQg0DABBGPDCCkAAhCAAAQgAAEIQAACEIBAcxJAMDanXWkVBCAAAQhAAAIQgAAEIACBhgkgGBtGSAEQgAAEIAABCEAAAhCAAASakwCCsTntSqsgAAEIQAACEIAABCAAAQg0TADB2DBCCoAABCAAAQhAAAIQgAAEINCcBBCMzWlXWgUBCEAAAhCAAAQgAAEIQKBhAgjGhhFSAAQgAAEIQAACEIAABPIjsLmvT5594QX53YsvSkdHh+y2667ePx3t7flVijs3DQEEY9OYkoZAAAIQgAAEIAABCJSJwNDQkNy8fLncdtddMjwyMqHp06ZMkfNPOUWOOuSQMiGhrRkQQDBmAJUiIQABCEAAAhCAAAQgkCWB1WvWyMJLL5UXVq6U0dZhWTdjlQx0bpSW0Vbp7J8mM9dv593+A3vvLTdccol0dnRkWR3jsjf3Dchl13xd5v7Ju+Woww4wzmea8EvL7vCSnrdwvmmW8XT18v7XU8/JtcvukK9cda7M7pkRu+wiZ0AwFtl61B0CEIAABCAAAQhAoJQETrv0EvnFL38l/V0b5MVdfyb9UzZM4DB9/Tayy4vvk/bhTvnEX3xUFp9yWiJOtQTe3fc9LI8/8Ru54oJTZEp3p3HZCEZjVM4kRDA6YwoqAgEIQAACEIAABCAAgWgCd95/vyy9+WYZah+Q3+7+gAx19IdmmrKpR/7Xbw+QFmmV26+8UvbZY4/owqtSIBhjI2u6DAjGpjMpDYIABCAAAQhAAAIQaGYCx55zjvzPihWyYs4vpHf2H+o2dftX9pDtXn+XHH7QQbJ00aLYWEwE4w8feHzSamPQvXPN2vVy5oXXyTPPvjB+/88tPsVzSfVXKqdPnyrL73lATj3+MM+dVP/+t1d/3Ut/+Ifnjq9kPr/iFVly5a3y0UM+KFfe8M/e734e/W+974ZNfbJhwyb5wX88Ljtst5Usu/p8eccuO3ppq+ty+/UXyvv32d37TfO+tuotefmVVV5dg3mrXVJ9LnqP6jrEhux4BgSj4waiehCAAAQgAAEIQAACEAgSeP8xx8jg0JD8es/7a64u+ulnrNtG3v78B2Wv3XaTf/rCF2KDNBGMff39ctHnb5ULzvq4J8x8Ubf0otNlx+229vYsbr/t2zwhWF2eLwyDwq1anPlCTt1fX3n9DVm4+Fo57M8+4JXnC8DzF873hJ+mve+Bn42LxKDrrDY+uH9S66llXXnR6eN5f/7Uc+P7FIN5f/XcC+N7GLu7uia0Scv90UM/lwPm7hPLPTe2MXLKgGDMCTy3hQAEIAABCEAAAhCAQFwCfQMDMnf+fBltGZVf7vP9yOyd/VNlj98cIjtuu63cd8stkemrE1SvpAV/D678qbh6aeVr46uD/n8HxaOKyTDBWL0Xsjr4TLAMvb+uMKoY9VcNg+mr86r4vPPeh7wVShWbcfIG7/vWmnXjgvGt3vWTyokNtkAZEIwFMhZVhQAEIAABCEAAAhCAwCEnnywaJfXXe/5Ihjr66gKZvm4becfzH5T99tlHvnL55bHhmawwatAbFVfXfPk7ctl5J8l1t9wpxx5xkLdq5//9yotP96KLmgrGOTttPx5FVVcR/RXMMMEYFKtRglHr6NdFy6qXN3jfasFYXU5ssAXKgGAskLGoKgQgAAEIQAACEIAABD7zuc/JI088EWsP48lHHSXnfOpTseGZCkYtWMXab59fKT0zpk3ac+ivCJoKRi3PPxqDFcbYZks1A4IxVZwUBgEIQAACEIAABCAAgWwJPPrkk3LWFVfIUFu/PPfuB2S4fSD0ht2be+Rdzx0gHe2d8v0vf9lzS417xRGM6v65YNFV4ge00XtV5/f3DZ510scmBL0JHs+h5Vx05a3j+xCr9zAG3UqrXV7rrTBqfYL7KcP2MAaFarCs4L7K6j2M2sa7fvATOfrwA9nDGLeDkR4CEIAABCAAAQhAAAIQSJ/ABVdfLT9+9FEZbN8sK3d5StbPXLXlJqMiW70xR3Z49d3SNtwhZx1/vJxx3HGJKhFHMFa7n/o39IXZq6+/Kft/YC/vzx858H01BaP+Xi9Kqgaq0bL8qzrSaVD0BfcwqutsVJTUr337vvFyg3s0qwPxVJcTjNSaCLTDmVhhdNg4VA0CEIAABCAAAQhAAAJhBN5Ys0ZOXbJEVrzyivfzQOcmWT9jlbSNdMj09VtL+1CX9/cP7L233HTppdLe1pY5SBV5eulxGVld1SuKWd2HcrcQQDDSGyAAAQhAAAIQgAAEIFBAAnq0xrLly+W2u+6S4ZGRCS2Y2t0t5y5YIMfOm2elZcEAMX700ixujGDMgmr9MhGM9plzRwhAAAIQgAAEIAABCKRGYFNfnzz7/PPyuxdflM7OTtlt113lXXPmSGdHR2r3oKDyEkAwltf2tBwCEIAABCAAAQhAAAIQgEBdAghGOggEIAABCEAAAhCAAAQgAAEIhBJAMNIxIAABCEAAAhCAAAQgAAEIQADBSB+AAAQgAAEIQAACEIAABCAAAXMCrDCasyIlBCAAAQhAAAIQgAAEIACBUhFAMJbK3DQWAhCAAAQgAAEIQAACEICAOQEEozkrUkIAAhCAAAQgAAEIQAACECgVAQRjqcxNYyEAAQhAAAIQgAAEIAABCJgTQDCasyIlBCAAAQhAAAIQgAAEIACBUhFAMJbK3DQWAhCAAAQgAAEIQAACEICAOQEEozkrUkIAAhCAAAQgAAEIQAACECgVAQRjqcxNYyEAAQhAAAIQgAAEIAABCJgTQDCasyIlBCAAAQhAAAIQgAAEIACBUhFAMJbK3DQWAhCAAAQgAAEIQAACEICAOQEEozkrUkIAAhCAAAQgAAEIQMA5Apv7+uTZF16Q3734onR0dMhuu+7q/dPR3u5cXalQ8QggGItnM2oMAQhAAAIQgAAEIAABGRoakpuXL5fb7rpLhkdGJhCZNmWKnH/KKXLUIYdACgINEUAwNoSPzBCAAAQgAAEIQAACELBPYPWaNbLw0kvlhZUrpbuzU+bus4/stP32MjA4KCtfe00effJJr1If2HtvueGSS6Szo8N+JUPuuLlvQC675usy90/eLUcddoATdaIS9QkgGOkhEIAABCAAAQhAAAIQKBiBM6+4Qh578knZeYcd5PqLL5a377TThBY8/vTTsviaa2Tdhg1y4sc+JueffHKiFtYSeHff97A8/sRv5IoLTpEp3Z3GZbsqGP16/eA/Hp/Qltuvv1Dev8/uxu1rxoQIxma0Km2CAAQgAAEIQAACEGhaAnfef78svflm6ZkxQ+6+4QbZatas0LY+98IL8snPftZzV739yitlnz32iM2kbIIxuPL5/IpXZOHia+Wskz5W6tVQBGPsx4YMEIAABCAAAQhAAAIQyI/AseecI/+zYoV84bOflUP/9E/rVuSGb31Lvvbd78rhBx0kSxctil1pE8H4wwcen7Ta+KVld3j3Om/hfFmzdr2ceeF18syzL4zf/3OLT/FEmL9SOX36VFl+zwNy6vGHeXn073979de99Id/eO6ElUxfyL36+pvj5QVXAmvlrb6XZvbz1Wqn3mvJlbfK0otOl3fssqN3P23b1759n/fffn31v+uV71fUNG+w3NhGSzkDgjFloBQHAQhAAAIQgAAEIACBLAm8/5hjZHBoSP79tttk69mz695K3VbVfXWv3XaTf/rCF2JXy0Qw9vX3y0Wfv1UuOOvjnqgKiqwdt9va27O4/bZv84RgdXm+uAsKvv966jm5dtkd8pWrzpXZPTM8gfbaqrc80aj3UvE5/4iDPMHpi9HzF873XEe1vDvufWhC3jk7bT8uTlWE+vcK3qe7qyt0b2VYfX1XXIUZbFt1W6rbEXTjjcob21AZZkAwZgiXoiEAAQhAAAIQgAAEIJAmgb6BAZk7f760trbKf999d2TRf3j9dTl84ULZcdtt5b5bbolMX52g1t4+TRdc+VMx9NLK18ZXB/3/rl6hqyfA/L2QwdVJvU+wjLfWrJsgJoOCcc/d3z5J9Klou/PehzyxWb0SquVe8+XvyJUXny61BKPeX+ujovPP/2xuaPm+uH3wp09OWGmNKj8oKKvzxjZUhhkQjBnCpWgIQAACEIAABCAAAQikTeCQk08WjZL649tuk22iVhifekrOvPxy2W+ffeQrl18euyomK4wq9HxxdNl5J8l1t9wpxx5xkLfiFxRNulpoKhj9VUGtsIpCfwVTBaMvAPW+YYKxOnCNL2yTCMZgfX3B6LfNF7O+6DQRjKZ5YxsqwwwIxgzhUjQEIAABCEAAAhCAAATSJvCZz31OHnniiVh7GE8+6ig551Ofil0VU8GoBetK3G+fXyk9M6aN7znMY4UxKMqCDa6O7Bq1AugLQn8Po+9eGwyMU2+VMKp8Vhhjd0cyQAACEIAABCAAAQhAAAJRBPSMxbOuuEJmzZgh/3LTTTJ75szQLM+9+KJ88vzzpaW1Vb7/5S97bqlxrziCUQXQgkVXiR/QRu9Vnb868mjY8RxazkVX3irLrj7f2xMZtofR37Po39Pfl1i9h1Hvf9cPfiJHH35gbJfUsCipwfJ9N1Z/f2Y9Qaqrq3HyxrVTlulZYcySLmVDAAIQgAAEIAABCEAgAwIXXH21/PjRRz2X1Cv++q/lg/vuO36X0dFR0aM3NELq+o0b5azjj5czjjseVGmGAAAgAElEQVQuUS3iCMZq91P/hsGopvt/YC/vzx858H0ToqRWn+dYL0qqLxK1HHU3Xbdh03jAHf1bMK/+f3VEVv9eYSuAJucwRkU6DStfBaNepnkTGSujTAjGjMBSLAQgAAEIQAACEIAABLIi8MaaNXLqkiWy4pVXvFvo6uHcvfeWjZs3y89/+UtZs26d9/cP7L233HTppdLe1pZVVcbLVaGml0YvtXXVEqm27l+G+yAYy2Bl2ggBCEAAAhCAAAQg0HQE9GiNZcuXy2133SXDIyMT2je1u1vOXbBAjp03z0q7g4Fp/PMKs7pxcJVuh+22Gnddzep+ZS8XwVj2HkD7IQABCEAAAhCAAAQKTWBTX588+/zz8rsXX5TOzk7Zbddd5V1z5khnR0eh20Xl3SCAYHTDDtQCAhCAAAQgAAEIQAACEICAcwQQjM6ZhApBAAIQgAAEIAABCEAAAhBwgwCC0Q07UAsIQAACEIAABCAAAQhAAALOEUAwOmcSKgQBCEAAAhCAAAQgAAEIQMANAghGN+xALSAAAQhAAAIQgAAEIAABCDhHAMHonEmoEAQgAAEIQAACEIAABCAAATcIIBjdsAO1gAAEIAABCEAAAhCAAAQg4BwBBKNzJqFCEIAABCAAAQhAAAIQgAAE3CCAYHTDDtQCAhCAAAQgAAEIQAACEICAcwQQjM6ZhApBAAIQgAAEIAABCEAAAhBwgwCC0Q07UAsIQAACEIAABCAAAQhAAALOEUAwOmcSKgQBCEAAAhCAAAQgAAEIQMANAghGN+xALSAAAQhAAAIQgAAEIAABCDhHAMHonEmoEAQgAAEIQAACEIAABCAAATcIIBjdsAO1gAAEIAABCEAAAhCAAAQg4BwBBKNzJqFCEIAABCAAAQhAAAIQgAAE3CCAYHTDDtQCAhCAAAQgAAEIQAACEICAcwQQjM6ZhApBAAIQgAAEIAABCEAAAhBwgwCC0Q07UAsIQAACEIAABCAAAQhAAALOEUAwOmcSKgQBCEAAAhCAAAQgAAEIQMANAghGN+xALSAAAQhAAAIQgAAEIAABCDhHAMHonEmoEAQgAAEIQAACEIAABCAAATcIIBjdsAO1gAAEIAABCEAAAhCAAAQg4BwBBKNzJqFCEIAABCAAAQhAAAIQgAAE3CCAYHTDDtQCAhCAAAQgAAEIQAACEICAcwQQjM6ZhApBAAIQgAAEIAABCEAAAhBwgwCC0Q07UAsIQAACEIAABCAAAQhAAALOEUAwOmcSKgQBCEAAAhCAAAQgAAEIQMANAghGN+xALSAAAQhAAAIQgAAEIAABCDhHAMHonEmoEAQgAAEIQAACEIAABCAAATcIIBjdsAO1gAAEIAABCEAAAhCAAAQg4BwBBKNzJqFCEIAABCAAAQhAAAIQgAAE3CCAYHTDDtQCAhCAAAQgAAEIQAACEICAcwQQjM6ZhApBAAIQcJfAyMioDI2Myuio/iMyPDIqI6OV+ra26D8t0toq0qb/IyLtba3uNoaaQQACEIAABCAQSQDBGImIBBCAAASal4AKwJHRUU/4qQDUf1QQ6t8rYnBURsdFYjIOvnhsa2uR9tYWafFEpf/fIi0tFYFZEZsVockFAQhAAAIQgIAbBBCMbtiBWkAAAhBIjcDQ8Ign9vTqaG+Vzf3D3irg8PCIJwb1Gh6uCEIXr4p4FGlra/X+rQKzva0iKFVcqqjUv7N66aL1qBMEIAABCDQbAQRjs1mU9kAAAk1HoJYbqApA1XzeCuHw2GpglQbcdla3vLmu31lx2KixPAHZ0iK6eqn/ntrV5v17cHgE99hG4ZIfAhCAAAQgICIIRroBBCAAAcsEbLiB+k1qdsFYbboZU9q9P63fPBRq1XrusZrB33+Je6zlh4LbQQACEICAswQQjM6ahopBAAJFIhB0Ax0Z2bIPUIPD+G6gM7rbPSEzMDRirWkIxsZQ4x7bGD9yQwACEIBA8QkgGItvQ1oAAQhkQEAFoLp7VkcDNXEDrVWdrWZ2yvpNCMYMzDVeZNQKY5b39t1jg/sv/X2YweixrF5maQXKhgAEIACBtAkgGNMmSnkQgICTBHw3UB2s64qf7vlLOxpoVMMRjFGEGv995tQOb/+iBvpx9Zo1vUP6B0dkYLCy0hwWPVb/jnusqxakXhCAAATKRQDBWC5701oINBUBEzfQ6migeYg2H3oe9y6bS6ovxoogGOPWEffYpnp90RgIQAAChSGAYCyMqagoBJqfQBZuoNXU8hBtfh1mz+iUzX1D0je2smTDoghGG5Tj3cOGqDV1j9WaczxJPPuRGgIQgEDZCCAYy2Zx2gsBiwSC0UBbpEXa21tkY99wqofCx22OjcF6rTrlcW8EY9wekn36PPpBVKuiosd2tFeOLdFLz8HkggAEIACB8hBAMJbH1rQUAqkQSOIG6t94x62myCtvbk6lHkkLyXOwnse9EYxJe0p2+XSleaPlaLmNtmZKV5t0dbRK74ZBryjcYxslSn4IQAACxSGAYCyOragpBDIhYMMNFMFYIZCHYFQX3LUbB2VoeDST/uNaoXkwjssgT7fouHX100/rbvdE4rpNFcEY58I9Ng4t0kIAAhBwjwCC0T2bUCMINEQg6Aba1dHmRYu0HQ20VgO2n90tr/f2yWiO2kWPXdDjMjb2hR/s3hD8iMx5iJkiipNGbJAH47j1LaJNbB5XEuUeS/TYuD2O9BCAAAQaI4BgbIwfuSFghUBSN1AXXECDgFxwj7Q58K3uHHkc+VBEcdLIQ1UEwbhNT5es2TBQqFXfPJ+bqP6Ae2wUIX6HAAQg0BgBBGNj/MgNgUQEbLmBurCih2DcQiCPQXcZBWNf/7DVSLRxXwIuTJzErXMRhLhJmzrbW2XmtA5Zu2FA2tpaReP3+P/WoD7+6qWWRfRYE6KkgQAEykAAwVgGK9PGzAkE3UDV3VL/ccEN1LWBqQviRfdi6SBx/Wb7LqkIxswfRXGhj0W10rXnMqq++nuzCMbujlaZNqVd3lw3YNJsb9+mXm1tLdLe2iItnqis/LdeuMcaYSQRBCBQcAIIxoIbkOpnR8DUDXSrmV3y5rp+GdaNcY5drg2eXahPdbRHmyZDMGZP24U+FtXKIgrGPM4QjeKY5Pesn3/cY5NYhTwQgIDrBBCMrluI+qVGICs3UJf3I7k2eHZh0Jn1gLFeh0UwpvY41yzItT4fVlEVjKvX5hv8Ka4lisDVpE2NRHs1KT9OGqLHxqFFWghAIE8CCMY86XPvhgi44gbq8kDKNTcyF+pTFsG48uUVcsd3vim/ePynnnv0aCA07X4f2l/2+9AB8sEPHdDQM+hiZpefR5+Xa8GoTOzo8sSYSf39NHlM2sSpX720pu6x7L1MizjlQAACPgEEI33BKQK+G6juE2lva5GNfcOiwlAHuzro1Wt4eNQp908XVs1qGdEFgRasmwv10aAXM6aa72FK8wFRsdrR1proLDvTeqhQ/NLVS6X/f74li+aJHPTuyTl7N4pcf7/Ic60flVP/aom85717mxbvfDoEYzYmKqIbbRgJF95B2VioUmrw/YZ7bJakKRsC5SKAYCyXva23NqkbqLrqbDerW15b02e9znFvqEcl6P7FPM71i6qra7PpLtQnb8HY1dEqvRviH34eZWv9/dfPPC3f/8fj5MNzXpY524jss0v9XC+tFlmwTOTgT14tp3/6bJNbOJ8GwZiNiRCM2XBNu9SkHhS4x6ZtCcqDQHMRQDA2lz0zb41NN9CiuG25IIJqGd61urlQn2YVjCoW//6v58k9n1krs6aJ7LpI5MEl4gnHqOvyu0TWv3OJnL94SVRS5393XTAWaTIsaOyivI+jOqjr/SOq/lG/29qjaeoeWzmqpBJRlgsCECguAQRjcW2XWs1No4HajgJalBntpDO6qRmwTkGu1c3WYKYeW3V1nj29U1av7bdhggn3yMoe1WJRb3rw34useLNFHrh41Fg0zjp4mcw//kTrXNK8oQqCtRsHZWjYvajF2k4daGtk5VW97ntPNKNgbJa9mLWeGVc9XnCPTfMtR1kQsE8AwWifeeZ3DLqBtkiLtLdX9gIOD4+IbgMcGR319gHqvwNxMDKvV9wbFGUmWM/1mtLdLmvWm53rFZdDI+ldq1tWgikOozwH7Fm1/9jD5soPTvult7LoX9f/UOTcb4nsuq25aNz/2p1l+b89Fwenc2ldn2jKs/8lNVZRV0XD2ut6/0hqIz9fM+zRxD220V5AfgikTwDBmD7T1EtsxA20yB96l4PJBI2cp4tjVGdzrW4uCNg8B+xqDz00PM3JhUd/+rD86hvz5PKjJ/aGh34jcvBS8Q4a172MutIYFJRhfef2h0V69yz2KqPrgiDP/hf1vqj1exHrXKst28/ultd7i3WkSRy7FWWiNU6botL67rH6btWgYn0Dw54bbPuYK2xra2VlH/fYKJL8DoHaBBCMOfUOm26gRf1AuupaU91lXB5M5el+GfZouSBgdRJlm57uXFwCs2j/uWefIcv+7FuhYnD26SK9m0RaW1vlY38yKncvinbTLPoqo+uC0bVn0uQT6PI7zqT+wTTNshezVrtd7/9x7RUnvemWB9xj41AlLQQqBBCMGfQE3TvTPzjsuX+64AZa1D0bLgRIMekeLq/iujbQy0IwmdioOk1eg8a02792ba9c+Mk9vEA3YZfuY3zo2coqo/5zzqGj8qUT6ovGBTeLnPkPz8pOO0eEWE0C3kIe1wfMafcBC0gnHNVg435Z3cO192EW7SzqBHEaLNQdd3Ao3Yjl9dxjuzravOO/uCBQBgIIxgysrMcraNAFVy51Udm4eUj6BkdcqZJRPbLa72V085iJ8hIgJtV0qW6urK7kxSRtsaDuqL+/c54s+vPwnuDvY/RmB8dE46V/OSqXHVVbNGqemR9ZLvMOO8KkezmXBsGYvknS7rfp19CsxGYXjC5PXppZqLFUtrexaPA0HadwQaAMBBCMGVhZVxffXOdOAJSiuHZWm6JIgxSXB6l5iaOwR8uVAVteTNLu03d8+5sy61cLZcEB4S+yp1aI7Hvxlt980fj1M0bkpP1r5/lmb3GP2HD5WVTiafeBDD5hk4os0uRdPR5FZB/Hvq68X+PUOc20tp/9t83olO5OBGOaNqQsdwkgGDOwje5PXNVrP2R/raaY+vVngKKhIl1ZjTJphMtuv7Y/ovV4uTIDrkxWr7Uf+CLtAasKxjkvLJQj31eb+q7niLz0xkTRqGcz1jpu43u/EHnp7cUNfONSfw+zShHFVxHr3CzsTb4/fpq03y9x7u1CWtvuuNvO6pL2tlYXmk4dIJA5AQRjRohfeXNzRiXHL9aFyJTxa60udCLbzeqW19a4f16Zy5HpXBtA57W6F+yDeTFJewUgyiVV26yRT09eNlkwagAcjZ5afalL6ntOfUze8969kzy2uefJy7amDS+i+CrqpGO1TYrI3rRfabpmb189Fmm/W02467eMCwJlIYBgzMjSq3v7ZNCRg6OLPOuoL+RX39rs9HmR2oVcPvvKNTGLYEzv0HYNenPR/B3le+fVfpG9tFpk10Vbflf31cuOEtFVxrBrwTKRv7ntFenpmZXR2zHbYnWVweVJpiIO6osSgCyqZzVLO2q1s1mEfZQdw3637ZGkAnW72d1JqkoeCBSSAIIxI7O9sa5fBhwJMlOklbpqc7js6hmsq8v7RF0TjC6sAOXVr7KYBT/t+EPlvgWP1H2TaeRTvfSsxlpC0S/gwKt65NsPvprRmzH7Yl2YkKjXSgRj9n2g1h1cfk+nQaXZ2+fSc6V7F3UPIxcEykIAwZiRpTVKqkZLdeWy7dufVrtdEzu12uXyzLVrq58uCMa8+lUWgjEq8E2cZ1H3Lz7ScbGcv/iSONmcSuu6YHT5XVHLkK69Q5J2uGZpR7PbKYl99bnSoF7rNtmJUK+ruT3TOpJUlTwQKCQBBGNGZnPtaI28VlQaxWs7THbS+rq8auDarLOKNZ1Q0fNK87qaSTAqwzOOmSvf+sQvZda0xojuf+3OcsudjxfWHVVbj2BsrA+E5W4WoVWU70lSC+b1Xkta3zTz2e6jKhZVNHJBoCwEEIwZWdq1ozWK+iFxTezU6i4u7xN1bUXDhb6YZx2yEDS/fuZp+dbn5sk3Tl2b+I12+V0isw4ubnRUv+FZ8E0MNSSja8+jSduaRWjl+dybcG40jQveG422IWl+232UIzWSWop8RSWAYMzIcgNDI/LGWneO1iiK8Ko2R1E28bssGF1j6MKgzfZsdLBfZyVobr35Rlnzn4vl+hPjv9RULK5/Z3HPXrTBNz7V8BxFfBe78Mymwb/ZBVVRt54U0bYcqZGG1SijSAQQjBlay6WjNYo4q62mKcqRIFnsTUura7rmLpunWPOZ5lmHrASjtu3+++6Vb1xzhrfSGBXcRtNrBFUVi1vt1xxiUduUJd80nsk8+17S+hd1S0N1e5tZMGpwux3eNkVcGnck7W9J8tl+7jlSI4mVyFNkAgjGDK33+po+GR7Jb59WsGlFEV7V5nB55S5YV5cj0bpmexcGzHnWIeuBzcqXV8h1n79Att/wr3Lkn4gc9O7JLzlfKG76oxPk/MVLZKedQw5kzPDdmGXRWfNttO559r2kdW8WoeV630hqH83n8qRlI+0yyWu77RypYWIV0jQbAQRjhhZ16WiNogivanPY/hA00h1cHYy4Zntd7dZ5lDyjCOdZB1v9RPc13v/De+Xnj/2n162Dk1fv2XMvOW3h2U0lFLWNOnGzTU+3rOrta+RRzjQvgjFTvDULd3lSLw0i+p7XQCyrHdoKk0a7TMqwfQYjR2qYWIU0zUYAwZihRV06WqPIH0tbA+xGu4Krs/C2P6ZRHF1wj86zDtpPVq/tk1FLzgd5tjWqL6T9exEmmGwH50iDcVHewfXaWoS+0YitXNt60Ehb4ua13fapXW0yazpnMMa1E+mLTQDBmKH9XDtao6gf/aJs5Hc1MIRrAyUNwtPaIrJ+c37nlOYpomxPLOTZ1gxfr6FFu9bXwyrp6nuinq2K+u0Itsm1ibO0nw3Xgpul3b565dl+x3Gkhk3rci9XCCAYM7RE38CwvLV+IMM7xCu6qIELilJvlweCLg34bM8Ghz0leYpWBGO891ac1AjGOLTM0hbZOyXYQtf2cpvRN09lWzSZ1yz7lLbdvDlSI3ubcgf3CCAYM7SJa0druCxo6pmhKPW2/dGK03URjBNp5Slaiy4YdaWmtaVFOtpbvUAbHe2V/29paZHB4REZHh719ksOD4/I4Nh/x+mrjaRFMDZCLzxvEZiatDrPZ96kfo2mcfn702jbovLrGGHj5iHpGxyJSprK71v3dInuGeWCQJkIIBgztPbIyKi8tsad4AtF/aAUpd55BlKJ6sa2RUq9+rgQhCfPwaNtWyRZeaglClUkDg6NyMjoqAwOVYSh//+6J7OjrUXa2ipCsq2tRTraWkXLGhoetSImiyBubNs/6t0Q9XsRmEa1QX9vdpfNIu6NNbGbSRrbz5Ruk2nVfRVcECgRAQRjxsZ+9a3N1oJbRDUlycAxqkwbvxel3i7X0yW33rILRrWFuqrbOnJHxXF7a8ukPaNJRKEKvySXtxJpQUwWQdzYHtwmsVcwjwvPa6Nt0Pwuv5/TaF/R+lUabfbLsOlBw5EaaVqOsopEAMGYsbVcOlqjqHs4ijIznOeqVVQ3dsmtV4WKBg14c93k/b16huDKlSsmNGennXaRmT090tMzK6qZxr/nOQi2aQtlPbWr3XMb1RVB33203kphUlFoDL8qoYmYHPVXNMfcXHWFMyzKLIIxqRVq58vzWUmzNUXxVEna5qIEh0vavlr5bD/zOvG1zazutJtBeRBwngCCMWMT9W4YkE39wxnfxaz4on74iyJ0XeZrU6RE9cawD7yeGXjrspvkzue+JRKiC2e+1SPz9zshtbMD87RV2rZQUagriL4rqIrCttaKK6i6i/qXvod891HbojCqT9QbDIatTKo3mJ7lqXsmg2JS/+b6WXRFWwlyeSIsTr9qdsFoc5UtDves09p+l3OkRtYWpXxXCSAYM7aMHh2wftNgxncxK972TJxZraJT2f4gRNcoPIXL9XRpsBTsh7qieO7fniGP/eERkYMkVCyO035NZOajPXLe/CVy+qfPTmomL1+etoorGDVKpTJTUegFmlHXTs/Fs9XbR6MicMgLMrNlT6EXdEbVk4g0y4C/2uD+ymTLGIvqPZOekNQVyaHRsT2XIx4TW+df1uqgRRvYN0v/ifvcNfSCsZy5qN/2NDDZ7p8zpnaMuzenUX/KgEBRCCAYM7aUa0drFG2wouYpysfQ5XrOnNrhDZb1bFAXLu2HP3vyOTnmpEPl9x9+ub5QrK7w4yKHTvmoXPfFWxK7qdZzi82aT9jAVUWhJwD131WiUOujtlNROFQlDk32QdoeUGXNr175/kRA74ZB8Zi2t44J6wpffUZVR+cpJov2Di7KloCofufSPu6ousb9vdnPmKzHw/be1NnTO71JOC4IlI0AgjFji/cPDofu1cr4tjWLV3eot9b3e1ELi3QVZZDlaj1tf1Sj+tbA+tdl/784ML5Y9At+TeTY3hPk+htvibpV6O95iHtfFKrLpK4K6sqYJxDbKuHZw0RhxeUyURPHM5VRMIbtj/WBqO1riUnfDv7xICrS1VZprky6+o6o1ctce3ckfRqK5gocp51lesarudj2nuFIjTg9k7TNRADBmLE1XTtao6huOUX52Ls6GHRtleCwo/eTp/d9Ot7KYvWz+rjIdYcvk/nHnxj7Kc5KMFavFLa3j60ajolCFSIqEPuHRmRz31BgH17sJhhnKNNgslFXY9/9V1cmK/tCK66/2l/SEpManMSl45aiOlKzCEZX381R/E1+d+39blLntNLoyvHajYOi517buDhSwwZl7uEiAQSjBau4dLSG7dm4tPAWRei6KmxdEg2P/vRhOfYr80TmNt47/viuneVnDz4XuyAVBtv0dMuq3vjnpJqIQnV7VPfRSpAZPzhLpZq2n0GXbB/bUDEzNCoY690uDTGZ1URFTEyxktvur7EqFyNx0YR6jKY1/ZEh9VjY/ObqO2CHt02JYxrSQqBpCCAYLZjSpaM1ijpbXBTB6Go9sxxIx32EjjnuUHns/Y+IpBGZ/CmRrx21XOYddkTcaki9FQdfFOoKk6406Uqht+I0ttKkK4X1RGG9ytgegCMYY3eN2BlMxaQW3N3RJvpNUFdjkz2osSuTcgbb/TXl6nvFFVGox+HQDDaK095gWpsrxxypkdRK5GsGAghGC1bUQ7o1+I0LV1EHj64FballSwRj/V6+dm2vvPvwHUU+nt7TsN+P95fv3vOj2AXqQOONtf2e22EtUehFGx2u7GPzIpGmEGXT9uCuqM98bIPmHP22Vn2DYlKFy/Tudq8ftbRU9rDqf3sTECNjK9He/2+JcpuEQ5p5Zs/o9Nyn+wbtuPylWXe/rGYPCtMMNkpid9sTARypkcRK5GkWAghGC5Z06WgNl1aa4qAvysqobTFgytCVAdOtN98ol/9qscjupjWPTjfz7h559oFXQxPqgMI7fkEjj47tSfOPp9AMGpQqC1FYr9a2+0jZBOPU7jbRKKkuXtoH3zajU1av7feqFxSTrS3aTyt7Jn0x6bsze5MWGgApBzHp6iRYHPsW9btn2sZmjgBbj4HtM5o5UsO0R5KuGQkgGC1YdXP/sKzZMGDhTtG3sD0jF10jsxRFGfS6KmxdsftlSy6Qr065qbFgN9Vd5n6RB6/5mey7775j4lBXbioiUaMBD49UzuKrCMPKSqH+Xfe+rF7b13AUUrMevCWV9hEVAraOONHBsssiKi6/euldf0/EES4qJr1+rOdutrV6YlKFpH/8SlBM+n07i5XJZhAjrveLRp8Bm/v4Gq1rmvlt25UjNdK0HmUVjQCC0YLFXDtaw6bPf1p44wy00rpnknJcjlbngt3PPfsMuWPOt9LZv+gb6CGRx69+Qt6z516TRGE9G+Y1yLI9qaDPzrQp7bJmvRuTVkmeK9M8tgeQpvXy06X1HqsWk/7quYpJ9SbQCRH/aJBGxWRez0lctkWeSGi0rS682xttQ5L8tt+lHKmRxErkaRYCCEYLlnTtaI0iDgBccamM6i4uD1hdGFRkssL4PZHf3PWK9PTMijLPhN/zeg5sD3LSEimx4OaU2OXnT5HYsoXnhj22MtmomMzrOUmzC9l+5tKse1RZrniPRNUzi99tu/dvO6tL2seOSMqiPZQJAZcJIBgtWcelozWKuCdFZ9S3m+X++WW2BoRJuq0LA7+v3XKjXPq7xSJzkrQgPE/SozXycrWzPXh1uU+m1wsqJbkuGHXPVXdXvnss44rJWdM75fVe+67bafaNogRNS9LmokymJmlbVB6b73CO1IiyBr83OwEEoyULr+7t8yLfuXAVNaKaCytkUfZzeXBu6+OqA5jKoeeVQDO696qtteIq98QTT8r7zv7fIvOiSJr/fujTH5Wv33qHeYaxlHlNnCAYY5vKOIPrgtH1+oWJySmdbaJeMlvOE9WowZX9wPpNGxkdtb4P2LhDjCW0vRIVt36NpLcd+KWRuqad1+YkKEdqpG09yisaAQSjJYu5dLSG7QFrWohtfhyS1tll96C0BJIf2dGPNqrHUlSikVZE4fgRFGNHA+j/e/uodMQpIh84eHf5/dEvJ0U8Md9LIpe/82o5/dNnxy4vLR5xb6z7XPU4BY2ebONyeRIj7fa7Lshcr1+1PYKeHb6YbPHcXVu942iCAXhGRyv7JlVMqoj0n3s9bzLvq6iTpCbcitanTNpkksa211F3Z5sX4ZgLAmUlgGC0ZPm1GwetRUWMalJRPzB5DfCjeFb/7upKaBx+/sH1Kmy8IynGRKEOEPVS8edFGx2qHGBfLQrrMbvj29+Uc/9jocg+cclOTj/z6z3y+IPPxt6/qCXF4Wgls7QAACAASURBVNF4TbeUYPv5QzCmab3GyrJt+8Zqa37gfbWYbG2ViqhsbfHeD3mLSVveFY3yTpK/qBPASdoazGN7clYn+nqmdTRabfJDoLAEEIyWTKch9FU0unAVdQBZlFni7Wd3O7nnp9otq1oUtre3eitfYaLQO7TePwsuhRUDb5Xxwy83drzG4yLXHb5M5h9/YqLHSnn09Q9bP5Dctmgo6vOexKjKVvvvuk1uvGur22B7dTkJw7QH5Tqw99417a2VFcmAmPQnn/yIrvqeyWJlsgjeKUlt1czutvWY2HbF5UiNpD2UfM1CAMFoyZIuHa1R1E3yRQlc4NLgJCgK9dBhvdRdzBeFOlDTFQBdKdSB2pZ9Stk+GK/8/mU5dsE8eWneS8mO2HhK5NjuE+T6G29JXNG8BloIxsQmi8zouiAr2mpQ1pMNQTFZ2fc85u6qM1djngxpiElXJ/EiO7RBgqJMpBo0JVYS2+9RdUdVt1QuCJSVAILRkuWHhkdkVW+/pbtF38ZVt8l6NS/KYMu2q2PUSqEvCnUMpquEm/qHvb1Gee4t0oHoiv/3Gzny5CPjrzQ+LnLsrMbEovYzBGP0e6JoKVx/R7hev2p7Zy0Y6/Uvf6+0rkw2KiaL+L0zffaa2d22HgPbE8gcqWHaI0nXrAQQjBYt+8qbmy3erf6tXFoFM4Vie0bRtF7V6XTGd+PmIRkYGklaxKR8vijUGXgdPKn7qDeIGpuJN1kp1NUXTe+Cu57WQ2ds//uZ38m5F5whjw0/IjJX6q82viQiD4mcN3+JnL94ScNsdfCuK6rqLm7zsn20Qp6Dfptc9V6uC7K8+lxSO7j6zjUVkyMjlf3W+u57c13/eOCtpDxczFfEb3kaHG1P+OmkAxcEykwAwWjR+i4drWF7FSwNzEUZ+Cb9kFUijVbcsmqJQi/aqO4lTOA+6tLgrzpgwf333Stf/caN8tjGR8JF40six849wROKO+28SxrdKTdxYbsfqwu6Bmt4c91AKtxcLsR1wZj03ZAXc5feGaYMqsWkTq7p0SBDw6PeHm19h3oTbCPi/Vvfp8Eozqb3cSVdM6+e1mNsc2VVv1fbze52xeTUAwK5EEAwWsT+xrp+GRhMb9WpkaoXcd9DUfZe1hu0+qLQizwaEIf6/3rWmTeACYhCL9jMSDrnnNkWKvX6Z62Q6L9+5mlZu27tpKzv2XOvRJFQ69UhL3Fh2w7az1SoIBgbeWOmk7eIgtHlIEImVgk+b0Ex2dpSOSNW29fS0uKJSX8P93iAL++dvOVIIJP72UxjO1KozbZF3Uv3pa5ea2fVmCM1oqzB72UggGC0aGWXjtbIa7DcCG7b5y4lrev0Ke1eRECdHKgWhTrLPTxSOausIgxHvOMp0hKF9epsW6hE8ct7ZjyvACm27eC7/+rgqtkv199rRROMrvM06c+m0TSD58u2tbV6YlKFZPCsyQkrknrmZM5isiiTqCZ2ipPG9liAIzXiWIe0zUoAwWjRsi4dreHSfrY4JnAl2p1+qCsz1JWVQh1c+P+vK4UaibRvwF8trIhCFYt5Xq4Jh7wFY17udnkIxq1mdsmq3r48u5+Ve7sucBCMVrrBhJuk8ZyrQPHe73oebZWY1G+BvtvzEJOmYtg+9WzvaHtlVV36dczEBYEyE0AwWrS+S0dr2B60poXZ5r6FeqKwsodQ9xJWVgf9/9eBg6tsbX9ko2yed7CGNAaSUW0M+912/3DN7kmYmeZxPahM0faOF03ghvUTG5Oj3qThmJj0vUp0ZTJrMZnXO8z0ecwqnW2hzJEaWVmScotEAMFo0VoaNfMNR9zCiurKkvaASzlUQrZPXimsJwrrdRuX2ea9qhfkVlbBaHtPYdkEo67mb+4ftvhmN79V2u8v8zsnS9kMgjHvVeckYlInI02OPcq7bcl6VeO5bEwCTPxWdUl7W2vjFacECBSYAILRsvFcOlrDJfFgaoYkA5gwUdjWWpn9TSoK69XX5QG6SzbPe/Bse6XP7zO2+4ft+5k+y1mkS/J+yKIetcrMu8/HbWsRg6NVt9HlPmEiJkd9T5axPZNBMely2+L2tTjpbZ/ByJEacaxD2mYlgGC0bNnX1/Q5cxaUK/sB45ggbEY1GKzA21OorkHeERVbRKEXWGYsQEHQfTTOveOkdUmYubSqF6xL3oNnBGOcHl2MtK4PoNWl/q31A858A6KsmvczGlU/k99d7xO12uCLyRbP3bXyXQsG4NHgaZpGg6v1D2kgtcqeeZOVSRNuLqexaVOO1HC5J1A3mwQQjDZpi4hLR2sUaTDgi8Lpevh8W4v3Yax8UFultbWyUlgtCvM8W8tVMW5zD2jUo5V3/0MwRlmoeL/bHEgmoZO3G3bcOrv0vohbdz993u+ZpPWul88XkzOndcrA0PCkaK7eqqSuSA5VArA1m5i02S85UiOLHkyZRSSAYLRsNZeO1nDN3UhFoT+DqiuFeuCyno2lf9NLBaB+/PRjuX7zUOUA++ERJ2dUXV1JcGnwlPfgPq8D7W27iNq+n+VX6oTb5d2notpeNMFYtPqG8W+GNtTqV2Ft0+fd+5a2t45NqFa+ofp3/zvqR3TVSdYiikmbE7JTu9pk1vTOqEeb3yHQ9AQQjJZN7NLRGrb3ASjqKFGoHzI9PHkosGIYFIV5rQrF7SYuCbNg3XWSYOPmIdEATHlfeQ/u8xRSOtCzdcxFnu203cfy7lNR7S2aeClafcsmGONufWgGMWn7DEaO1Ih6q/F7WQggGC1bum9g2NvD4sKVVaSxOKKwsp9QjFcKizL4dW311u9vLg2o847wl2dfijvQa+R9oc/jNj32BGojdW00r0v9O6wtujLy2prinIdZtPqGMbf5rDXaf+PkT/v95W/78Lx7vMjhY3snHVuZtB2FnCM14vRK0jYzAQSjZeu6dLRGI6t1vijUj4p+XKrdR4MrhXFFYZRJijAAcHXgmseqci175i0Y8xRStvuwzRXNqOc3y99dfe78Ntu2e6Osi1bf6vbaXo1qlHec/DaFk6mYHBmpTP7qN1+D7+g2krQv22cwbt3T5Z2tzAWBshNAMFruASMjo87MMEd9cCqRRiszjb4o9GYex2YcsxSF9cxic/9C0u6RtxhyVaQF66Ur3NqVdD9qXldeA2Lb922GlSKTPqKCcVPfsBMu10Vf7WoGsZX2KpxJH7SVxrZwqtUu22IyK8+oWu3Td6cG1uOCQNkJIBhz6AGvvrXZiUAt/oBAXWS94ygC4lD/X8Wttzl+7EiK8UikOYfuthkhLWn3sP1RM62nS/Wa0tUmXR2t0rth0LT6qaezLdz8Bti+r+37pW4owwJd2qNbdMHYDGIralLUsFs5mcyF92cUmKCYbG1pkY72iptrS0uLN1nob0cZD2DnjTlG665M2vSS4UiNKAvze5kIIBhzsLbtozX0o1l5WU8Whdr8/sFh50RhPbO4GlAmWGdXZn+rObo0yFBG3V1tpRSMtlf8yiIYXX435OkCneQz1wyCsZFtF0mY2czjqheLKYMwMalCMnjWpB/NtTJpPeKJyZnTOmRz35D0DWYfuK2jrUW2mdVt2iTSQaCpCSAYczBv74YB2dQ/nOqdq0WhzuT5InHIm7GrnMnkv3g1nLb+vQirddWgXN+npPV1daDiUr1cqIvu7Vu9ts/6ir/t+2YpGFe+vEJ+/atfyrq1vRMe1ffsuZe85717p/qeiyrMZcFYNAHmwvMZZe+o312aIIuqa9zfi/AdjNsmP72KSW/80qZbYlq9lUlfTOpYR8cuYWIy7T2THKmR1ILka0YCCMYcrKp7ttZviu+GV08UVgLL6JlKk0VhvSa6Gs2zXp2LMLPqqiuUS4NAF+qS17EBtu+bhWBUoXjt1UtFB1UHHXTQpEf2pZdekgcffEj+7COHy+mfPtvKmxbBmB5mF57PRlujglFXrNYl+N42eu+s8xfx250GE/XOUC+tSiTXLV5Taue0xeSMqR3ijzfSqDtlQKDIBBCMOViv3tEacUShLxJ1ti3pZXM/QNI6VudzaR9erTa5uprgUr1cENW2hZvfX2zfN03BuHZtr1y2ZLEnFC+//HKZM2dO3Uf7e9/7nnzx2uvkss99IfMVRwRjWm9ZkWZYnSvC5GJSixXROyhpW4Mrj9vNqn80jX7j/JVJPy5DlJjUyXaN6lp9zZ7e6T0HXBCAgAiCMYdeoEdrbNg0OD47pu4Wba2V2bHqlcI0RGG9JhZBfFXXvygz32kO0tPqpi7to3JBvKrAWLtx0HNxsnkVWTCe95kz5MLF58s+++xjjKy3t1cWLFggf3H0J2TeYUcY54ub0GXBqO93PQT8zXVunMMbxbYZBGMRJ0Sj7JLXpJNpvbJM1+gko4mYHPU9tYZHZPrUDo7UyNKglF0oAgjGnMy1eWBYNDKY+txnLQrrNdHV4Cz16lwUwejq8R+uCFkXxGteAkNXBzQ6cdp7bmo9N2nZfNHZZ8hhh37YE39JrgMPPEguueKqzFYa87KnCYuivLf8tjSDO2cz7/NL65k26buupMlyEiNMTE7pZHXRFdtTj/wJIBhzsoErR2s0OmOXBz4XVqZM2u2qy5DtCJ31WOU96MlLYNhe2UyD87VX/728d4//lVgsaj/QfY0nfuokWf4v95s8QrHTKFc9psWWEI9TwaIJxmZw53T9mJU4/SeYtijfwKTtq5XPpkeUTmju8LYpaTeB8iBQWAIIxpxMZ/tojVrNLOrhzGkMgLM2fV5iJKpdtt0hEYyTCdjuG40+L7pv8cJzz5R77vleVPeK/P32228XjRQ9//gTI9PGTWB75TZO/VQwTpvSLmvWF8MltRkEo6uTdnH6TVjaIk70NtpmzW/TxZgjNdKwGGU0EwEEY07WVHc0DX7jwuWq62Q9Ni6Jnlr1dDWKnUuDKNvHS1TbSl3W+vqHrZzpFby3bcGonFf19sV+3eiEkgaM+OqyG2X3d71DjjzyyJplaHAbjZY6a9asyPvsf8CBmawyuvxeyNKdLhJ4ggTN4M7pcn9IYJLxLEXcStJIe/28Nr+pHKmRhsUoo5kIIBhzsmbSozWyqK5LAsK0fbYH3Kb1CqbT2VA9K2pzymduJqlLnmLFZeGf16DYdv81EYy+OOzqaJX29lYv0qCehaZ9eP4xR8s3vnF7qBhctGiR3HPPPbJixQrP1CeddJJcdtlldaOnap5Pn/UZ2eGPdvYO5O4fGknlLEyXBQKCsdE3V/z8RZwMNWll0fqSSZtM0th8vjlSw8QipCkTAQRjTtZWEbFmgxuuSbYHr2kgtznTmLS+rrp0ucQu78mKMgnG1Wv7xkVZPXE4MDjiBeIaHAvKpe6oX/i7i0RdSasvjX46e/bsSX/XozYefPDBmqJRy2rvni5HfuxIaWtrka72VhkZFU+c6v2TikibA8q474WiDfJdek/EZe2nb9QVO+l9s87n6rcl63bbnADgSI2srUn5RSOAYMzJYv2Dw86EV7e5LyAt3EWos80N+nG45iWSwuqY92SFDrxUqGzsG4qDsOG0NoNx+NFo1QVexVlw5bBaHIY17NfPPC0/feh+78zF6uuhhx6Sgw8+OJRHPdH41FNPyU03f1WuWHrNeF4/SmFnR1tiEem6YCzSIfJ5P5uNPmTNHBjGVe+VRm1WL7/teAtb93RxpEaWBqXswhFAMOZkspGRUXltTfw9RVlU11VhU6+tRZhhdXWfSV4iyVXBqPVSF3GbV1aivdbKYWtri2zYPCQDg8PjK4em7X30pw/L7194VtSNtPrSqKf77ruv6Epj2FVLNGq+pVd9cYJgDMsfV0S6LBiL8M4K2iDv1X/T/lkrXTMLxrz2Xjdqk0by2w70s+2sLmlva22kyuSFQFMRQDDmaE5XjtZwVdjUM00R3LtcDaPv0sA174FPXizSEIy+mOpob5XODt1zWBnc+G6dQbfSRoSUCsZf/fdjoSuMej91Lz355JNDH1cNgnPOOedMCpbTSKTUeiJSXVvXbhqsuLXq0rFDV159LSmCRvpM0nummc/V928abSy6mE/CwOY3nyM1kliIPM1OAMGYo4VX9/Z5s/15X0X8sBahzrZnRE37kUsHcqchnEzbHZZOV9dbW9xfYQwThyOjo977Y0j3Gwb2HIa1s5HBv+5hvOi8M0WjoNa69Dd1T/3JT34iu+yyiycQVSzqCmPYpe6tHzponrznvXs3Yr7xvD6fWdM7vQA6Kp7Vrvrfw8OjiVZWU6lYoBAEY9pE65enE6HdXW3euZzNdjXyPBeVhU1PKI7UKGovod5ZEkAwZkk3omxXjtawvTcgDeSuirFg21zl6tJAKu+9qDZnrYN9o55QjhKH/RqUZjheVNFGB5innXSc3Pev30/j0fXKWLBggfzNpVdKT0/0ERxxbhqMBqvPn644trVtWYHNU0QWbd+ZBhhxZdtEnD7gp83r2U5S17h5mjWYTz0ONicXuzvb5G0zOuOahfQQaGoCCMYczbt246D1YBu1mmsz+lgayF0VY9Vtc/HD7tLqbN6rLnkNKn3xoK6TOpsddCsNrhwmEYdhz1ejgvGOb39T9tnzXd6qYaOX7nfUIzW+dMMtjRY1KX/U85aniLQ54E0DbBTLNO6RZRl5v1uyaltRvn1pt99m1F5dzeyZ1pF2EygPAoUmgGDM0XwamVFFowtXEfdEFGFAk/fB9GF9C8G4hYrN1VZdFW9vrYhDFaoaUGFouHJ8hbqVpiUOsxCMK19eIZ89Z6E88vBPGn5dafCcP/2zP5cPfuiAhstKY4LGlogskmBsBlHiUnCvNDt6Mwfzqcep0UmvODbgSI04tEhbFgIIxhwt7dLRGkUMoW7zA5K0m7goxF0acOS1wufbU8XztCntsmZ9umei+uJQj4joaNejLPScwS17DtUGGpTFVnTWNJ4VXWXsfeOVmsFvTJ4RjY76iRM+Jd+950cmyWOnSWsSqZaIVFfgwSG149h5kTEC6xRJMLr0jojdCcYyFIl3nDYWMUhdnPbVSmvTC0rdUdUtlQsCENhCAMGYY2/Q1YVVvf051mDLrfPeS5YEQhFErot19M/lW9Wb/7EuLgjGGVPbGzoTNUwcqhgc0n9qrBzadpfTfqjBPxqNHHrt1Utlpx22Dj1iI+oZVrF44qdOki/+wzLZaeddopIn+j0twRh286CI1EmAzvY2L7COqYi0efZmIniBTM0gGG26MDbKO07+vN+ZceqaVlrb/ZEjNdKyHOU0EwEEY87WfOXNzTnXoHJ72wPYNBpdhAGBq3XMcmAdx7ZZrfCZ1iGue249caj7ESvRSqMD0th+3tISjMr1siUXiO7xuf76600xi4rFsz9zjvzt330hM7GolbHdr/1zL9XNOEpEujh5VMuAcZ8L445gMWGReMfBYvvdEaduWaW1HeRO3yNcEIDARAIIxpx7hCtHaxTRzaUIq6Ku1tGme0+9RyzvgakORDS4wZvrJrukpiUOw9pv+zgPHTzrfumhlI7xUffUB398n5x77qK6gXBUKOoRGpv6h+WKpVenHhW1mq1twRhm21oisrW1RTb1DXlHfbh4TmSwLXk/l2l8ltNww06jHmmX4eo3Je12Bsuzuaqqq5nbze7OsjmUDYFCEkAw5my2N9b1e4OHvK8iDhBsD7qT2MjV2WBXBlN59zvf1emt9f1eQJrgnkPfrTTOyqFpH7F9FmYWqy16PuNXl90o3/3OP8vBB0+OnqrRUDunzJDzFy/JdFUxyNzVoyBUROq+KN3/2Noqsd1ZTftVWulsDtDTqnN1Oa6849JuX7PuzazHyeZ3lCM10u6xlNcsBBCMOVvSlaM1ihgVrwiroraFgWl3TnvFyfS+1els703R+1evHHZ1tHmupLrnMAtxGMbG9oA8C8EYbJdGUa2+Zvb0ZL6iGCYSXNibG2bzagETx5016fOVNJ/t/pm0nvXyubDanEW7XHl3Z9G2WmXaFMkcqWHTstyrSAQQjDlby6WjNYr2gc17dcqk67gqarMWECZsNE3WgjHKrXR4eERmTusU2yLD9oDcFXub9osk6bLuS0nqFMxjsuLlioh0daLL1AZFnAA1bZtJPzItqyjpbMYC0C0KKhq5IACBiQQQjDn3CJeO1nDxCIh65rG9ET5JV3FV1Nr8AEdxS8uNMEoc1gpIk8dECYIxqlfE/70ZBGNYq/MQkTZdAONbOjqH630hugW1U6T1vmykDrbz2hTJHKlh27rcrygEEIw5W2pgaETeWOvG0RpFXIVw/ePpqqi16eIT9YglEWxJxWFYXZLcP6pNUb8jGKMIxf/ddZGgg97Va/tkdDR+26pzZC0iiy4YXX3vNmr5Zl45rcfG5juaIzUa7aXkb1YCCEYHLOvK0RouiQhTs7gS7bNWfV39wLs0IIwS/Tr4844taKscXaD/TjMgjc3BiN9PdOV5anebdzaijauIk0FxubguGLPuZ7VEpD4r/Xrky3Dl2BeTSLlF/BYE+4urWwHi9unq9K738UbbF5bfdps5UiMLK1JmMxBAMDpgxdfX9DV8oHYazXBJRJi2pwhutFkPFE1ZBdO5ZOugu1G1OLQRkCbNlR9TW9h2VUYwmlomu3R5vAeSisiiC0bbK/jZ9ZqJJed9bq2tdgbvY3O1mCM18rAw9ywKAQSjA5Zy5WiNIs7KFmEgbHP/hWl3dmFA5YvDnqkd3oSJriJ6+wz1n+HRsX+PpOLCV49LHvZBMJr2VPN0tlcizGtWSZmHYAyrY7WI1BV7ZRdcidSjBTb3DUmfA0c+xeWs6TVoibZp3SY7K/hJ6pgkjwvv7ST1biSPzTZzpEYjliJvsxNAMDpgYVeO1rA9iE0DfRFmwl1cBdXJge4uey6RtVYOVRx2drSKRgve2DecRpeIXUYZBKMGOdq4eUh0z3SzXq4LRu1ntqPxmtpaRaTy0xV9dfvu7mjzsiZxZzW9Z5bpXPKgSLOdzSqE6zGyacupXW0ya3pnmiajLAg0DQEEowOmdOVoDdcHXGGmsvkxSdpVXFwFzXJyQMtu032HY3sOfbfS4MphULjkzUfvr3sJdXBs68qSf1gbdGJlU99w0wtGbeeb6wZsmdH4PkV7t/rP5Mjo6LiIDFuJ1Gdan5s0AvkYwzRIWISJRINmTEoyc8wbQ8cMZbls2pIjNcrSq2hnEgIIxiTUUs7TNzAsb613Y5DjituUKeIizLjqB6+vf9gp9660BIuWUwlIMxaYJsStNGpVK+/VrzwEq6646uDElrgpg2C0zdT0HaXpiiYYa626V69EViaFxlzJvaA6GmBnOHcRaVNkxOkHjaZt1nbV42Lz/cyRGo32UPI3MwEEowPWdelojTzc8xoxQRH2Xbo4K5xkAJuGOKy1+qVRHDf35+OSanNA4rdf+evgZLWlI3VcnLRo5LkPy5vWJEja9WomwRjGxkURmccznUW/qS6zWdtVj53NMcnWPV2i7xEuCEBgMgEEowO9YmRkVF5b0+dATUSK9kFyeZDoG9RFt9mo4z7CxKGuHOgKgrqgqSta1MqhaYdWQa0h/8smGLea2WVtT1sZViZcfhfoBIGr7rJhz2nUUTdRz7YvIv3jcLo6tgTWqRzvke1KpIv7xqOYmfxuUzyZ1MdGGpteT9rvW1tbbDSLe0CgcAQQjI6Y7NW3NjuxD6RoA8skK2W2TW4zyluctvkf4nriMM7ZbXHuHUybt6DOY/XNdr8t2nOdpC+5LBhdrlsY66wG6cHgV1mKyGYVVq6fO5zkua2Xx+Z7kiM10rYe5TUbAQSjIxZ15WiNvAfvScyR1eAmSV3C8rjiNjshnH5bi0ztbveq668c2hCHYXzy7nN5iCmbAyFlnkcb03p+TMtxWZS5XLdqvlHeB6b2ME0XJSIrwbLiHa/T6Aqpad1tprNtF5ttq3Uvm8+N7sPfZla3C82mDhBwkgCC0RGz9G4YkE057eEKInB1NayemVyfdbX50fM5BcWhHlvR3loJShMUh3r+oe6hsxkdNMyOeQcuykNMqX226bF3zEIebbT9as3jOTNtY5EOXLc9mRHGMExEahDjgaGKW3yUiHR9EtG03wTTuWCXJPVuJI/N8QhHajRiKfKWgQCC0RErr988JOsdOGTY5UFXLVO5vl8l6wAnJuJQB1hDwxOPjdD9qnoGaPXfbT8SNgcFYW3TFU4djNoOVW9zFaQsgnHalHZZ40jE6WBfs33uaSPPsKvCxFREtra0iM39wY2wjpO3iN/mOO2r9W7Wv+v4KOtrxtQO8b1dsr4X5UOgiAQQjI5YzZWjNVwdLNQzk+uBetJ0JQoTh2ozP5DEwOCwDI2MGolAV7jlPZjOyyXW5ipIWQTj1O4270xN1668J0Xi8HD5eJLqdgRFZEd75exXnfzRuCUqMqJWIuNwyTttkfpQWqxsvrdmT+8UZcwFAQiEE0AwOtIz1FXQ1plsUU22OZCNqovJ7zY/Kib1CUuThGma4jCsTnr+4ea+odzPh8x75hzBmLRXu5Uv74mHejSKNNiv9TyufHmF7LTzLm4ZPaQ22g9mTuuQvoERCYpIU3dWVxuYt+t+Hlxseg9xpEYeFuaeRSKAYHTEWi4drVG0CHN5DfjjdJ0oplmLw7C6uiK08xaMOhDzVyTi2LTRtEkmEZLeM++jS5LWO04+l0WZ1k1Xv9Y5sO0gimkt4X3uZ86Q6264JSp77r+H9QP1wtC93GqDoopIF8/zzdrYUd/NNO/PkRpp0qSsZiSAYHTIqq4creGKq6KpaVweKPptCO4XzEMchrF0RWirW5m6A9k6xL6aRV79x6ZgVFurq3JeZ12aPsuNpMvLjiZ1zmtSwqRuJs/DHd/+ppz7mYUy/+MnyMyeHpnZM8vLNnNmj8w//gTpGfv/JPdLO49pPyiaiHRlgi9te9Urz9Y7Ur/JO7xtis2mcS8IFI4AgtEhk7lytIYrroqmpsl7hapePX1xqB97jUaqARmS7jk05WGazhXBmPe+WdMBpCA/FwAAIABJREFUpilX03Q6e76qt880eUPpEIwN4Ws4syvPmklD/NXQla+ulh/dd6/cddtSOfrdL8u53xL5y/e3yJc+uSV41kurRS6/W6R7zkfluhtvcUI4NsLaZRFZtIlck75WL43N7wJHajRqLfKXgQCC0SErv7V+QDT4Td5XIx/cPOruSpCGeiuH+vHTPTWb+oeMAtLY4JiXUKpum+0jJqrvn9feN5vuVnlFgrXRj/17uNKfw9pcpHeq1nXlyhWy+NNHyzG7/VIWHCCiwnDXRSItLS3ywnWjMmebia18aoXIOd/ukZMuuEXmHXaETbNPulfarpuuiEib74tcDTh2c5vnF3OkhgsWpw6uE0AwOmQhV47WcHngFWauPARHXLfStAcxaXRbmx/kqPracj0Kq0deZ+TZHAAWSbBE9ZVav7v83iqSYH/z9d/LX5/0EbnthJfGhaEKwn0vrgjG604YlXPmhVth0TdF2vZaIucvXmJsxl//6pfynj33Mk4fldCG62aUiBweHpH+oREZnXiSUVTV6/7u+nnDDTUuJLPN55kjNdK2HuU1IwEEo0NW1f1FazYM5F4jl108a8HJUnD44rCro1Xa2zVwQovnWhrnKAsXB+wu2TlL+0U9UHlxQDBGWSbe7zYHmPFqJmJDxMStU1h6jYT62dMOlW9+6uUJq4gP/Ubk4KWVHLtuW1llrHWpaNzrE8uNVxo1mM55FyxJLQJrXlsqaolI/U4MDI5IIyIyzaOZ0ugnNsqwOcnCkRo2LMo9ik4AweiQBV05WiPvICRJTJLW4DsNcRhWfxcHs6648iovtd/qtX2pzsib9iMEoykpt9PpM9be2mLlkO+4JIoiGM/79Hy56k//dZLL6e0Pi5y8rNJqXWW8baHISfvXFo37X7uzLP+354wwnXLifE8sHhpwZe2Z2SN/vPMuifZEBgOMGVUgw0RpiUib+/kyxBGraJvPDEdqxDINiUtKAMHokOFdOlojzxWfJCZJEhAgK3EYVv+83B7rsXRpEJKW4E/Sd/ISztpn9ZB5DYaU9eXiCnfabUYwNkb00Z8+LP/5lXly/YmTy6kWjLtu0yLPXzdS84aavnfPZTL/+JDCxnJp5FUNqPOOaS/LNx4RT4QGr395ukfeecBfyfyPnxhr9THPd4mJBZKIyLwmtUzak1Uam2cwbjurS9rbWrNqCuVCoCkIIBgdM6MrR2vkueKTxCRRbkj1xKG6Cw0OjXjHDgwNZzN4d/GD75KbU56rAnkJ5ySTHEmeDc1TBsHo8tEVulrS1z8sfYO1RVZS26aV77IlF8gnt75JDnr35BIvv0vkirsrf9cVRr0eXDIqB+5R++61Vhnvv+9eue36C+TU97/sBdTxy75dVy0PmFieBts55zs98r8/ukRO//TZRk0t2rdLG6XvIN3q0NnRJm1tLdLV3io6j+S7s+rvra3iTTCV5bIl/DlSoyw9inY2SgDB2CjBlPOv7u2TwYxES5yq2hzMxqlXrbTBoDL+x7ejffKeQ18cKmMbKzt+ffMSJVFsXVlJzrO/5WUbm23OWjAqw5HR0Vxciv0+nnUbo56ler/btHWSeq5d2ysXfnIPuecza0Oz677Ef7h/y08qGo98n8jdi2pPsC24WeRvbn9lgluprmL+6xfnye2f3lKWX/ZB727xRGjYdf0PRR4dOkGuv/GWyOa58k6LrGhEgqCI1P3z+j3TCU0VkcPDozIwOOyNFWx+xxptk2l+m5OZHKlhahXSlZ0AgtGxHuDK0RpRK3auYPM/qtOmtHuztBqMRi9/ZlZXDl35qGqUu9fW2Dl3z9Q+rkTey3NAnUeUXbWPzTanLab85667s80byCpDffZ0VUSPBtLnT/+dZpTIqD6ddhuj7hfnd5u2jlMvP+2vn3lafnrDfnL50eG5FywT+cbDEwWjisbnvzQyab+jn0pF3h8fe7988EOVZUO9x40XzZskSv2ytbwHlozKQTVWLdXN9Zme+hFY83qWkzCPk8efENVnqnolUsvRiKzNJCJtTuLpO+xtMzrjmIO0ECglAQSjY2Zfu3FQNvYN5V4rFwdfwZXDTp1xHdtzoINTfxvYuo129oQlMZCLM9+23H6ieOXtspeHmLcpIhp9nnUgrm5y6jKnqx36/zoR44lDdece84rQZ7QiIluku6NtXEDqakjaxwxU96lG2xjVRxv5PU+Xa5N6637CWb9a6LmIhl1HfknknicmCkb9P03/9TPCVwU1suq9gxWBp9FXF5801xOLs6ZNvMPBfy/y0LMVV1cViyoaa126avnJv3tM3vPevUOT2BQaJlzTSlMvAEyYO2vRRaTNI5/Ulb1nWkdapqIcCDQtAQSjY6ZVsaiiMe9LX6L6IVq3KZ+61BOHYW6lLu4RrLahK+IsWC+boqVen7YZES+sHnmIeV3F37h5SAaGst/XFjcgTLVA1OdRBZ8+exrN2XSvry8gdYJHBae6z/UPajnpC0iXBaMG8FDvEVfdB3VfYetPj6spGH1R5z87/j7GequM3/uFyNNbXe3tPbz26r+XIzo+H7o/ctdzRF56o1Kylldvb6Tuabz4wf3li1/7UejrJK8AVll/r+O+p4suIm1GFedIjax7L+U3CwEEo2OWdOVoDZsCLEwc6n4oXcEYGtIB6og30Ko32CrCUSBxP/o2uqYrdbJ55pYrglFF8qa+YScEox8Uyl8d1NX7JAIxqs/qc9rV0Sa+gPTPMvXdWBtxYXVZMLo4WRS0le4t/P2d82TRn4dbMCjqfGHnp1Q31kv/cvKqoLqkzvzIctnvQ/vX3R85+3SR3k1bBGO9VUtNpUFydj4y/JxHmytTUX09zd/T6D/+d7atTT0FKh46rS1uurMGYxKkyTGsLHVH1fceFwQgUJ8AgtGxHjI0PCKrevtzr1VWAkzL1bPS1LVN3db0o1UtDnUQGXfgaHOTfFLjuCLOgvXP2xXUr0veg30dkK3qtbu/1OaqavUKY5hArOw7rEQMtrHqqbbXiSndA9ndWRnANiIgtQ9ppOPN/cNJH9HM8qUx4M+sciKey+hXztljQjCa4P2qBWNQNNY6YkP3Jp55/bOycuWKmmK0d6PI7DO23MlfuXzhutGaeyOfWiFy04q/kiuWXjMJic2VqSztUV12VnvNfU+CahHpP4d+LADbK+M2340cqWGzJ3OvIhNAMDpovVfe3OxErRrd15WVOKwFp9H6Zg3d5kfQtC06k6uDgrwH2XkfiZDHgN5mf9CBtM6i64q9t7rX0ea5ltoWiFH9Migg21rVhbXiYeC5oUdMJCEYo+jW//2zpx4q/3f+I6GJWj458c/77CIya6p4x2rsO0fkwN1l0t7EA6/qkW8/+Kqce/YZsuzPvjXpdy1RXUx3XTRZMEatMh52+/7y1W9PdkvNeytFYxYIz217MtQFEWnzDEbdjsAFAQhEE0AwRjOynsKVozXizGraFodhRnF9n1DebpdhzPJe2fPrlPfKQDMKRhVfGqDGF4jqvaATA54As7BvstEXp78KWql/q1QLyOo2uDL5EdZu1yeztM71At/o0RdzthZRoeiJxarANdVtrgS8uVjOX3yJHHvYXPnpOb8M7Q66WrjvxRN/0lXGqAisH/vHHvnKD16dVKYr77NG+34wvwuBfGyLyDhjj0ZYK9vtZnc3UgR5IVAaAghGB039xrp+b0Y976uWC6UL4jCMjYsun8F6ujiYyXtlzxXBqH1HD8W26XqVtsAJc++sBKkZqRwG3tFa6IO/qwWk78Lqr5JO7dZV0/xXy8PeTXkEVYr7/VC31M+edqg8cv7LcbNOSv+xG3rkqn9+1juD8biP7F6zTA2M85fXTRaM+pd6q4watfXLPxrb+BjIbnPVvmFIhgXYjCdgWCUvWVYi0uaKKkdqxLE4actOAMHoYA9w5WgNjeKo0Qz1fKfgnkMdVOteoS3RSuPvOcwCu+tnR+a9ihbG3JU66aBIz9Jcs34gi64RWWYekw2NulD6AWRM9v+5YudIQ8RIUL0PU91sdf/lpv7KUR8uraIWQTAq+n/74b3y1D8fJ9efGMMQVUk12M3a3SvRUfU67fhD5b4F4a6uerbiycvCBWO9Vcb9r91Zlv/bc5Mq2YyCsUjPrv9M6r5kjVHQ2d7mBdaJsyfS5ooqR2okf87JWT4CCEYHbZ7X0Rr1Vg5dE4dhZrMZWS1Jt3FxptiVqIJ5s8lLMGo/Wr/Z7NzV6gij/hEVJhFGizToTPJsaR4VCyNjjhkVF9ZkR4EkvX+9fEVwSdX66/vgH669Ulp+dYVo9NO4l0YwXf/OytmL/rXo7DPk6rnfCg1io+mvuDtcMOpfLztK/5kYgVUD5Sx84AS57sZbJlUvj+c4LqO46Yu+LzOuiLT5TdLzF5UvFwQgEE0AwRjNyHoKG0drhInD6pVD3TvU2pLfWYxxwbv+Yc1bFIXxdKVOeZ+flsdAM8pFWZlUIoi2NXyGYVkEY9Altd5Zkiqybbkfaz226bEfhTfu+1PT+/3kmi9eJ0/+y2K5fWH0fkX/PmFiUX+rtzdSI6l+4+HwmupeyYP2ELmuarVT9z1+s3eiKPVLcH0fexKbuLj3PUk7gnnqiUg/nY0tAhyp0aglyV8mAghGB62trlRvrE3vaA0TcRgWgdAVMWFqojRnJr1zyV5eMenWhx52hLcvJ8ll09XGtH55CzW/nnmzyeN4kWrBGBSIHW0t3tEy6lqp4kbPRIx71EywD5RRMFY/A0EBqSJcXeX6BtV9ddRjnJWAzLtvm74LfMGoe0PXbRqUXz/ztJz36ePk6Pe8LIvm1RaO6lb6tf/aWY4+eYnMP36yL+vatb1y0fwd5XvnTa6JCsanXxLZZZstAXXmjP13rXprAJ4/PfN++eCHDpiUJI/gVXH4JknbjG62YRx8ETljamXFT4NcxXVnjcuXIzXiEiN9mQkgGB21ftKjNZKKwzAMWZ3FmBXyRgWuBn24/7575avLb5Tfv+NlEV8X6vF8/hF9r4nsN21/Oe+vl4QOWKLa5pprmiuD2bzrkcegTAWjruKPjIpUC8TB4dFUBUxZBGNf/7D0GQYM0wGqCkcVSEEB6R/jkZaAzLtvR72Tgr+HrXrr5NnXb1wqszvXSutgr5f8pTcquWZstYt85C9OCBWKwXJruaWqe2lUxNVgOXoMxyfu3F++e8/kIzU0XVH2isaxie7N37h5yKk9uXHqHzdtcPIurjtr3HtxpEZcYqQvMwEEo6PWf31NX+SA0V+R0AGPbjDXf6cZkMZmtLI0zKADM3UxWZ1gdVaF4qmXHicyV0R2j6iNiseHRE7b+6/kvMVLYq04uiYYtaWu1CnPeiQRjOpq99hPtwTzmNnTIzN7ZsnMmT0y//gTJvUL7Z/eERHtlaMu2ttavbMQNUiL7hFOS6CE9V6dTNEoourm1ayX2nBT33DigbUvIL2jSNrbPEwDQ2PHkDRgn0beS7ZtFeUmnbQ+Ohn3d+cdJzcd+cvQvYym5Wp01ItufVZ22nmX0Cx5vkNM2xA3XTOumtZjEHUGo4mIVM+MoeGJe1+r78mRGnF7IunLTgDB6GgPqD5ao1oc+hEBs45Waus8pLTMkGSGWQf+535tociRMWvxnMh+q/eX7y4Pn+0OK83Fj38SZjFJGSXPsx5xIpZqf7nrtqVy6vtf9vZYVV+6CnL9/SIDb9tfln7pq7LbO9/uCURPgOgxFxrBc3DE+5vv/mcEqIFECMb48MYFfkBA+gGG9N+mLsKuuH2bEEgycWJSrqZR0bj4pLnykwvXmmaZkE73SLb87y3RV8MEwFYzu2RVr+8Okug2zmUq2je4UYBJ2ltLRPqBwSpRWieKSI7UaNRS5C8bAQRjihZft2GTfPn278mJRx8if7TDNg2VrAMSnSHTlUNb4jCswlGzfQ01MoPMcT82icWiX/eXRE7r+iu5Yuk1Rq3JI7hKVMVUxK5e22c8AI4qL+nvea4OmKys+OfUqVDUM+KiLhWOi5bPkv3+8m/l5NPPmjTjbdNNtAyCMetnSwWk58La3iLdHW2eK7GJgGzUVT6qn6X5e5aCUeup7q03XHKcfOPUtbFWGhfcLLLP/GV1XV+LtoXC1G55vhdN65hWujS9mqJEZGtri0ztqngScEEAAtEEEIzRjIxT3HT79zzBuPTC0+TIeX9qnC8soc6Mbdg85M2KhQWkaajwGJldP9uwuilxBK4GdTjmb+bJusOSzXiP3/shkeuOrj+Y8dNmPaiNYdrxpK6seuZZjyjB6IvFb37q5VgDXYVcK3qkbcGY5zmXSfpl3Dy2n61qAemvZujZtcEgRUUTjHH2gca1kabXZ+n8Tx8nx7zrl97ES709jH5AnXMuuyVyz3iROJtyK9L+V9M21UuXtegPisjpU9q9o3e4IAABMwIIRjNOkan+8OpqWbDoKm9lcfd37iwXnv2JyDz1EujM9Vs5HWIerJfrZxtWM4wzaLxsyQXy1f6bROY0ZCovIM4f/2Bn+dmDkw+Sri456xn8JC2JwyxJ+aZ58gyJr0ey6Ngh7EzERsSi33YVjbMOnjipYFswavTBN9cNmJqjcOny7se1zskcGR0V/a0I+0dtMtR949/95o3yrrZHZNbULd2td5OI/vP8htqRV8M6p83nydbDUSR35jSYpBnpPKo+HKkRRYjfITCRAIIxpR7xmUv+0ROKOl/186eek9uvv7ChktM+WiNpZVw/2zCpINNQ73P/cg9Zd1SDq4t+BZ4Sue7D0auMUStZSe3USD6bg8R69cyzHjrYrN5P6M9G//Xpx8rnP3Rv7JXF6rbuf+3Osvzftkwq2HQTbcbVl0Ymixp5Xkzz+gJS3d70PE0NcOQf4ZGn10jUM7h242BkwBBTBibpdEIm7KoV2KZWmWHPsMn9XU7TjCK4Hm+b442te7pE34tcEICAGQEEoxmnuqn+66nn5OKrvip3ffXv5Ln/WSEnn/sF+fVDtzdU8sjIqLy2Jv/N+zZn/BoCNpbZVJB5UVH/71hU1DRu3Cty2ubovYz1VrLSqEaSMvI4gzCsnnkLRo2OqVE2/X1qKiDffGuNLD1xK7l+8vFyE5qg+xV1lSTKva53zy2TCjpYseUmimBM8mSkk8cf9GvfUuHY3VkJdlQJxFE5A9IVAZmnW3ijtE3f/Y3ex2Z+mwLKZrtq3cumR5PuDdV9jFwQgIAZAQSjGaf/n703gdOjKPPHn7knk2OGS0TNwa7ucigEr0UgJqw/IaKYiSDHCiaRU7mCYGANmIBEMQpJJCiXkBg03ARBCLhCICD8PTg8NuzqKgkgSBIyRzLnOzP/z7ff1KSnp/vtquq6+p3qzycS81ZVV32ruru+9TzP9ylZCq6oiFnEnw1/3kjHn7Fg8P9/ZHJajobkpt94u9O6EEneXGJ4P7AXnnsm3TXpdqJ6BQtgZxMHPHQQ/WLtcyUbdPHEGB9pbFg7u/vUgSHRko18YyBSIIpFkli0AnX1FBX1YOW/ZvFVdGzNt2jaAbsGBHL44kailzYRrduAv1dQawdRYwPRBdMHaPYUSrRGhq2MJkmcyXtJTL2SKjhwMG0d4+l40jOPOQnSrNRUBknK+/r7ieWAtEUg80wYTZINnnlXUQYkGOJKO7oKKppzvg1Tmgk+pYbzS8F30EEEPGHMOClQRj3qxIvoI4fsTy//ZRO1t+8IWtzvfRPpknNOpv3fF58viue20dQaPHVUl1GpWqa6b3Ht8VpEPzn9UPrvz/xebZdWEL3+246Sbbq4cXflZN5EfCcjiMWNelVAEJHiAnFmtTVVtC0SN3zykfsEaQCQJuOB3xG9tLEiiK9Ku247c4BmxSipzl1F9OlLnqUDP3Bw4A5lKq7Q5L3SsNH1Owgj4gR15rOU6TsIY3VlRWx8LGuPuT8nEUgcXpi48qzIaeL9YWIOwvcoxzGVwtBUHHtNVQXt1aTwtNj0wvD38whYQMATRgWgr1n7NL1r7z0CkjhuTAMhnvHd79wzs/BNy/aeIKm37Us0VYXN/vJujI+fdTQ9+5FdSdeV9PkOotefLs0mXLTYuuImq8PSifWQ5AYY3oTHrRvEVq3++v6BOyqsikdeRfTKFqIK7O5p13/j1s7U/Qbo8fnDE0ev+S3R24fcSdOPOdYTRiUP3a5GXCWMMgcyjECG3aNhdQxbvxXDFzRnMxdq1vHY8FDI2ue0+uU4plJjNrXXQFxx05jaNPj97x4Bj0AIAU8YNSyHVfc8FgjfXHfV+Zlah2Jje0dvpjZUVBZJVaHiflna4JUhP37G0fTsJ9USxvfcm66Uytu/LBiI1nXFTVZmYx0dKxMaEY0TiyOMiHNte+xEmvup4l1adhA1LyF6csNwhEEio0TyL9f0DXNNhSvrqpb5dNG8+YFyZuPoGiPKpbwHKaJrx6XyrrpTqljXpQgkrOTI2Zv1wj32aqzPbeL7PH2neOfK1TXN23+Rcia9mcY21BB7LkX66Mt6BEYyAp4wZpx9xCxG3U7hpgpLY9bLldQaNsVIZDDkOSUPUmqMup6oSeYOMXW6iI5+6TN066q7Uhvk6V9qIwoLmBRfKdVtmY11UiqDaC68NLjiyBuSjL929/RBwsjagFvpsrWlWwR5vG/uADV/eGg5EMYH+hfTGWefG+QAg8uZiVQXJslpGta6fnd1c60jDg2b67ogBrJqZwxkRZD7Ee7VsgTSxcMskbXi6vyLjCFaFmPa3NplXcsgyxh46+rOwRjux25jagkHpf7yCHgE+BHwhJEfq9iSyL+I3Is6Lnz4TWwm0/qeNzEBno9soJJ634lEk9NGz/n7m0SnD6SrpKI1U243nD036hpZqk88svjYVBRdTKuCDXNSsnTesbNy2CwjL9fm1u7BqiCMf1w5nRYeN7y1pY8QXXh78l0Onkj04reG/45E5EwpNe6eov3mLW+SnPL2SXU5VwmDDlfrKHalCCQOHnniOvNOGF17r6pY364dLqoYU1IbJj1dfEoNnTPp2y5XBDxhdHhmXUmtwas86gqUvGqJ7/5wA9FsRb1eQ/TYkqKYSdrl2sbW5MluGmGEYmQ4wXmYIEKoYGCAAgXTYiqCAa6NcNp84Pe4zTJydf7nCe+iNV+NbwHWwpnXFuMawxfSa7zwrXilVFgnT/7WBkKOOZMbdE8YeVaBnjI2hEtAIIP4x6ri4QqyB3SF8kDGEci8W6HLjVyZfD/oWflirZrcZ/iUGmJz40t7BICAJ4yOrwMXUmvwKo+6AiWvUMA1ixfRtZsWEclnPikOuYXo82+eQkuX38QFgWsuvq5sTFicHYSeiu52xaTKcLNTTRCjE5UUv4VY1199JTnWFXGNC++DeirRxL2IJu1JgRvq5ARx5GlXEf10fVEYySTunjByPZpaCtkgjHHrO45AsjQeIJB5jnM1+SxpWSQxjbpykGdqvKY8mfCu32f3UaaG5e/jESgbBDxhdHwqXUitkbeNBK8LGCxIRzUfSq99YlOmWMZx9zXSYyueC6xGPBcvoeVpS1UZW3L62OgFqQR2EsTKioqAHLJ4LB5XOp0Y3LV6FTX98SyaHZMiQ/S+6/6b6Cdbdrktm9zkmnR/FcVFVXnXLPdsXCCMXd191NVrJjUGD56Dz11NJdVWF2O5kAcyOP9yMDVJ2phMPktpfVH1Ow5q6+uqhnhcqGrbxXZM5WD0KTVcnH3fpzwg4Amj47P0dntPsIG2eZlUL1MxThHxFKROQIqN1z69iUgmLdMaoiWn3UgnnHwqd9ddsDhEO2vKnQsbO3ywYe0IWxBBEGmAqKG+ylrcbhIGJx61Hz149iZqGs09xbEFZ1zXSFf/ZAM1Nu5SWgLJeaulK1vDHLXLcUMdHbYpLDngHlLExQOi6BiwPvDexDOJQxskiy9a9YvWfbiCu3zl7VCTB0uemG6edvJSxtSBj0+pkZcV4fvpGgKeMLo2I5H+uJJaw5YFSmZ6RIPn//SHl+hL559Irx2+ieidnHdsIaJ14mQRrYsQWs7eZC7GIxQkc5MwQYRYDQ4fEHsYbEYL/UPSAdi2giURRqyP6y/+WGIsIw8uELv5Q+PX6aJ5lw0pbuq58oSRZ5b0lHHNBT1plGGCgvXCckDW11Q5TyDL0Rrn4ndCzxNSbNWUaJFPqaFzFn3b5YyAJ4yOz25ndx9t295jvZd5ynElc9oM99QLLz6THt32ENGhlGxtBFF8kehjo6fQFRcv5hK5iU6eyeB+3oWD+YU1O6sLaJJaYxxBjPbNNqkpZaG6+YblNPD8vFjF1DSMQRYfbo2PcTVp2d1jXJ0Ra2YaHrp+N0W+RfufF8JYiqAwAsncx1WpE4tiWYrsRgWzVLVtqx0XPVF0YWEyB6hPqaFrFn275Y6AJ4yOz7ArqTXysunBdGYRC0AqhVtuWE7Pvr6e2ipbh66OLqKP/fMU+uqZ8+mww+WD2lw8DZedX9X54Gy6Faa5RIE0Pv/QIlr5pVZu91Sk33j1XfPponnzY980njCqewGbwlK0x3i28hAXKJIvUlX+U1Esk8rjEA5KsPDIKZfLVEyfC3hl+WaL9t+n1BBFzJf3CBQR8ITR8ZXgSmoNUwpmKqZDRcwlLI5tra3cQjYi/ZaxgIq0L1OWlzACWybVX1ONeMTKnXFO8gnDw/21uelPI4zoJ9xTF15yFn3yPb+nudMpkTjCqvij30yg4+bMLxnfamq8tq23MmtStI4pLEX7xbOuRNvUUZ5XLCzu3ninFfOjVg6+E3oLO13P+/q1x0CKkF0d2OloU5XXh46+qW5TNIwky/3f0VRH1VVFBW5/eQQ8AvwIeMLIj5W1ki6k1shbPIWrm0csIhfznZVyf8JmkMUzhQkiYhB7IFaj8LI5byKWIFiir128iPao2BiMvqWYKSO4xu4xkY767ClcQkimLKqeMCpcpIJN5YUwqnSBNE0gVfZdcHq1FdcVV66twxkaNhWm4VNqZJgkX3XEI+AJYw6WwOaWrkAoxOaVt1y2aAD1AAAgAElEQVSMLm/SXNy8h60L2OwhHiiIV6qpIrhFIxdikLNNMUGMrmmbmyReK6vK59AUYTQZI6QSH5G2bB42lOqny++icL91pv/AO6X4PqmkqsrKIIUHywEJJdasKqw6+y6yBlWWdXU9qxwja8sU4ce3d+/dZOTQdYzat+kRyBcCnjDmYL5cSK3hohtlqamzsfkXWUoubQbY3OJjClcdkwQxjjBubevOLL4jMhesrI01Y5JMmCKnMtirqOPSMxUeT15wN7X+mVs7I5DMa4ERSJlDKVN9V7FOedpw8VCRp9+yZUzFa8JTZvextbLd9PU8AiMaAU8YczD9rTt6aUeX3WD+vFkoTH2AZJePKQnxuP7FuYuhXF/fALV29GY+7ZfFBPWw8cN6L1iwqNvYdHrCmGW1DK3rKjFzlchGkbf17JWKi+Z1ezf5HKlbscktmRSBMTGetHuYmj+4vjaOrknrjv/dI+ARiEHAE8YcLAuQRWyibV952fgAJ9dFekwKGjBFQyZIwSTxWWJuuIOZFB0otY5tkDbWH7hFdXT1aXe7DY/f1EYJ93SVUKl6r7k6vry8N02uxVJzLiOs5UrfVa3lvIWAZB23qZQ4PqVG1pny9UcyAp4w5mD2XUmtkadcjK6L9OgkRjKS97A6jh5VTdva7eb8hGV4R2fBKGkLE0a4xSH3qalLRGhHpk+vbtpI1yxeRI/+94O70sR0ERH+UDFNzOmzzqXpxxwr07wzdVz2gDC1Gc46Ga6SLp7UPXkh5bxz5MoBHm9/s5Qz6X4Ld1S4pfrLI+AREEfAE0ZxzIzXQEzHltZu4/eN3lAnyVE9OBdzHYbHqNJlFgSxKGlfRXXVEJQYILhywYLYXeATlHAlRtWmeIUp4YXwOtBFGJEWZsH8eXT3y7cTHUpE70x4wkAcXyQ6cMtBtOS7N9KBHzhY9aNopD2Tm07RAblq+YyOIy/ENkwg8c5D/sXKyorACwfvPLz/8n65fuCpEl+T7rc+pYbKmfNtjTQEPGHMyYz/fWun9Z7a2FDLDtoVApTU/yw5z8IEsaaqIog5ZAQRaroyGyaTH+1Sc2pzjWGTVugfMG5hbO9Qa1GFVfH4WUfTa5/YRNTE+QSBOK4hWnjKYjrj7HM5K7lTzFXC6Gq/4mYur1Y6vLv2HFdHHd19waEZCGRXbx+xPJAy70PbK9vme9D02E1aU7HG/eUR8AjIIeAJoxxuxmu5kFojT6eerhCgpIUigiU2nYGi4E5perQZpLlAHsTefimCGO2XKxtbmwm4ReZE1QtAtdVeiiyGB7OOaOH/4yeNLEcn0iVUVFRQR3chWJMySpdZMHVl/br6XPFgmxdLaHQs0Xc9LJCBtwVSA1XvIpBMhTUPBFKlBwrP3NssY+q961Nq2Jxlf+9yQMATxpzM4pa27mAjZvNy3c0zjA02DXs31dOb23YGa9kELubepRIVmyCIcXC44JJmavMQN34b91ZNGI+afij96Yjf81sWY4AY93AjPXbDczR+wsTYpyZ4D9RWBYcY2Hx39SCnXl9g6WbWAqRKgMUnLKyk8xF0mTAibmqzAyEFpfB3FT+eNZMWfz34Pt1JIIMDt0LfYB5IFwlknvQCeOaoVBlT1lSfUiPrTPn6Ix0BTxhzsgJcSK3huptndCpdIEBJyytMvrGhgWsp24SjDlxLsdlWZUHkWeYuuKSBSMOlrL3TfBoZG/dWSRhvvmE5LfzjPKL9eGa7RJkWos+/eQotXX5TUIhtuLE+R9VWUWdPkQiWWps4sGmoqyYo87JE7SCWsEBmTdIe13NXCQ/6hQ3x1ja7YlJpK8JV/NL6jd9FXRoxVqzlmuoKqq+pIoQ8soMN/FfH+uQZR7iMqwJEouPgKW/KmupTavDMhi/jEUhGwBPGnKwOF1Jr5G1T4eopLXBsqKsifMBwuo3NNSOIiEW0kYMQj4ELmxTRzZ/Kxxf3hmWsrcNcChuVqTyOP/FoevYj64nqFaCyhujF2/+X9vuXfwoII8ihiIhSuAcsTUJDfVWwQe/tQ1vF9lRZd9BHFy15eTlkg1sn8tO5TmzjVnbW59ZFAunC4Z2CtwhXE6a+O1jf+Ob6yyPgEZBDwBNGOdyM13IltUaePmQqrTdZJjxOFh6bZpATuBrbIojRMZnMDZmEp023ZxtkVZUq7K+eeYo+/+3pRNOzrNRQ3TeJvlJ9Hl1x1XeVxyOyuEcmbw/iGFgsC/Iu965a8vJCGPPSz7jVrdqVXCYtkaKnLmgmbwezWcduak/hU2pknSlff6Qj4AljTlaAK6k1TJ0GqpgWVZtx0b7w5A1zMW+cCwTb5sbVBllVFb9zzeKr6Nq3vkU0SXS1Jpf/2C+m0D0PPKquwZiWmHUHrqtZ4h5dJoywrLZsN2e1lpkwG2tfpp9xdbIoTvP0wTSBdF2wjQcz3jImybFPqcE7K76cRyAeAU8Yc7QyXEit4QKp4J0yU4qbzOWOxcVg48vc7uBimmQ5MXWyyosXYkl2dKpN8cB7b1bOJmFME88QHQtPeVWE8UunnkCP/ttDPLfkLjPuvkba8Pgb3OWzFswS9+iqS2VeiJgN63rW9cLqq3qGePuD90Qx723xkAPvepbCA3/PGgOJNTOqvpq2tbsd98qLV6lyJp9bn1JDxYz5NkYyAp4w5mj2/7GtS1nMj+ywTX+cZfuJeqWUSLO0i7rMrQ7CCXU1VYFKJOKyShHE6D0hyvOPlq7MG4ysY7G18Yrrt8kNRPT+Nsiqqufp347cj147bpOqpRC0M+7xRnrutg3U2MibzFHd7cOHMIj3TYt7tDF3PKPNCxHLGgfIg4WuMrYPulQTyLysGRXzaWqsPqWGitnybYx0BDxhzNEKcCG1hup4EZ3wqzypxaYgyOuFfIg7CWKQCzFDzjnXRHng2gUREggs2bpMuii5QBjxPBX6B6izuy8T5IHgzZT1mdqIVh7300ba8CtzFsZSnU+Le/SEMdvU5+m9Hh2pS+9RdtBR/E7sUghmOSB5LJB5ngvRVWhqrD6lhujM+PIegeEIeMKYo1XhQmoNUyeCKqYlyyYyjiAyt6Ms4hzhcbnm3mvq411qbm3Gdtqwbqpymw5cUg9+SI1C6s4J+tj6KXTPnXpjGGWe87i4x/6BgWCD7prKJ96X1ZUVVtLEiGCrah2K3FNVWZfj6qMEkrmwMgIZ9y1R5XWgCl+d7ZgaK7wUmsbU6hyKb9sjUPYIeMKYoyl2IbVGFhJmGmoRa5VqtyKesZrKP8XTF5TR6cLL2weUsxXbaSM1QxaSHs6PeOdPV9GcR+dkz8HIJqqF6PTOc+iKRd8VmTrjZcNxj+HYYV35HkUHaCO3p2gfUV63cIxMn3jruJxvNzoGnnh3174LvPMgU87UoalPqSEzO76OR2AoAp4w5mhFQHr+bcuB8DY21VmmKIl8MOU7JlwAV0yc+rIEzlmFC3j67NomzRXrsU3CuMe4OnqrpYtn+pSUESWMYetaOD/in//vb3Tol/YnalbSLaLniJZ8+kY64eRTFTWotxkmWATRJrif8cQ9yvTortWr6LlfrafKygpqaWkJ/gSEa1wjHfiBg+j0s84dEvMpOr8yfVJRx5SlR0Vfo23Yel+oGEuYQBZdWCuCtbW9s0A49HAl5ZKKsca1Yco6vNuYWsL3zV8eAY+APAKeMMpjZ7ymK6k18vSBZsIy+BAj9jCILamuDGL1im5BfdRdyK5sJ7MYXNtM2lAJTdpEmCRtrA823GF51sCu+L3KoKss6X3UnW3uuWfS3e+8nSirRk0X0XvunUD/37MvyyxrK3WAUTR9RVrco0hHQRTvvesndNqX5tDs2bNjq65bt46WLFlK793vQLpo3mVBGZ75FemHrrK2UhBlHY+IF0nWe5moj3fQ3k311NXbFyiwYnz4PhXj5fvKjkCa2kvs2VgXCNX5yyPgEZBHwBNGeeyM1+zvH6A3t5mzfiQN0NSpYBaAYUGE9HljQ03QDAgiFEyLFsQB62qz6JNryoSuuBvbXF+m3duSXBaDdAy1xQMOrF1GEvH3pOvVTRvp0P/Yn+ikLE8OEa0juvvCtXTY4R/P2JC56nGEMXx32XyPra0tdMask+j005KJYnSUa9asoe9ds4Su+f6NdMC//rMSUSPdSJpyDVQ9jrx5vPCMP0yiQCCDdE1VxfdBZQUFZJLF05d6H/Dcy2YZk2Qf73VYbv3lEfAIyCPgCaM8dlZqvvF2p/U0DC5uLhhBLH5cKwKMQBBBGts7eqmrt9/KfJW6qUoVVxWDc2XzBdVDuF7b2AyZOvFm88VEUTq6+wJyiPU7qraKOnuQpqUvsCyI4HDzDctp4X/NI5omuSJeJPp8/Sm0dPlNkg3YqSbiTi2S7/GE5um0/LplNHnyZKGBvfLKK3TqF2fRLT+6ld6xz/jMKrhCN5cojHc6RNXy5gLpyiGXBOSxVdJIVDkRSFMeLT6lhqrV6dsZ6Qh4wpizFeBCag0XgvKZ4AfcS7HRxhW47ex032GbbJdjc1zb7KRtVkw9KjYPJEwSRhxyjKmvDkgiVD6xfkESsx5uXLN4EV371CKi6YIzllOyiFGKEMYwKnH5HuGqjjQn533lDPrKWafRtGly7Bukcc6cOXTfg486TxhtWvUFV+mQ4oElvq6KWrb3ZmnGmbp4JyDebnNrN1efBr+DSPlUvcsCyVRYRQ6buG6osJDsMyvaBRwg79VUL1rNl/cIeAQiCHjCmLMlAcsLNpU2LxtxObwEMYqLjb7yzo3o5oC33SzlTBKmpH7aJIzYOOuMn4zGI2JDBy/TbYrFrBBzt+DmedR2WCvRO1NWBHRb1hGd/m/uq6ImjUTV5pPNz1133E5trS00d+7cLI8TrVixIrDcff6kUzK1o7tyXgljdN6x7l99ddMwuMaPn0BHH3PsEEEi3ZjKtJ/V6yRMIOtrcBBF1FPo2xmvL+atINN/kTqmvs0+pYbIrPiyHoFkBDxhzNnqaO8sBC6WNi9Vm7NSY8CHDyeDgYtpdSXBEoDYwyAGsdDP7TrlWpxgeMw2RFbS1o3pGL64/sAq3NHVR6ryXaaNOfy76o0z5hhW8KR4RJ3PEmIab7lxOd317O3UdkBrfI5GWBX3O4Uumjefxk+YKAKVU2VV43j6rBPpp7f/mJqasioIEU35+FS68/61TuEV7YwLz70MQIx0/OjW2wZFiaIWYSjZwtp7220rAkGiqJKtzH111VG9jlnsbk11BTECyZTA8V8TauBJWJny/hnbUDMoPqVr3ny7HoGRgIAnjDmbZRdSa+hwpYwSRKYOJ0oQo9NpKk5Cdhm5YNHTSZhkcDG1kYjrmwrCGM6PmBaPaMKlDsItd62+nQrd26l21BgaO7YxGPq4xiY68P0H5ZoosjlUudH+1TNP0R+ff5YWLlyYuHxBQKCKesUVVwRlYIm84IILYsvDythf1UDTjzlW5nEwUse19xDvoLf+4zU6/5wzadasWYnqteG2MGeXf2MBXXDx150UddJtdWMEkqmFwwJpi0AiVn3b9h7uw1/eNREt51NqyCLn63kEhiLgCWPOVgSktbe29VjttQpXSmZ5qa2pIpZ/Sod8uA5yqxJ8EJTNrV1WT3rD47EpOMP6YTM/JdxhEQ8lGvsTzusZzo+YFo+Ypu6pcq3Jjk1lH3S1pdKTYMH8r9EXTjo+NnYRRBEkceXKlUOGUlFRQVu3bo21SL744ot0/Q230BWLvqtr+Jnb1e2KnbmDMQ3Agn7xBWfRqh+vpEmTJnHfAhZHEPzJHz7MuTyjpg/L2HvLRropFYdzPJPuU2rwoOTLeATSEfCEMR0jp0q4klpD9EQ6jiD29kHkQ29+KRfdPqMEzcQpK+8ithk/yPqo+5S9FBYi4+fNj1jqfiYt4HlVwuRZu0xtFi77Wa8zZp9EP3/wgWHNwFJ45ZVXBu6N4QtkEdfvfve7RDXVYz7zWbpl5Z1Zu6alvitiVyKDkyWL4Xsgn+YXZp9NB37gYJFbay1rOx9m+OALqTxYvmJmhVTpwiq6h5AF3qfUkEXO1/MIDEXAE8YcrggXUmukWcbC6oOIn8DHhxFExCCajE8z9WGSWUoiBEWmfdE6UMDd0VkwOj/RPrpKGNPiEUWxRnmTFnDX1poMXkl1VBLGr809m36yaqgFERapZcuWDd6ekUT8A/7e2NhIb7/9duKQZsxoph/eulrlkJW1lUfC+NXzzqSrv/XNWMsi5gpWxObm5uBP0sVSn7gUX2rKTZN38eD9BA2B+trKwW84ywGJ77ksgTS15vDO3mf3UbzD9eU8Ah6BEgh4wpjD5eFCao24zSezuIAg1tVUEdxng1QXvWYJYnRKTbm+yCwl2yfK0T6bdomKw0yle6HonETXtUg8oui9PGGUQSy+jkrCeNack+jBnw21MB5yyCEE19LwBaLIiOPll19eMubxyCOPpLWP/VfgUdHRXZDeaKtDbFdLsCo1jq6xHurAO7a0GNN999130AoMV1XEN4JExgkYLV26lKi6wRnXVJe/Vex9Fbiv1mQjkFnVYHnXik+pwYuUL+cRSEfAE8Z0jJwr4UJqDViiCoX+AJviB8QdghidMJctK4jXg9vPjq7srnQqFiqsexBCsNkflQImopgEhLmnnyorodBbSSLxiKL38oRRBrH4Oiqt0lBIffihnw25EQRwmMBN+IfKykoaGBigv/71r4lxdLB2/ccpX6Qf/+TuQC0XMv+wzrB8j6LxsupQK7Zk0sqtou+lYkyB9W677TbsNiCLCxYsiE2T8uljZ9DNK+5Q0bXMbbjsDRMdHPMiYgSyqhIurDsPiHv7gzWeZIE09Y73KTUyL0nfgEdgEAFPGHO4GGyl1gi7p4AgFnbGICK+waSLqeiUueBmmdRnlRtdUVziyrvQH5NxfQwDFfGIMviDkIKkmhCycvngRAa7cB2V63buuWfS4m8Pd3eENerCCy8c1lWkcXjiiScShxAnerNrvVUF9fAOtfUeNaHUm3V+WX0o/l564ZfpgQfWxDa5Zs0amjlzZuLtYG1ELGr4gtvqt6/9ofUcja7H26fNYVIYSuBhFPEyMnUw6VNqpM2a/90jwI+AJ4z8WDlTsrO7L5Cj1n2Vil/AqWJlRQW1Wc4JyYOBTdXNtP7ZdL+M65sL/TFh8UiKR4RVsaO7j/CMmbg8YVSDskrCCJfH1/66IdYaBbIxZ86cIZ0GWYzm/gsXSHN7ZKkOWJxYV29fkIc0S4yYCKqmrD0ifUoqi7lp2/p3+lJkDlj5aKxptJ24ucL8vOef9reeZgPrYPextbS5tVsFVNbbKKVjYOo961NqWF8GvgNlhIAnjDmcTF2pNZIU0np6+wgpL8LuJSY29aqmRuVmUlWfWDumYjl4++3C5lHX2uKJR8RaKfQPGCWMe4yro7dauninSLqctzDyQ3fizOm0/qknYysglx+sWHB/nDp1apCPMelCmWM/O4N4hVWwyW6oq97pDl108dMd9+jCIRHvzNy1ehU1jalNzLkI4v7kk/HztmTJkthDAMzfi3/8X+txjK59C3jnhLdcWCl9DEIf+gcGhfCwpyn0DfA2xV3Op9TghsoX9AikIuAJYypE7hVQlVojSw4mFbkYTSHrAglKGqsuciSLrQv9UXnSLpof0fThgim1QKwHl12zZdcrq6faxQ3EhAodsQQD94TCJv5Mnjw5VkyF9Quxj017vkuKjIQtNOG4R7iuqtxcm17zWeYa8zLpPe9IVD9F/CJIevS64IILKLD0xlxwY33ltbek5ijLWKJ1Xf5OqRwn2oK4z9vt3VRdWUHIxYzY3soKCg6mi0J5atb4O5rqqLqqUnX3fXsegRGJgCeMOZ12mdQa2DwXJbKrqK66mGMJKS6KOZYGhJOVI7/Rm9v0W0ayTpELJChpDCrJUVacUN8FrLKSKIwBG2y4TcMqjhga3vgw05vnrGMVmXPESsLV0eV4Y5HxhMvqsAx/6dQTgtQNIIUyF2IXL//GArrxNjWCKljXWNOwQOJSFfeommzLYMVbp5S7MPCGmm30SrMCu+KSavrdw4u56nI4CNm7afjeAf+OvQlScDECCfdslsZDVBzKp9RQPXO+vZGOgCeMOV0Bm1u6ApJX6goTRMhL48LpnSxBjN4LhPEfLV1OScTH4eGyNTTp42lrWbpCYEUOI1TmRxxdXx2cdKtIAM87hzhtN+GS6gkj74wUy0Fg5czZJ9E3r7yiZIxiXKsgL+edfwHdf/8a6qF6sRtzlI6Le+zqHh46wNEUuRzjHe3/q5s20g+XXT1MuAbl4kSJkFYDcYv4b9I1e/ZsuuQb37YuepOneeBZV0lleA/JshJI3Gfv3dQ/e1nG7ut6BPKMgCeMOZ29uNQaLEYL1kOcRDOCyNw8RE/o0qDJS0yUa6QsiqtLUuquKPWlYcLWOiyJOJHGGg+siL39wpby8HzYiOfyhDHtTZP+uw4LIyONC+bPo8P+7UOJ7qnR3kEY55Yf3Ua3rrqT/mn83toPA9jGGs8CS20gEvfoQu7V9BneVeKM2SfRzx8cmicTv4L4rVy5crAgUmm88MILJckiCk+dOo1W3/eISBe0lHUtJ6+WQRKRbKzm4P6mppJqq4surLBAMhXW6P4GVkqICPnLI+ARUIOAJ4xqcDTeSuuO3mCDHORAChFEWB1VbJx5BoSYqM6uAnX1FvMxunylERCbfQdh2NzqjqXWBaziLIyi8Ygyc2ojjsgU3uVsYdRNehA7d//dP6WZM5sDYhKXBB5E8Ue33kbHnfCFIB6O15Iis06T6sjEPeaNqCTlYdx3332DuFJ23X///YmxjqwMBG8efOQXdNG8y1ROg1RbezXWBernKuNTpTqiuZKqQzlmZa+prqD6mqogf3BPoUggsQeC63bj6BrNo/HNewRGDgKeMBqc67btHfTynzfSu/fZi979zj0z3bl/YGCnyliRICIW0fSHxrWk86UABSnb2tadyfqUacJKVIalFgcApucvqUsi7qC6MGHzhU2BbDyiTN9s5KQzSRjhtpiHAx7RudNNGFl/EEN3yw3Lqa2tdbCL48dPpHGNjXTg+w8aIpxiMmVKEl48cY958RRhY4Rb6lULLqEHf7bLygihGwjesGvBggUEwaG0a8aMZrp6if0cjOiny9+oNBxFfte1b4gSSKqgIPWXvzwCHgE1CHjCqAbHkq28/sZm+sHKB+jXL75M40aPopf/71U6Z3YzfWV2s/TdIVyxxXK+JsR74SWdh1yMLm+KXOubzY0Li0eEdD4u5KKDex0ORVS7VMc9fNhgjx5VTdva9ec5Zfc3SRhx+m4qx6T0y02ioinCKNI1WMRh4djaZm4tlepfUtwjkpvnzbIFi2/Llr8PkkIonSLVCa5SiqhhfNLyY4rMtYqypt4DKvqapQ1Tz+qe4+oGQ3Oy9NfX9Qh4BIoIeMKoeCX8+oUN9Pd/bKV/P+KDNG5MQ9D6D1asCf57yvFHBf+2Zu3TNP/qW+ix1d8NrI0ylwuE0cbmWgYr1HHZfdY1lzDTFs+4eESINLVs7zWu6GlDJdaURdfURk32Gc1Sz8Wx2VhLvBiG4x7raqqCNAYicY+899FZbvm13w4IASyJc+fOpWXLltHBBx9MEBxKu1AHwlYXzZufVtTI767EjpsYrCnXW59Sw8Rs+nuMJAQ8YVQ02yCFP777UfrIIftT+07X09uWXkr7v28iwRWVkUfc7vU3t9BRJ11M99x8RfC77PX3rZ2yVZXUc1l9NDpAXW4wKoB0rW8mLJ5p8Ygm+hA3dzY2+SZFb7yFUcUTy9dGXg7UsP7aO3sD8Sid+R75UOMvBeIx//IF1NPZHpDEjRs3BiI3cfGl4VZdI4vomyvq1Pzoy5c0pa4Oi62/PAIeAXUIeMKoCMvZc6+mRZecNmgxPO+y7wctX3fV+cPu8JsXX6bz5i+jx+68ZgiRFO0KT2oN0TZFyruuPhoei410CbxYupZ/S1eCd5H8iLr6kDYnNtwITYkeuWiFS5sP3t9dFPQJ1nt9VWApd/mKWrh54h5dGA9znV+//kn6/IzpgSsqyGASYYyKErkwBtaHvBwuZMXM1J7Bp9TIOlO+vkdgOAKeMGpaFbA4ImZxxdJLh90B5PIjk/cL4hizXFvauoM0AjYvU6eFWcdoQ8yEt882lDlL9U0VsciSH1FVH3jngJWzcdJvKmbUFqaicyBT3kXC6NpznYRrqdg5lfkeZea1VB1GdP/0h5eodacI0a03XU977L5L/IbVf3tbC33y6E8PESVS3Z8s7eVlrWQZI+qaUg72KTWyzpSv7xHwhNHYGgAp3O+9E+jSc/9jyD1VWRfRKJQ1d3QVjI0p7kam491kB2vD1ZC3r66dLsPiCYlymbWlKj+irSTWpjY04bVhijDawpT3OchSzhNGefR4XaKz5nuU72F8TVOxv6r7Hdeeyx4wKscvm4NRtA/A06fUEEXNl/cIlEbAWxg1rBBGCu+95cohojaIZTzu9G/QF48/ik49/qjMd8aGHqTR5uWymEwYFxuWI955cY3MirrIsnhExD9hUwmrN1RNs6RvyEJaeXGPK2dDfAKxWG+392hXgdWV3D4L3qrq2nJhLtV/VfnmVGEU147sAUlSvkc8+xBk033J9lt3v2TbL+fDnDAmppTVQRZxL395BDwC6hDwhFEdloMtJbmcXr38p/TyXzbRV2bNoN++9D+ByyryMj738x9K9QLKdrYl210TbCkFpKsn0q6RWZ6Nrkg8osziFiWtMvdIqmN6ncBKjzg33WlDdBJGHBog55kJshA3b7ZEktIIY3VlRaDG6eqliniZjnt07Z2ZdX7L2V08jI2p/cLuY2sJbqn+8gh4BNQh4AmjOiyDllbd8xj9+J7HCNZFpozKVFIP/fSXgzL7vW8ifeKID9KHD/7XTCqpLqTWMHViqGKaXI23NCUEwIthXLxnOB4RH2Ld+RFBWm1ttk3nQzPl1q2aMDL3Y7Q7MEDUj5vYWOQAACAASURBVP8hIiixwvth5//lXXaZyrlIGG0eevCCqUPkKS7uEWsCXgeq1oRrXhm8eCeVM/UOyNrPrPVNpZDyKTWyzpSv7xEYjoAnjApXxetvbA5cTuFuOm7s6EEL4jlzZlLz9CNow583ZiKIcV21nVrDVEyCimkylf9Jpq+mSUqpPrLNGKxeyHMGV1NI7ncXips+uJ3ptobZFIEwPRemyI4KwhiOUcXfsRZgQWPrgVmaxtRXDx4qdHTrJ49xGLa2ttCzz6ynttaWYcv96GOOpcbGJplHlbtOHgijbuKlK+7R5vuBewEIFDQVxyzQJS1FTX2DfUoNLdPnGx3hCHjCqHABPP708/T1b988aEH8138eTx89ZH+Fdxje1D+2dWnfvJcagI4Tal2AmdqYy/TflQ0D5rOhrjogibAYqYhHlMHDpqotrwiIzLji6phal1niQtnBUE1VkSR2dPelup+CjMAajT99/f3U3lEISKQqK1MYS4bhuifX0bWLF9GrmzbSPzW10pzDWmnSnsWSr2zZVWPFU0Q9u0+hJdfdROMnyOfCLbUGVBB0VWssqR2Tz5nKuEcet3nd2Kls37QbvMq+i7RlwsvHp9QQmRFf1iPAj4AnjPxYOVnSdmoN19wpS02SKXcYmYVi0yUpGo+ITX1tdRW91dIlMxQldXRbPkp10jR5N0kYMW7emLrwuujtGwisy53dfcLzy4jC2IZqqqqsLAoiwVKtUBzl5/evpttvuJKe+t1GmjWFaPbHiaYdULqrr2wmuuCORvrgZ+bTGWefKzyutAp5EDJhlrqHH/0l3b369mFDGtfYSO8ZP5FOOPkU5RbZLHGPebDepq0P9nuevqG8Y4orZ2qcPqVGllnydT0CyQh4wpjz1eFCag0Tp4YqpsnlTYYp0gAc0+IRbSiFRud3JBFGUykheNY/TucRl1xfWxl4LgSWRIUuyFhbsGCjfbg5b+8qBO1nIY/XLF5EY/+yaHAJLTxO7G2x9BGiXxVOoaXLbxKrmFI6D0Im9939E/rFIw/RvvtOorlz59KkSZOGjKqlpYWQ8P53z79A7/3X92sh1rihaNyjKfEUpQsioTFVwkMm+prlHvBe2W1MLW1u7c7STGpdeMc0jalNLecLeAQ8AmIIeMIohpdzpV1IrWEqLiEr+C4L9GBzuWLFSvrJrd+nysLwmKuP/r9TaPqnjqUDP3CwFAyi+RFNx/FFB4X+AhMbKsCmVEvZmG0TRrY2EHcIQrejq2gB1B2ninvhmRxVW3R/7uqBq6tYvCPI4n23LqKDJxI9uYFoxod3raSmBqLmD6VbGlEDLqp/aJxPF82bL/V8xVVynTAumP81OnC/9wZEkedaunQpPfZfj9OCby7W5sbLDrRgJcLGHxZpuDNH14br2PLgycq4lodXpO8iZU25P/uUGiKz4st6BPgR8ISRHysnS2JjhxxuNi+T1rEs43RRoAexVnfdcTv9+r9W0Wkf2RS40sVd6/67uKmtOeAc+uq8+VzuYVnyI9qOqbF56m7aPdiUq3TYwjhUjKQYlwhrX6GvqHRq+mLxjiAJTIG3FHlkzw3I4oLjii6ouOBmyq6WjuIzg39beirRpL1Kj2r2DURfXrZBGRkydRAgM1dzzz2Tjjn6EzR79myh6q+88gqd+sVZ9L1lNyrDqVQHkuIeccgA75oslmmhgWssXG4CPklQmTqwhRUTmPrLI+ARUIuAJ4xq8TTemgupNfLiHmTTzTFuYUDF8WunTaeLD/99arwVqw/iePkjE+gb19wZa21UlR/RdBxfFB+bbrGmD0BMWUtAGKurK2mgfyAQosFhE494jemXWrCG66uCONqeQh91dA2NdwRZvPj0o+miqZuoOWRRTOonCOPcVUXCeMikCpo1JZ4Uo9x/3D2F7nngUSVD3m1sLe3oLDhHamBZPPzQD6eSxRdffJEmT548DAuQxnPPu4BuWnGHEpxEGgmr8PYPkJZ4WJH+qCgLIlVZwR9brOKeNtowtU/Ys7GOsE785RHwCKhFwBNGtXgab62/f4De3GZPnAQDzssHz6bVKrowQBbPOHk6LW/+PU0WFGls2UE047pGWrzyOZowcSLVhdQoVeVHNG1li3twbLnFlhthjB4iwJIoI15j+uUWtoIi3hHk9n//8le6YPYnadUXN6VaDKP9XXgv0ZX3V1D/7clWVBDLI768lg47PMHULwCC6XXE07W1Dz9Iv//drwjupXEXyOC6devoiiuuoI0bN1JjYyM1NzfT1KlTg/82NRVTkSCusWV7D51w8qk8t1VeBgdauH9N8O4rxsN29fYFOUBV5ntU3vGYBk0RKRNjKXUPHKB0dhWoq7dfa1fgHVMJBu4vj4BHQCkCnjAqhdNOY2+83alFqp53NC66eib13RYJCfcnC1lk7QSk8caJ9MSv/6YlP6ILm11bc2XalVCHmiYOR+CWBRdPJl6Df8M2ilcllff5N1EO5HHrP16n8774SbrtlFeEySLrI0gjLI2lXL8f7FUTy+jCoUt0bk6fdSL99PYfDxI/9vuaNWto5cqV9MADD5ScThDHJUuWBJbHKR+fSnfev9bE9A+7Bwjj5tauwe+ernyPJgZnysPAxFhK3QNaBwif0Rkb7VNq2J5lf/9yRsATxjKYXdupNVxz9Sw1pS4out58w3Ka2jkv1Q0VLnIQ7mgaHT8iHUId7E4uuNNFN4WmHlXTGzhV+frCwkb4OyxysCSyDRoIZHVlRS4JI+b+9JOPph98er00WWTr58iriG47Kzmm8bAfqHFLNS2elPZ8/OkPL9HP19wxzLoIayL+8F7XXnttIJQDK2N/VQNNP+ZY3qrKypU6TFKZ71FZh0s05OLBgo5xm/j2Ik/sXk31Orrv2/QIjHgEPGEsgyWAUzu44di6TOVXUjE+Fz7O2Pj+9PPrY4kgSOIDv4NYRwW9tKk44qn7D9CMDxHNnjKcPE65ZgJ975ZHlQtQmCZNcXNrK47S9NhBGBGPBcVjmYtZEkESIV6TFJeYZ8IIq/x35ryLVpyVjNCLG4nWbSD62fMVdMHRxWcm7mJCOEnpN6Ze3Uirn3hDZiqG1LG1fpM6fs3iq+jYT32Spk2bNlhElCxWVFTQjBkz6L777iPEOF5/wy10xaLvZsZKpAHR+OZwvkd4KuL5UJ0HVKT/0bKurZMsY0mqa2qP4FNq6Jg936ZHoIiAJ4xlsBLgYtbe0Wt1JLZVNXkHb9vV8lfPPEV/XDmdoptViNlccR/Rky8nx140NhAtOWVgiDvdmt8SvfJPNyqPJcpKYnjno1Q5WxYaVRY/Xgx48iNG22JxiUy8BhvgtNigPBPGgOzUfGuYVR4HLCCJV9xL9MqWIkqVlZX02Q8O0P0Xlo5VhHJq3FWuhPHzzdPpmfVPDg75wgsvpGXLlnEtUxBFdiGu8e233w7+7zGf+SzdsvJOrjZUFcoSiy6a71FVn0u1k5dvZxYsTOVgHNtQQ+x9mqW/vq5HwCMwHAFPGMtgVbiQWiMvuRhNW4+iywt5405tWjQodANrB4jixi3pQfrYtH1xygDdduaujTBiGc98XH3ScRkSo/pRskXuTY+d937YdCFXYm0NctMNDFpKBjgzYeSZMH7q3/ahl65sHbbEIFKzLBJGh+dk2gFEj389GRjEMkJhNU5w6pgVU+iW1dmVUm25VCc9hyfOnE7rnyoSxjlz5gQxi2lXmCii7MDOxfb8888HcYxHHnkk/eSeh9OaUfo7ngPk2suao5XFPeLQBcJhPOlclA4EJ/YVRHs31VsXrlM9rmh7plKH+JQaumfStz+SEfCEsQxmv7u3L/PHMysMtjb3ov3m3ZyLtstb/vPHHErPXPD7ID9cGlGMbtZwj0l7Ev3fkqEqc5+++SC6+Z7neLvAVQ4feCgPtlm0XNtaU6bXSCmVYWYRGV1fFQh8QOEUbqcywhEuzCnX4osUQhqN1V/fP8ilGL1gYTzk60TIucguPDf7vqOC/u/aZDVGWOZRJyp+g/YWbThHiZslCONbLXYVrMN4nTXnJFr145U0c+ZMevLJXZbGKKZJJJGRRSilPvHEE9aEb3QkgLcV95jFWirzLNmqYyoHo0+pYWuG/X1HAgKeMJbBLLuQWkOH0qOOqbG1aWYuhB/74HupbcvGRItiHEmM4vC7q/qHWEYg4vGT9aEdswLgdGzKRLtlKqF9tF+m08RELX9R8Zqunv4gvlGGJIbHZuqUX3Se08rDjfu1u6fT3E/Fl4S1EIcv4Wv3MZW09cZkwoh4R5DGqGs4/u2lPRbTGWefm9at1N9tqfwmdQwKqW+8/iq99NJLqX1HAUYQw4UnTZpE999//2B+Rgje3LrqLq72VBUysY5Z3OOo2ipiAlI64h7zJBiXZf5M7Q98So0ss+TregRKI+AJY5msENupNUxbZWSnDR/o0aOqaVt7j2wTXPWYuxNcnd5841V66sknB3ObhRtgBDFucxa9EcpANfWJy4a60kH45s7HXubqF28hFzYyttyHTR8qMMJY6B8guMdB6a+UeA3vHEbLmdhoy/atVD2oe/7pRx9LJIywCuLQhMUwoi3EMfatKk0YYeWPWi2R3/Tqn2ygxsZivsEsl0uEEVZaxDC+9uqmWCLIM06QRVgW8V9cyNm46OrvKbHG8tyflTF9oKMz7jGvz6TIfKGsiRyM+Obus/so0a758h4BjwAnAp4wcgLlejHbqTXykotRVfxL3HoIW4bgztld6Ke//OWvdPuqH9PPH/oZYdPW1jY8Dot3bcWRRcQwnnT/Z5Sf8uvEiXe8psVnWL9MbuLYAQYsGZ09fVoTW5scF+8c85QL0kF852OxLqmsftTKCMK49Yb+kilpUDfskgrhqV9UXE4XXjyfegrZk4u7JGby7DNP0dqHH6TfPPd0QPhgZQTh470OPvhgQq5GRhZRD/8fCt2m02rYFORSHfdoylWTd551lTOhBOtTauiaPd+uR6CIgCeMZbISbKfWcMEixTOVopLsaW2CWGGzD8sQ2k6zDM0990w6oOf2IH4KlpGXNg61jCTdL44soqzKmKvwvV2IrbFltdbtjhsVr0FKDViPW7brVTrOK2HEuvzyp/ehB84vfdiy7wW7niVY7v+6ZCAxZyPEckAWmegNDl5O/fEEWn7Hb+md79g9iN9l8aIy5FH1eybtPcT7e1j4Jnh/vPJKkB4D/8WflpaWoClGDPFfxCw2NzcPu8WMGc109ZIfKrHG8vYf5Wx5HkT7qCLuEa6acDWXTakjgpvNsiZyMPqUGjZn2N97JCDgCWOZzLLt1BqubpDipjerqxiLR4RaJYRIunv7ufN6xaXVwGYVMVXBn01EL72yK9/ixL0ocEMNb27DY1r6CNF7Pr+WDjv840pXsgvzadr1jAEYzG99lVICx6zPUDkFtju6irngsFnUTVDZuPJMGL906gl0x8yHEi2GGCOeHwjgBCehFRX0+PwBmrZ//GPRfC0FOR2bRhPh+YMr6mXfX0sHfuDgnfWJsP7qaiqD/49nHJt6XkVaFw5c4kZ+1+pVRIUOmjt3bqb3xYoVK2jj65uVxHqKdsRWbHNaP2XiHl0hv2ljy/K7qW+JT6mRZZZ8XY9AOgKeMKZjlIsSnd19tG273ri8NCCyErG09lX9LuoeE45HhCUR8utBcnRJtcoTj9qP1l+0KfNwsNE99gb18YusY7bn03QsYZgwjm2ozqw8zNYNTr5BILBeYLUq9A1N96CDoMYtLlP3ybywYxoA0Wn641nDVE2jRWffQLRyffFf111GNDWGMML1dM3vivGLsNDP+tFQshhtkxEBkH3e1AuuEkaMDeI3P1j+/SHupSJzBkvkqV+cRXfeH8lnItJIhrK21JNFuswb95iHsYiMO66sqRyMPqVG1pny9T0CpRHwhLFMVogLqTXykouR5yMdF48YqORJksTwMsPmt+WJs4YpNIouRcRtvX+Weusi64ftGCxbFrGs7tWBxXCnmzLWTHC4UCImzhSRM3Uf0XXMWx4HLau+uCnRzRTthAVw1nyVaMaHhrcO6yLUUWGd/9/+KbTkupto/ISJXN0Ahmxu+/r7qb2jEJDIqOUR74/dx9bS5tZurnZNFmptbaEzZxdTbIRjEnn6wMji95bdyI0ZT7siZfCdQQhGVtVgkXtmKVsq7nGvxnra2tadm7HI4GDqPe5TasjMjq/jEeBHwBNGfqycLulCag0eIuYCiEmKbaLxiFnGcs3iRTT+74sSlR/T2ob73dXPf4auvUGfpL2oJTatz6K/m1K0jfZLRvAn7Kbc2zcQuJvC6s9zZSWoPPdAmbwTRohGzZt1KD15aelYRqifzrmRaMXZRLOmDEUHv124iuiTnz2FTjj5FGlXbpAAKCBDcRnxjjgUCKddAGGEu2HW5PK8cytaDlh+8xuX0P/7xJHc7qlwQ/3RrbeRTbKIcdp+L4liHS4fjXusrKyg7Z0F7pCGLPe2VddUaME7muqouqroQu4vj4BHQD0CnjCqx9Rai7ZTa+QlHiMsNJAlHjHrRCMu6+z9HqLmD4u1BLJ47pqD6ObVa7UKTuAAoHVH7zAXSrHeypc2RaSiPeS1DqEcNkP1tZWBhUDWTdnUOPNOGDFPUPp86uYTAzJY6jrkP4lmTSWaO31XKVjk2987ny6aN19+UcbUBAloqCuuAyaWAxEjWCJlCSNine9afTu99urGIXccN66RDvzAQXT6WedmfvZh+bl79e2BgvOcObNp2rRpgcBN9GJE8bgTvkAnnHyqUuxkGrPt+SDT57g6WDd7N9UHburRfI9xVmtV9zXdjol9gU+pYXpW/f1GIgKeMJbRrG9u6SJYN2xdtlQtRcaLD0tjQw1BsKayoiJzPKLIvePKLpj/NRq98Xpa+LldQjdJbcLdDhaSX7dPoWtuuDPzhjGt77YtxjKWvrQx8fxeKv6slHgNT9txZTxhFEMOpHHld8+klae1JrqnsmcFrqfs7zrIYrTnWB8gYiCQRFC/hEsyv1gO3NV/8ejP6X3/vG9g+YtzGV23bh0tXLiQ3rff++mr8+ZLvwfY+/q1N7cE5HTDn35PsHiFL3iuHHrYFCeIIutXuRDG6HuGN+5R7GmxX9pEDkZgt/du9fYH63vgEShjBDxhLKPJtZ1aw5Tao+iUReMRYQ1CkvS2Hb1OxI5gA3zPquX00bHrY0U9kIJjzW+J/rdvCn3uS/Ol3ehEcbOtRshr6RMdV1r5qKpfnHhNWlxi2j3Cv5sixrZcfEWw4C0Ll8orLjmT/qVqPTV/iGjaAcNrQtxm3QaiX74ygY6bM98o6WGHAL2FAYLoERPKgttqktIqUu5MP+rf6XMzZ8Za+qIjBHG8/BsL6BtXfmdQ3ZUXP5Szmc9QpJ/hsi6LCYmOqdRBUVLcI1NWFr2XzfImXIhhzUfMsL88Ah4BfQh4wqgPW+Mtw33QZj4nU5YSHmCxCccpP2Txo/kRXepneCxwQ3vql4/QW5u3DtlUjmtspKOPOdYYUWR9MuFKVGoubW4OYcXAAQw2+9iM8IjX8KzLuDKm4t1cXfeyuKEenpnHHnmI/vzbh6jQ3x80NX58UcAGBy1HBbGK5t0oo0IfzB24trqKegp91NE1VAgpiGneZ0/ueEKGGfImIh/i4qU3CIvQwDUfRJY31jbLPKmqa0pxU1V/S7XDKwajIt+jifEk3cOERRihAY2ja2wO09/bI1D2CHjCWEZTDLII0mjrsrnBx5h54xFd3nTYdgMNrx0XLBAmNhvhMbM11FBfTVAeZmImvPn3ZJ49U5bUciSMwNv2eyduzpPIQNhazcRyrrhiYRALCzfT8LVmzRpatmwZvfjii3TwwQdTc3MzTZ48OYg1DF+yyqW2D4RknpVyspJjzrF22zrEvtlJ+R5djHs09Wz6lBoyT5Ov4xEQQ8ATRjG8nC7tQmoNk7n74tx2eIRHmNjAm9u6nJtPxHvs6CyUTMNgqtMuxKSaWE+74s6qAssuRCiwAfn71k4jUJvaVJUzYXRNkZTHeoT30Au/eYZ+/ezTQ8giCOCRRx5J+G/c9be//W1YbCPcUx985L+EBH1su5zLPFw8uMq0a6NOWHxN9v6uxz2aOpyFOyo8QfzlEfAI6EPAE0Z92BpvGbnetljO+6U7R5aq/IimLVe8i8GlU39szmAFET0B5x0rTzld8xReR/h7V09/4M7Ncrsh7uatFjMHCqYII9u84VBFRIiFZ55sljHl0isyRjw71ZUV1N5ZKFkNSsl3/HTVkJhFiN3Asph0zZo1i6BcGr1AMq++9ofcrqkueTPwYuvCO4m3r2nlVL/rXYx7NEXwfUqNtNXmf/cIZEfAE8bsGDrVgimrSNKgdWxCSsUjyoKvm9jK9ssFN1DWdxdEjFQLJmADg5PomqoK6untL6bCKBRj38IX7ru5tStRoER2fuPqRUV2VLYd1xZz6+vbmS8ybvy6+6CyfRcJI0/uudbWFrr0wi/TAw+sGYQDMYn77rsv4b+lrhdeeCFwTw1folZG22lzZNaAC14PMv2Oq6PjW8nu40rco6n5gieKvzwCHgG9CHjCqBdf463bTq2hys2JNx5RFmCdH2vZPqEez0YzS/sidV1wYVRB7NlaYuI1ELDp6h1OEqOEcWtbtzEVXZMWTTZOHMQE5Lm6cid55k//ILKOdJd1kTDybJRvvmE5TT38I0NiEhG3OHPmzFTItm3bFquketgRH6d7Hng0tT4KqD6M4bppxkJ5FOpJGrJJ/G3FPaq2osZh6VNqZHyofHWPACcCnjByApWXYlvauoPNn62LZ6MU1zfZeETZcZrIDSXTN1MuPDx9M5XuoVRfZK0g6PuY+uog3ybcTEXFa3Dflu3m0q7YIIwMd5Z4Hlj1FvoDRdiCxXyuPGszXAbvnOrqStrW3iNaVVt5Hk+BC889k2784XXDiN8hhxwSCN0kXVOnTiVYE+OuqVOn0er7HuEal0nCwtUhjkImCAhHN5QUgbv9P1rMeDGEO2wy7tFETL5PqaFkOfpGPAKpCHjCmApRvgrYTq0hQnhUxSPKzBDPhk6m3ax1XLDqsTGYiq1LI4ztHXwiQGwjNLp+l3gNDk9YXKLI3MgSVZF7hMuaEPfh6RvWHzZgVVUV1NlVSLXE8rSpo0xxrot95RG60tGHUm3i/YJcr6VSVpw+60R6+KGfDWsGYjdwS026FixYMExRlZWdPXs2XfKNb1NjY1PqkHXFB6feOEMBEwQkQ/eEqrqAv+64RxOHEj6lhtCy84U9AtIIeMIoDZ2bFW2n1kgjPDriEWVmwiXXz3D/XbDqhftj0/KFfqRtEKPiNSCIUDnNaiEz7bLsCmFkcx+1OuK9ojO1CO8zzNyLUT4p/pS3LZ3leCxhSYQR/SolfJPkjop6SL3xw1tXc82Va2uOZz5MH+Tw9EmmjAuHcdF+64h7NLHGkH8R33N/eQQ8AnoR8IRRL77GW7edWiMup5zueEQZkF0QdInrt2sbCRMf/FLzl7TxxvyNqq+muurKwIVSNXkY6YQxPCdhq6ONlC/h3IW9hYEharYyz76JOjyEMU4hlfUNojdwTY2m1ijljoq6cEn95eNPUF9/P8EyXyo3n+3DIJl5MGGxkumXaB3XDgbj+p817tHUt8yn1BBdfb68R0AOAU8Y5XBztpYLqTVAMrZt7wncxbChx6bFNbexNEuozQm2TdLCYzepFhqHeVjkInzw0LtT4bOUy1+WOcSGv6MrXkE1S7tJdfOweQdxw0l+XU0ldfcW05DotDpiwwnXzoqKCurq7Svp3qljTrK0ySP+FSd6E74nyCJcTJ988sngnydNmkT333//MHXUMMk868vn0dLrbwrS4YxtqA7+y+J3w2q4pjbzWTCMq+uCG6eKMYmEbqi4X9Y2onGP3TtjnXFYl/QOMEWKfUqNrLPr63sE+BDwhJEPp1yVspFaI+waWFdTRZ1Qotz5R+emUnZi4iyhsm2prufSpsj2iT4IA8RYMF9MvEY2LlFknngsRCLtpZXNA2EMj4EduODfeGNM0zBgvwepT2oQhzoQ5DGUiUHlvZeucjwHDq9u2kg/XHZ1bE7FcL9gbYTIDdxNS10o8+Qzv6Ezzj53sBhzLUa8J8gj3LXZ87PHuDpjuUZV4ezSYVqWMeHgBe80mzluZfvPLP44OMJzigNh5LHF9z78rJoixT6lhuxM+noeATEEPGEUwysXpf+xrcvIJou5quHDgY8Iy2uHk23Vm0gdwLtEzMLjU5FKQhVeNmKG2OEDVE6R8gGHD207zCmWAjsbhNFU3kdVawPtMKvjqNriIZGs1RFzzjaYrnkjyODF69J84szp9ODPHohNkSF63xkzmunqJT9MFLwJzxVrG6raLh7oxY09r1bRuLG4KromuuaicY8gjHgPYC+AfUFwoNRZEG2Wu7xPqcENlS/oEciMgCeMmSF0rwGdqTXi4hE7uoeKjLiasiI6U7ZkzdNWDO9mM60dFb+b6ks4Tg2bACZeA8JYXVmhddORtKFLU7lUgS9ro2l0TaBMmoeDlqRx490welRRfII31jEvIjaic8373Ny1ehW1bPl7ouop731hXXzwkV/QRfMu46oCcg7SUllRMWghwnvcZfLoslcIF+ihQqYPpET7J1uexT2CLDJPI7wLSsXSyt4L9XxKjSzo+boeATEEPGEUwysXpVWm1mDWHpF4RNlcjKbBhSUPsZZZFTVV9ztNGVT1/Uq1xxOLlaU/gfhQbVXwJ068xpRbU3QMNiwAzAIEkly01ru9gU+a97RxhN3X8yJiI7rGRfJ4XrN4EY3fZ89AGVXmQqzjueddQN9ddgNXOo1go43nrq4qyDUakPb6KqqtLroX8pJ9mb5mqeNy3LnouFx6x4v2nbc8ngE83zXVFYE7NE/cI2/brFxDXRU1jakVrebLewQ8AhIIeMIoAZrrVbKm1kjKj1gqwD2MCTb5+EC4Hp/BawUwPd8unT6HRWdUAAdcHgAAIABJREFU4RC2UrO4xKS1xTaz2NiavGweeria0kIGf2Z17OsboJ7evuBgII8iNqJjF3Urn3vumfSVs06jadOmCd0KZPHUL86i7y27kcZPmMhdN+4gJmzlTxLL4b6BhoKuKlvLDNV2bLhMn0XrhMfIG/coeg+fUkMUMV/eIyCPgCeM8tg5WxOb77fbe4T6lxSPGFbW420wLyfBLhGzMLY2yUp0jlX1BYcQEHqA+IaIeI2tteRKnk42fhAu1alDeJ/nrOVAToAn5r2yggKBjLxaT3mxECUEra0tdO3iRQFOS5cu5brNihUr6O5776dvXPkdIbKIxtMO9cJiOVWVUFotBCq1NgWIbHkbcE2GYCFXwyEEh1GyeJJAUam4R9H9xm5jaoO17C+PgEdAPwKeMOrH2PgdeFNr8MQjynQectp4kW9u7ZapbqyOKjKkusOukBWMK0tfwuI12CSAKMD6LbLptEUYsQmxETuZtJaYKEwgAtRVoK7eftXLTml77IAA7mgsrQPi48LWU5BgHG6JbhKVdlRTY6KEkXUDMY233fwDmjmzOXBRbWpqGtZDEMUf3XobHXfCF+iEk0+VGoHIu4+tvYY6kP6iIqYNwp/lXSQFksZKrgquqRqyiEBROO4xbNnmiXvcs7EucKn2l0fAI6AfAU8Y9WNs/A79/QP05rauYfeViUeU7Xwe5M9dlTZ3yfVK9FQ/Trwmi2UMaxaW4K1tYhZz2XXL6omOO+v9eOurUiXlvZ9oORERG+bVALEfkGDEOLksuiKCRdY0Kb965im6e/Xt9OqrG4fd9oSTTgmIItJy3HLjcmprbR0s854JE2ncuEY68AMH0WGHfzyxy7IxumzOEDvG8uvyhiqI4BdXVrbPWe+rur4ImVJ9b1PtMVf0bYKeTqL5HkG8K+G24C+PgEdAOwKeMGqH2M4N3ni7M9h8ZY1HlO297YTvPP0GMRtVX02iHzWetrOUsWVVi+szbwwhIwpMvCbIwanACmZrc+USaU9aS+H4QJuWuvA7pru3X9h1sZxiNtlc6bQggUzCffVfKtfT3E8RNTUMXyErniL6xWsH0YXzF8cSRxWxyWz9wSrUU+ijji691mJXQwhE3/WmEtqL9ktleRUHbmlxjz6lhsoZ8215BNIR8IQxHaNclsAGEi/UcH5Ek65frgrKhCfTJWIW7pdLG4pSGKGfyJVYW7MrLlGHtSGrtUbmAeYlyjJtq64TttSZVLjE+wVWH1gIYUVGjFvWix08VFRWOKvWmTZGjAGucn/f2plWVPh3iOMc0HM7zf440aS9Sldv2UG08D6iHRPPoSsWfXdIYZXkKxzvqFMsR7dis/BkSFbIw2GU5NAGq4m4PPPcKy7uERZuuEn7yyPgETCDgCeMZnDmvsvrb2ymtu0dtP/7+BXv4hpHjMn2zqH5Ebk7oaBgHnIx2rJepcGLj+NejfX0Vstwt+K0uqp/j5JX5jI0ur4qsGBv7yoEKSBE4hJF+2jDvdnVw4RS2JlyV4X1oL4G8z8Q5MfUMfdsLMjnBqslYl9dd1cFLoGrZmFAOFaX55lYMP9rdDhdH5BFkWvdfxNd9ouD6ObVawfTboB86bAIhudNtVgODiGRMsq1NEgic4GyaYJDou25WF7lgUTc+IoHetXB8+Yvj4BHwAwCnjCawTn1LiCKsy/8DmFX1L69gz5xxAdp0X+ekVovqQA2cu0dZlMRhPuSl3gTG2SEZ1Jd6RcIIlIEtHb0Bh9n/H8Z8RqeMSeV0enel3TPPBLG8FiYu3VvQdxFNA6TqDVRhyU5bS7we3tHwSmRnLA7riorK8aJ+MS1Dz9Ijz7y4CAsb/zPepp6QNEFtflDRNMO4H+qXtxIdOn6zwxaGncfW0vtnb30zndN4G9EsCQTM4EXAqxBWcVyZIWEBLutvXhevo1ZgDCR43hsQ03g4eAvj4BHwAwCnjCawTn1LrPnXk37vXcCXXrufxAjjzOnH0Ffmd2cWjeugExqDakbJVRyVVAm2l1XYy1dkF0PLEm1VTSqtoo6ugrW0jrYmCOm9Lulrdt5y1ap55bFmUEXQoZsiYjYqHx/xLXFrFdwQ4MHhU2row53XEYUr1m8iLr/9iDNOayVmj88HAm4mi5dSwQSuPA4oskpziivbCZaeC9RSwdR0+jh7b1VN4X+beqxdMLJpwxaIFXPZVQsB67ToiJHNt4DqnFAe7qtbzr6LNqmCXLvU2qIzoov7xHIhoAnjNnwE6q9Zu3T9Munn6eX/7yR3r3PXgE5BEnEdeC02XTbkkvoo4fsH/x/lL1+xRr6xR3fE7oHK9zd22dcWTLc0bxYaFx1cxJN/C21SGIqhcVrsKGDeuXu4/TEY/H22cTmI64vjGzBSmeTnPDiVKocI1tIywEX4lJpEbKK2Kjob1obbG5Qzkbcpo4Yyz/94SW66vzptPK01tT4RIwbxLF5SdHaCPGb6MWIIv4dxLJUzCPcVi9/ZAJdsOCmkuqqafOS9juLRRvbUE1wWQ3EsThTq7jidZE2xrTfEa5hcs2m9UfH7ya8QnxKDR0z59v0CCQj4AmjodWx6p7H6Mf3PEbnzG6mj0zej65e/lN6+S+bBgkhCON1V51P/37EB4Mewcp41MlfG/JvIl1NSq0h0kaWsnnJxejqx9ukaFCceE04LtH2yT6waNneqyVWjmeNs8MP5A3MkiKE5166y5RSJGXrQKWIjYnxwJtBd6wjI6gD/XriNhlZfOC81lgrYCkcYT0EOZz0DqK5RxetiPj/c24kuu2sdHEc1jYTyak6aD5dNG++7qkbzMlZX1tJEMth8dBx4mwuxXVnBcbWYWDWfvPWN6UN4FNq8M6IL+cRUIOAJ4xqcExt5Tcvvkzv2nuPwLKI69cvbKA5F36HHrvje/Tud+5JcEnFfxddevpgW2E31dQbxBRgqTVk6qqoY+KUMWs/VcjLZ+1DXH3dRJZZkVgMyI6u4kl/nICJ7Q2OSfJcai6Z9RWESsa9U8c6ydImI8L9A0RwWQUh1iVik6WfPHVBKOqqi2lyMA5eq1Va20zIRic2iFe8+PSj6cGzNwmTRdZ/kMYr7gNZrKDZUwYCd1URshjGAW21v9cMaWT3DQs29Q8MDBM6MkVC0taDit9tH8CpGEOpNkykq8J62Wf3UbqH4tv3CHgEQgh4wmhpOYBAghA++9APaNyYhlgXVGaFXLH0UqleIv4KliJblwtxeGljVy3/nXY/3t91ENmwqyH+jrWBU/001UHbbru6yTPvnEQ3t3DvzKtrWTgGD2IkgatgdWXggqwif6YopirLw1KKOEcQ+zT327j7svxvEHkKLMqaVYBPP/lo+sGn13O5oZbCad8LiDZuraCJew7QE/P5LYtxbc6+gejLyzbQ+AnZ1Lpl5jUa74j1CbdwuLFubeuRadKpOnk4SM0CmIocjGn3r6mqoL2a6tOK+d89Ah4BhQh4wqgQTJGmomSQuaDCwtg8/YigKZR5/c0tgVuqzPV2e09w0m7rsk00eMbtqsS5SiLLTnxhgcF6EHWrtG3hczX/WjguELiqyEPIs2azlAm7VkbXgam0HFn6L1I37H7LY3UEiYZ7a021urySaf391TNP0R9XTg9iDLNeK54quqHOmVpBt545kKk5uLTOe+4UWrr8pkztZK0cJo+wPMI1HYqrrqdYSRp3OVlKk8ZoQgUWhzlNY2qzLi9f3yPgERBAwBNGAbBUFUWexaNOvIiuW3RBEM/ILhBEiOJ8/5vnBf90/uXXBTGPjECK3t92ao085GJ0VZwnq8osc5+sramk3p0uerKExjZhc11V0CX1zrh3hIyIDSOWPERL9L1kozwjHnFWx7C11bSrMXIrnjPx+pJKpyBvy9YSzfgw0bSiJlriBSvj7KlECz6XHWWbVsZo75lrMP4d8Y447FDldpwdKf4Wonlt+Wvmp6SJ97VPqZGf9eB7Wj4IeMJoYS5LuZpCGXXV3Y/Sfu+bGBBFWbKIYYEgbNtuz4UHbpWIiYPCpKuXqx9wWAXr66qCE3Xei1lIICIB3FW50+lwj+UdE8rhxLrQP5ALCx5LReKCsqoKEZsw0cqr+214rUVFf6oRvIn8jp0F46JKra0tdOkX9icI3SRdF64iWvZosY+4GhuI/rZkIDHWce4qotkfT061ASvkyvVIyVGMdSxFQhEHef3GcwZzN4o8s6rLhj1B2ByGxXJAHtNc61X3SaY9mfe6zH1s1jGRg9Gn1LA5w/7eIxUBTxgNzzyUUWdf8G2695YrCZbG3770P0Wr4lXnB7GMKi/bqTWyWslUYpHUlqvqe7yWT2Y9QnJsjIUlD48Tr5HFU6V7rEwfbN9fps/hlBw4uFE5H2n90SHU4roVNQ2T8O9hfJAeA5cNMgxl1Geu+1iiOypSXRy5iKgC4Ieu+y8coBkfKv5DoI5a1FELLhDCpgaKzd+I375009C2UOevSwYS4yePWTGFbln9qAi8WsomvQPw/ivOZzX19fcT4h1LpYzR0jmBRl0NgRAYQmpRE6I+PqVG6jT4Ah4B5Qh4wqgc0tINnnfZ9+k3L2ygsWNHB6qosCB+5OB/HVRPVdkd26k12KZ5W7s9KycPni7m9yqVliQsysHEa0TjEnlwYWVA/IPE7512LMW27y+CVbSsqZQc0UTysLjoivNiMbHFNCPpoklZ8FNZlxHFqOXdVuzmXatXUdMfzwosgnEXUz4NE0b8/fyjB2jJKcUYRaTCQBoNdsEquOa3xbyL4QvlDplPtHHLUMKI9hDvOGtKfMzjjO830g9//obKaZBqi8fLIU4sxzXymMfDL5EJw7O0d1M9vbmtS6SacNl3NNVRdVWlcD1fwSPgEZBHwBNGeeykaj7+9POBZRH5FlVbFOM6ZDO1Rl5yMdpKDF9qAcVZPgN3ptoqaqivpg6oWSLptQEVXBOqd6WwKIdT+bB7qMo4OUbekB9Q56FB3PywA6HgMKGjQHH586RekgorgUhDIAOxvMz6Xqp5RvBRRveY1j78IFU+c2IiYQTxm7lkl4UR5G5gYIAe//oATTsgfhSoA6vj3E8N/R1E8pCvD7VWMiJ6/lH9tOTU+PZm30j0rfs6FM6IXFOicXFBDHd9FdVWV1FPoY86uvqcWJ+i45BDy14tE6I+PqWGvfn1dx7ZCHjCWObzv7mlKxA9sXGZOm3MOjbbKqBJ/Yflc0tr9+CGl8Ul6rQelSIGtizFJvJ6ZV1DvPXDyqqybpAyIja8/ZMpx8ZUVwMVXjdcAqMWV1HBJxMuuGkKqSB++87dRfJAFmdNIVpxdvIsLX2k6KLa/OGhZUAkP7d0uDvqxD0G6IVvDbVShmtOvbqRVj9h38Iom1on7I3hglhOHoTgZN4BrI6JdzWe7b138yk1ssyTr+sRkEHAE0YZ1HJUx3ZqjTzkYnTtI87ichCXCJKIXIm6c8GVWtK88ZS6HgubKpa6xhR2g4Tli8d1jinfQumTx1qmq+9J7UYFZSB2pcstNqkPDCP8zpNjlAcjXVZHiN785wnvojVfTe7FkVcRvbKFgpjF5g9RomWRtQCL4MLPDc/ByFJuhO80eQIFlsUkayXKuhLDCCEVfMuyxAKHxXKqKmFxLgRCWlna5Fk/4TIqxiF6T5PlTXiDwMtm97E+pYbJefX38ggAAU8Yy3wdtO7otapSmodcjC6ouYatRvg7LDVQAUSiapMbmrjHwRUl2XInjp09fcGzGiVZOkRsdL/2dJGspH6bwChsSe3u7Y+dK1Fcj59xNP3qK+tFqyWWB8F84rLhP8NaiT/smjwx2arIyqD8og1uqKSqDhvAOw3EA4dyyOtoyjJuQhBG2WKSaMjEtxQx7Y2jayR656t4BDwCWRDwhDELejmoiw0oSKOtS9aVyGR/bYqqsDQMNVUVgRUxHIfmiqusibgUkfkuR+KI8YdTcsDtGJtZZk007YYsMh+lyjJreU013FWLufNUWh0ZUWTPjonDFRDHuupKGlVfTVljR9OEb0TmAaqqS9dSSYulSHsQ3ZnQfCdNP+ZYkWpaysJTRZeQSlQsh+V4VLlOGSguCqypnDATMZo+pYbKGfNteQT4EfCEkR+rXJa0nVrDxIlj1okxnRuLuc3hhLu70E+dELCJEa9xyVVW54ZNdv7KkThiLTaNqR20Kmd1w5PFVnU9lUqkokI2qscSbi+cp7JIWsXdcE88aj968OxNibkVefvffG2x5NJTh7uk8rbBykFV9TO3HER3PfycaFUt5U28f7BGEec4tqGa4LKqWizHtYM3HRNlIgcj3FHx7fSXR8AjYBYBTxjN4m38blAuhHCKrSsPuRhNxOgxlUyoNTLxmrS4RB4peVPz6vLJeN6JY5KIjWm3TlNriamrilrnsgrZ6BxfOH4T6UZgSeVVjX1100b61lcOpQfOa5XuIqyB9/5pQlB/99pWevJS+bbQBtp7/6y1dNjhCTk/pHsqXtEG0QrHO6oSy8mLarj4DO2qYUKzwKfUyDJDvq5HQB4BTxjlsctNzb9v7bTWVxOqaVkHp+tDjo0OTkJH1xdPQ5HHMI0khsfiUs6uPMTe5I048orYsHEhybyssmrWZ0RH/bB1rtS4wkI2plOHyIxbxuoI19S/PTqPlp0sTvRA7trfO5/mXXoZ4Z3xs589QM/ddnxgaZS5IJDzcOsptHT5TTLVldfB+odVabOlg89w7GplRQUlxRqnDdy0J0taf1T/bkoVHYeX/vIIeATMI+AJo3nMjd/RZmoNVwRTSoGu8kMXFa8BQZRVazShOMe7GPOk7uc6ccS8BmIbhf7gEIE37i6ckiPJjZl3Pl0ql5TCwoSQjU4colZHuKsWSqQ4Ql7Gld89k1ae1hqkxki7IEoDsviOwy+jhQsWDB5KYT1ds3gR9f1+UaCY2jQ6raVdv4MsPkNuCN2wXpnwAOFFCH2Bl4iMWI5L73Pe8YqUM0HsfUoNkRnxZT0CahHwhFEtnk62tqWtO7Bs2bhUkjGd/c8aI8MESyCGAXc0FZYQl06kXRHgEVkDLhHHqDtlFvEXmZQcIrjZLIs1P240JPMHgneWCKG22e+0ezM3XJQD2UfscpyoCtxTr7jkTPqXqvWJaTQYUewZfyotWLiAxo+fGIsT8jwuu+JM+uanNqWm42Bt7vGx+XTRvPlpwzH6u0vvwfDAmSUZXiR9/f3U3lEIFFeTxHJc8hjRMYEmvIl8Sg0dM+fb9AjwIeAJIx9OuS5lO7WGibiGrBMkY0GLiteABIgmCC/Vb5dO1vNIGBm2Nolj2Eqm4hAhvF6YBauhrkraTS7rc6OqftF9uzJw4QZOiAMcPaqaKiso2IjzxgOq6o+udpKsqdH7/ekPL9HaRx6kHW/+nja90UotHbtKTJo4qSRRDLeFXI+33Lic/vLU9XTke1tjrY1QV+149ykBURw/YaKuoUu367pljqnmYr2Winc0oSAqDbKCiib0CnxKDQUT5ZvwCEgi4AmjJHB5qmY7tYYJ5bSs88FLiGTEa2T7ZsLFh7dv2Ox0dffFqrnytmG7nCniGCY/yNdnIjk4O92Hm2tcLkfb2Cfdn80J0m7AdTt64BKOHzOVK88UVqKiRgwr9E/U8gri+Owz66mttWXI8MY1NtGB7z/ISaLIOmoz7ZHoWoiK5WBNw1KOAw+XVK9Fx8VT3oQiOvIvYj34yyPgETCPgCeM5jE3fkfbqTV4yZhxYEI3LEWIWFwi4lawIdjRVcwnxxt7Jjsu3Guvxnp6q6VLtgll9VxSbM06KF3EkVfEJmv/S9VnJAQWOtnYWZ39Y22LCvmE4wHzRorT8EyzOmYhimn3zsPvcOXsH8B7t5CH7g72keUgbairDlxWYX1EeEipONZcDTDSWROHij6lRp5XiO973hHwhDHvM8jRf9upNUycPHLAULJIdFOCTRzc4+Duhw9/FvGaLH1zJZ0F8KmoqKC2jt4sw3GqrgriGF4nIGmilh9dgIhar3T1I9ouLKFw3cuClatjU4FheGxQjmX55lxZVyrGKNpGObhyYl5BdnAhzrHcrOUYlwlPIp9SQ/Tp8eU9AuoQ8IRRHZZOt2QztUYeXIpY/EVPb1+wScMfVeI1WRaGK+ksmNptlo1+Fhx01pUhjipFbHSPLVjbVXZTcuhQPGUWHLiz4kAHKqRJgiM6MVbdNsY1bnRN0GwxJq6QKzdj1XjAlbMc0smww7/AE6G+imqr+cRyVOOpqz0TWgU+pYau2fPtegTSEfCEMR2jsijxj21d2l0ok4AyoZ6WZZKYguGo2iqC+y5EN7KoWGbpS7SuiVNbkf4yrMrNLRAY8BBHnSI2IvMgWjackkO1OFNSX8IpZgLBn95+Le+gsGqsbI48UTx1lI9zPWWCKqN2xm2VA3ESxQ4hDRBuy7MrJ+Z2j3F1Q8ILwt4JpcRyRPGyUd6EGrpPqWFjZv09PQK7EPCEcYSsBpupNVxS+2TTjY8PLC9QZoRVAuIkNdUVtLWtx6kV4Wr8J+YUAgR53qCXIjpwwYVVDgqdiFUFUayrKaZMgTuZ7vhVXYswLV5OxX3ThGxU3COpDfauCWLeOvOhrsobo8jSOGBdlpNFNW09wMtia1t3bp85jA8eGruNqaXNrd2xw40Ty8G7Ji8kOW18aXPM87tPqcGDki/jEdCHgCeM+rB1qmWbqTVMnD7ygB0Vr8HGH0IK2Py7pEgaHosJIQEe7JLKjK5HnGd1rMJllnZdqDtmVDUh/hZXR1eBWnaUT/ymjpQcPBZaU/MaJlfIe9hlKQ9tqfHyEsVoG2EBILiIg1iUS9qROLxcccvPsnZFvGyYqzVE1vIS72giVyb0BJrGFONA/eUR8AiYR8ATRvOYW7mj7dQaiG94c5t5tc848ZqkfHi2+lhqQeRBnTTs7pgXq04S5nEiNsHGvqEo5V5OOQEZBlndjMPKrK6Js5iwqIq+0MPEumV7bybL2UiwOroi/CU6z+HyzEMB8y1ysfkFWQJ5dClcIjwOEzkYfUoNkZXjy3oE1CPgCaN6TJ1sEafQb7fbc7c0HYvHUhw01FcH1qHAlTDFymAiaF90ccA1MiAqne5LymNzPnZUTeDamzdiFXWjjIthLWd1TqyxMPFLOlSJboKxkc2LEBKz8tiyyum0wIZdGnsL5WN1BNGCpS3JlVP0fWqrvIr3OHs+qyorqafQRx1d7liWTSihw6UX68FfHgGPgB0EPGG0g7vxu9pOrWEiFo+RxNqayuDUXvQ01jSp5VkE+EBCECFP6SywMYYrbR6IhIyIzUghjnEWVVNCNjzPhmwZZlGtrDBjMdZJFOMwYOPDb3DH7S705049FjFxSEPR2V0UIctrzDCbH5WpQaLxjuw7Z9MtGUq2ul2/92ysCw61/OUR8AjYQcATRju4G79rf/+AFZdQNlBdrpW7kiNXBZsiJCuXVWM0QWpFJ55t/rZZtA6L9pmVz+rqKHvftHpM8AiW0CwiNuVOHBlOEFnBZhCiE/g7NqjYyOf90q2uapooRucj6o6LOXOdeMnGdbq+FnURKjbHEOSC5REpWGzMMw5b4cGkc33BA6gSpzz+8gh4BKwg4AmjFdjt3PSNtzutnTSrcMlhqIWtHPg7CCKIYlZFOZWnwKpm2EWFWdGxuaKoyizQqklPORNHlhMQ+zRsSNs7e8uCLIbXcFhEBulism64bRPFJKujy3G4wAzuzbD4Q6laJ/EQfX+pKG/CewXvIXjX2BDL0R3O4VNqqFiFvg2PQDYEPGHMhl+uattMrSGiEpcEKjYTsHLUVRfTG/DEWYlMkEpSK3LfUmVdVW+VGR8UVUfX1xglHeHDBd0usuVEHMPxjOwwxkUBGZl1WKpOljl0kSimWR0hhgbPDJsXcwsvF8t1HJamU4NExXIgRqbLNRnvhb0a64fkmFS9nmqqKmivpnrVzfr2PAIeAQEEPGEUACvvReEyAqJl45K1lDGrEIgiPng6k467GC/oSkoSVWsm7EKlUxiHR8RG1Zii7WQhHbr6xNsungEcnMBqn6R4ypRkYckoxzycwIq5utdUV6bmPGRrDdYdqGDajCXjnWeUs71OmaAN3ul5EPUSwTZa1pbSK55VxMDDugwPgaILvlqxHBM5GH1KjSyrz9f1CKhBwBNGNTjmohV8lNs7xGS9VQ1M5BQSHyBsRsPiNbJxiSL9dzVe0NZmQwQ70bK6FFVlRGxE+85b3vaGnLef4VQiojGd7JmB9ZblNOW9bx7KlYpzDBNFvFvzGteJ9y0O5JBPFTFwuq2O5RqnmLSeRb59Op8JXWI5silDRMY6tqEmOMjyl0fAI2APAU8Y7WFv/M62U2uUIj7YRGDTArdFXDu6iiehJmNZZK2guifStDuT7vGE22eKqvg32Zx0YVdAUcJjYqyuEscwblndAV0do8r5ZWPsHyAa6B8IDrTyTBSj2IQPDjBG1TlV2XqrqKygth3Z8k+qnFfdbbkYVhA+COkfGKDu3n7pgwITORh9Sg3dq9S37xFIR8ATxnSMyqZEd29fIChg64oqqekSr5EdnysnwdH+u6o2KotzXD22GUcOOQir8MRV6RKxUTmucFuukCqVRDFprZpKWaFrruLaDVsUu3r6A8VY3akETI4vulZxgAcl4SxkgrUJ6xAIdtaDCVt4ZLmvivj9LPdPqxuNd8TahqWZ5x2MtnUpoIf77VNqpM2i/90joB8BTxj1Y+zMHWyn1mBpK7CZHFVfrU28JgvgLrt/wvoKt7HWHfmJkxKdC0aqkjapJkVsRPvOWz5MHGWtqrz3ipKA0aOqA+uYasGoaH/CKTlUW6pkxp6lTpLr6UgQAQoryMLtWDT+bSQI2qStLRMum2l94P09OISrr6La6irq6+8nxJn39pXO46krZUi4zz6lBu8M+nIeAX0IeMKoD1snW7aVWoOlVoCIBCydrp40w/1zc2sX9+mq6UkOx/6ZJBumx1kUX6mhHV29gXtydNOOjSvvCbjpvvPeL6xEmiQww9tWqXLg3gnJAAAgAElEQVQ8QjYq7hPXRtj1Dc+8iOVCV5942w2nekhzPWUKzjKkirc/tssxSxQsq4gpLzWXzA0TaUp0rm3bmPDc30X17bR+h92TIZqDZzfpsEB3yAT6ss/uo9K67H/3CHgENCPgCaNmgF1r3mRqDWZlqK+tHIxFZOqLruHC+gMrKCx4WXM66h5fmiVO9/1NtI+Nwp7j6gKyiFjWcrWs6iKOzLpT3NybjQeOro88WeMYUZRxoXTF7Vjn8xlWOoYLeZhIjDRBGx6cTbhs8vRDtkxULAdpdvBOYWrAunMw+pQasjPn63kE1CLgCaNaPJ1vTXdqDeYyCJVTfGgQD8HUExHLUV9XFYibuHrBvSZPLnTMTRVxf8C6HK6oiA3cU4P8mxAZ6SjkJm2B6FyoII7skAaxZ65a8RmRVREbJ4pxqfJZiGKeCXIWDMMEGdbVvKUWyTJ23rpNY2qoCxa63vy/n1m6GYRGwGUVzzD+/lZLFy8cwuV8Sg1hyHwFj4AWBDxh1AKru43qSK0Rdl/BB4VZNKL5yFxVIQ3PVh5Pg8NuqnmwjiY9HUzcBzGucWQnTCTL2R1XhjhG807mIcUDm2/EVNp0W1RJFOOIIzbUQYqgPsSOFpz3XhD9erEDAFgbcbCDMcLq6LqXhug4ZctD7G3b9p6yw4OJjjXUVwdhJqJiObx4+pQavEj5ch4BvQh4wqgXX+dax0YSHy8VV2AxRP6u+mrq6CpuEkqdomJjtse4Oq2nkVnHlcd4EzZm5FNrHF1DIkqjWfHKWl9GxEZGUTVrP23U5yGObNOG/ukWstGFgS03Tp1EMQ4rW+PUOW+wnuGbAjdFFlNcbuPMip/uGL+s/ctSnwn6dHT1EQS1EO8IkRyVXjo+pUaWGfJ1PQLqEPCEUR2WuWgpa2oNtkENTsx3qi2KCJC4rEKKCcyTol3SgosKxri4MEFu4bbMctmJrCE2npGQbgRjjSOOzKoDq5VN65zKtRVOk6LT9dg0UYxiFHYb1mWVUTkvcf0PH6wl5crNU9yqTrxc/+ZlGTtyMAYpdDoLQTPReMdSYjm89/UpNXiR8uU8AnoR8IRRL77OtS6TWiMsXoNTZBb0nrRRKDXoaC5G1wDKg9ssD2ZhYQqdm2+evoTLhImOKosY2gT57Ozpo+07Ny6i/cpDeazN3cfWBl3tLvSXbfJzFicFRWUcJKhyr7VNFKNrLG+EKuz2jFh4kff/SLU6uprbV9X7DhZmxDHGPaPhb1BVJZRWC0E5kXWDfr6jqY6qqypVddm34xHwCEgi4AmjJHB5rsaTWqOUeE2WsbNcjNH4xixtqqzL3Dq3tqlx21XZN5m2MI/4qNt0U42K2MCqIrppSBt7OH0DDjRUkYy0+5r4PUp0YFUc21AdxMSVi3UxDsfwnOIwAOJZMqlU0A6zZrsqBOQ6oVKVTxHv1yCMoa46IBCyc2riuVNxD5ZeZHNrt4rmnGuDNwcj1je8SfAcwmWV17LuU2o4N+W+QyMYAU8YR+Dkb27pot6+gWEj5xWvyQKZ64pxwGDvpnp6c5s+1bcs+MnWZXkwi5u0PtlmhOohxnXUTpclUxt1RjJgnVIZRyM0cEWFkxLGs+Z5YhwVdcVqM1kscaqIjikAwrkOg5hwy/lGw6lZmNuhCizCrotozyUvCBXjY22wd+C29vI4gIxiIxOfydY41E9BHpnbatxhEN6Be+9Wr3JKfFseAY+AJAKeMEoCl+dq0dQaLHYIJ79wdeuEgI0mCfA8iMqUa8yJCTIlI2Kj41kKWzXzthkVjeUbKcQR6wQEBu8pJIQvZZ3KG1GMPgNZSLKK54l5JpiwYjMCgVQwrqVayYIlvnVYh/BWUe1RkaVfKusiB6Ps4SrWOERy4C0Bl9WeQh9BPCfsfYRnnbnhq+y3b8sj4BEQR8ATRnHMcl8DqRcgfsPctJh4DdJh6P6w5UFUxvU4y6wLMLwZbO3olXLzi/ZBhYhN1nHF1c8TmcoqZJOnsWad6/BYw7GweSeKcbgwkoz0I6rifpPwZwctFZUVxmNkmdURrosmxpp1DZbCEKEXcItXaZXV1V/ZdlWqnieJ5cBTBMrf/vIIeATsI+AJo/05sNKDAqSvu4ouT7pJYniAeRCVwcceuJhy3bSyAHaqb+JjnEUshgnOwOKjezObBSeXFVWzEsUoLiOROAKDyoqKQJCrnOJX496d+DcdVnNYxGDRcQHDsGtuMa+vXPxqlneGaN1wrGw554lluOiK9w+L5YAw4rn2l0fAI2AfAU8Y7c+B8R7A5WOLpSD8PIgA4Ps0dlQNwUWq3D/8YWERWJ55xIjC7p4BSTRgmVb1kIQVVW0KbkSFbHRgOBKIIyPbENGoqaqgqqoKLWRK1fpT0Y5qd1WXrbJh8gDhLhzk8byjVOAs0obLGIqMQ6SsCW+hPcfVBWI5/vIIeATsI+AJo/054OrB629sph+sfIB+/cIGGjemgRb95xm033sncNWNFrJJGNGXvMQI2hCKkZpQBZVAYMbtdP1p29Eba3WGgAOSM+MyJWKjYGjDmrCpqJomZKNjvOVIHJM26OE4XZUpOXTMS9Y2wy6ciDWEFa4QI2aWdB9YiBAfBrKNwxOTniYyYw8ryfKqbMrcR6QOe55Rp5wVi+MwMaFH4FNqiKxGX9YjoBcBTxj14quk9Zf/solmX/BtOmfOTPr3Iz5Iq+55jH759PP0izu+J93+37d2StfNWhHKaptbu5TEzmXtS1r9kWRtBBaMJLM0BnAHwgkvFO1MCGCkzYfK302IALH+shhPWMCg3qpLVKoUPuVAHHktOaqtcCrXnY62RNJy5J3khOcWhwKiRFkV/rxrUdX9XGunVA5GVX3F4bK/PAIeATcQ8ITRjXko2Yurl/+UXn9zC1131flBOfz9qJMupj+tWyHd+6TUGtINClR0PRdj3FBGkrUR499tTC3V7XQFgjBOucaFYaw6FVVVxycKPGaJRfNIHMPpHRBjx5uPcaQRR6zl0fXVwbMLL4Bw7B9zgwaWcLV30bVTdH2HiTIOYqDyzbs2RO/FyuedcMuOO1oPORh1pi7yKTVUzZRvxyOgBgFPGNXgqKyV4067fNCSyBpds/Zpun7FGvrWpafTu965Jz3+9PMEq+OiS0+Xvu+Wtu4g9szGxZvs10bfSt1zJFgboyI2sCzCKlbusZyYdybi0D9AmRUigSNctvCMueqqlgfiGCaKIEBZ3CbDKTlwAJKlLdfeTdH+RIkyxopnOc+u5GnvZhDlhrrqgCTrik8eXV8V3IM33tv1dZKlfzI5GEXu51NqiKDly3oE9CPgCaN+jLnu0La9g26/57GAGDZPP2IIGcRvP1ixhtY8sj5oq31H0Z30I5P3o0WXnEbv3mcvrnuEC+GDh4+qjctE7IPOcbGNdrkoqaaJ2LisMKpjntn8iuaEA471tZWB0mQx6br+NDUqxu8icVRJFKMYJaXkUIGla20Ax8aGmoAc9w8MlL0gEPAPx1qrUpMtppAo/1QZIutXtxYBDgB8Sg2RGfFlPQJ6EfCEUS++3K1D1OY3L/0PDQwM0GXf+RE9+9APAnEbdoE0wvp474++Gfx78P9P/wZ9FKRRwtIIsgjSaOPCJgYJe9s67Nxf1ZjHjCq6fgFHEbEJVffP2g7blKMdHssDO11v7+wNyFC5XyB/UMtl8ZxJrm6McEMC3oWUBLLz4gJx1EkUk4gj/l0VsZDFXnW9OLfJPKaqyIILPAZweJPV6ogDTqzLrW09ZW2VFsFaZQ7GpPuCLII0+ssj4BFwAwFPGN2YhyG9+ORJF9M5s5sDSyO74JaKPyuWXjr4b7A6/vrFl4f8G+9wunv7gg+gjSsPuRh5cWFujLBGbe+0Y7Hl7SvK4UOfRcRmJLjlRvHEwQA2nTu6YJXvG/w5apktlzhPG8TRJFGMI47M9TrvxDF8ePF2ezzBGWlxneGk8CKHA3i3I5Yb3gJwK/fXLgSAzdiGGtrWrm8PAQVfEH5/eQQ8Am4g4AmjG/MwpBfzr74lELYJk0PELZ532ffp3luuDNJpwCJ5/uXXBaTy1OOPEh6FzdQa7EO82VIuSGGwOCq4HtsCEoBNMcgiNj9ZyQ0jFciNBoujbqEJjinQWiSaioOpxgZ5KAvlaW01QRxtEsXoggnPcVQwRuviUtQ4LGF4vnm8BdgtGf6I29UpYKJoiJmbYVZWEJGkWEdGuisqKzLHMmfusKMNmMjB6FNqODr5vlsjFgFPGB2c+g1/3kjHn7GAHlv93SHxiefNX0aPP/MC7ffP4wOX1JmfmkJfmd0sPQKbqTXeuVs9vbmtS7rvLlbERgNS466QKGyAsTFi4is6yA2I8uj6moA0ZiWhLs5puE9MyAbxYEg3MlKEL3QQR4Yl1kxWMRvV6yZvFrgw6Za1hEXVRm2kfVE9j6XaC+ewRDlGlkd6qgzeOTChQ+BTavDOhi/nETCDgCeMZnAWvgvcUr94/FE0Y/oR1N6+Y5A4gky2b++gjx6yv3Cb0Qr/2NZlLSYjT7kYRYG2bW1ME7ERHU9a+bCbat5d+qJjDbvwQvGUkRt2OIDyI0FBFuNUQRzzoB7L1kDY4pgWx5r2jOj4HWsQbnu9BXVKvHkjyypwZesah0DAFArieYxJV4EFbxu6czD6lBq8M+HLeQTMIeAJozmshe4Et9Rfrv8djR07OiCOMm6naTe0mVojj7kY0/AM/27D2igqYiMyHp6yLJ7TFQsrT5+TyvDGJ44019wwcRSZ5zwRxbg1wVJy9PUNBOrSNlNymMgDGI77wzwjjq9cXa/DVkVgO6q2ihCTXs5jzvJuRF18v3WKvfmUGllnyNf3CKhHwBNG9ZhmbhHWRaiffuKID9K/H/HBzO0lNWAztUZeczGKToZua2M4lQM2sy7k/GPqosUYoV0iMaLY2Sgvq3gK4ghVPxctUbpw5Em3kneiGMUu7Lpp2poOEjemvqjYqSIOmXdd2Bwzbx9lypU61AuPGYrQeJeVe5y2CIa6czAiRrxpTK1Il3xZj4BHQDMCnjBqBlimecQnhlNqyLTBU8dmag3EQARCC5ZyQfLgo6qMDmujahEbVWNl7TDXNqQdMb2xlhmLqtx8LKYzqqgq06e81IkjjuVGFG0TRxdi6+BBALVgPNN5PxjhTZURdtEt5lYtX0uryPtGdw5Gn1JDZDZ8WY+AGQQ8YTSDs5N3wccP0us2LmyAcFoOt9iRcnILy9u4hlpq6+iRymNoQsRG9VpgZBnWz9YO99RUdRCbcOzbSBHGwboBcSxaBQaot29gRChMhhU1O7sKpFospohpTSAo5Yo4UDTOEX2z6aIr8s4q5g+sDfAUFQiKCgN1F/pHzLcrjLGJHIxIZ4J3s788Ah4BdxDwhNGduTDeE5upNTBYRhpH0qYamy3matOyvYdrwxF1k4T4Sl42aGxRM5dNF9xUs+ai5H1Qy1kMKIpBmHjjIGpUfXUgxgIPgpFwIKQ6JYeJOEXedVyqXF7cVcPuvMg/nOX9GSXMWO8jSSSHeRTozMG4Z2NdcADlL4+AR8AdBDxhdGcujPekv3/AemqLsLtmW0evcQxs3ZCHQNkWsVGNjW031aiQDTZ6JshMWFFVp1CE6vniaa+UhZYnxpHnHnkqk1VllK1R5FOE90deiAhzkUfuwqKasDsHBfU1lUGSedWHVZjruupKGj2qOliieXC9V/EsmcjBiLRblZUVKrrr2/AIeAQUIeAJoyIg89rMG293Gtk0p+EzrqGGaqorRkyKAuARtkCx1AyBSl9dVRAn5IqITdrcif7OCBRiWNt29GY67ee5d3gTblIsJNq3cJyki+65PFiyMiKuvCOVOCLeD+IdvPF+LsQpiqyBuLJZCXPW+4frm7TSYo1D2RN/isTUHcKsGlO49OJwF2JAOi6fUkMHqr5Nj0B2BDxhzI5hrluwmVojbkONYPftXYWyTwIfHjuL/ert66eaqgqjCog2F69uZVFX3eV0j1vnnLKYOliRRBV5RyJxxFzAwgUrFA6A8G6LWg2Zaz4s3qJxdTrnOkvbLN4ahDkQN+ssGE3LYYt8h9ORAL9ysjoWBb2qKatLb9q6wjdwr6b6tGL+d4+AR8AwAp4wGgbctdvB7QkbFVcuFuNXtK65J5KiEqeoiA02ViPRyopNCHKfqYplFbF+qZxP0baYomoeLBJh66goUYw7GAKBGkkxjsAgeoCBODoI2pSrJwGb9/C4IdwDwRldl0mrYtoYysXqGMbUhGeET6mRtrL87x4BOwh4wmgHd2fuis1fu4Oxgyx/4f/f3rnFSnbVd3qdS9XpPjfaxiiAFfwQW2lrHsYwg5UojjQKwjAKEh3hKIkzJB0BD/GFgEjkBpNEBAhtAYKATR5sRCdWDChGaaREgbZAI8UokZ0Y8zCiEeQBIgdmsN3d59anq85l9Nvl1d5drlO1L2uvvdaqb0kocZ+91+Vbq6r2b/9v5zbiieMpuqnjktgUiW0sOk5M14nJ6lLHKGzFuueWmX/eohHTA3g+WUqIlnWXQhHhOCCgFxrKAqmm77cmBVSZz1DT1zbtrmp/M/R75jpbbR02MVsd9b189UrXefznOJ6KN1XZExoEIBAWAQRjWPvhfTZtltaYtFjV/dKPleJBYisAP2ptRZPY5GMbU0uSMmnPrUC51C+WYXM4kU2MGWTFpO2EQKPE3MriwI2yrkWxyJ5Pi8VRD8KKc9PLAZ1VWdfn5mYyL49pEo6K71SZof7Ofu3ahvlSGeLqI5HVpDN90N+tW7ZejBX9jqs6Vt37itaqrDvO8P2U1HBNlP4g4IYAgtENx2h7udTfzWISQm158ST32ZAfBkYx1MOMHgrlalr24VuCWT+eSpqxcXEn1C1qZF7WWnCQm2ooiWxcLz5vaW0j/qlJi+IkVinHONqXRRKGwy+/mra8TeLe5t/rxhm3JWrqMsvvuc6E/qcyVyE0+x2k36s2MpdTUiOEU8AcIPBSAgjGKT8VIZTWKLIFehu9crjjLM6tyJh1rrFp5pUev25mzuXD81nW1DYERB0Gde/VQ9XLFjuZBca6qVqu+jcl0gjJ9azuevP3+xZuvscbx8p+1otmF3XJ3XVf1kuiSJKgaRaO4jSwOhbLMpq3KsaeKCgvmpV5tM2SJPYlZZvu8ZTUcP0tRH8QcEMAweiGY9S9hFJaYxLE0Gs22oLweus9qEXm7q1xfu2pJwMaPgd6oJJrspKE7OzteynFMeks+vp701a3kITiMFObPTRG4Vgn+YqNeStTksPXeWx6nGHLm8RTPqts3mOjSqxz0/Ov03/bVscQrLVi8KqrD9fByL0QgEBDBBCMDYGNqduQSmsU4WbjgOSiKhHRdht2j2wyjm6Sq2bbLFyPn894KrEoK4QE87TEe1mersWTLAkqYVPWTdr1/hbpz/Xai4xZ9Rp9F0joac6qMVrXAp4X9C5fQFVdn8/7ht1V5VUgtk1nWvW5xoPG8ml1tC8jrRW8zfVTUqNN+owNgfEEEIyckOwN7nNrl4IQX0W3I4RsokWT2BRdU9HrUrc25q0Ig/ievctnMx/TOo0uurYESVWXsTqWr6Lns6nrQheOTdb+qxvr19Se+OjXZpVV+ITE4jR5WAy7Kev7cLiOZ509kPu3vlNCEOHWzXh+brbOkrgXAhBoiACCsSGwsXWrH+PnN3qZK2UsrY2ajfmsnG1bZ1KzNpZJZGMfoJVlcZoeIPXZtA+RnfnZwgXRYxaKw99HoQlHawWX1VsP3k16PUybcMyLcIkliRt5GcRQu9Tl76g+8wvzs0bZhNVcxG+H5KmjWP8jSx2DWHR5augLAm4JIBjd8oy+N2WlVBmLmJqPmo022Yoe0qtad5pgmoK1MZ/Ipuyb7sHDesdsbuvcNlcQvIm9q9tn/uXFQdbWlIRiaMKxTbZ5K3zZz0zdc+fjfvu9NuqlXL7mquYybZ4G+r5UcqCiCYKG98vWVpQADyFhEHUXfXyiGAMC9QkgGOszTK4HPYBc2IyrhIV1Z3FZs7HJJDauD41E89Khjlnb6mUunDE0az3QQ2Gd+KxpdlPVPlurk8J5FTcnC1deTKZey9O3xTFvCVcctUsXwbKf2xQzq9rkK0pqM6nURN7iqu8QiaDYSi+V3XN7vU2OJLfSosLZfufqd7Lt34ksC/ZSN4tLpUEAAuETQDCGv0etzHBndy+rz9ike5XrheWFQ50MekoIsnxo3tiSGE0msXHJwLroqs/zG+EK/nwiG5dF4W0il2l0U7XCUYls9vb3zezMTDQlaFx9BnwIR4kZfS+EZtVLQTjWKZWRwvrrfA6KWB3t2a3z21hnjvl7iVd0RZJ+IOCPAILRH+voRlJc43ll+uvF5eqnN66ri91MNE16Q53flHwSGxcxIm1tuF1/SG6aNnukHrZtyZGmXkbYOn6DOKe4zm7VM5O3KMpyMI0lGSy7JoSj7TMUN76Dzkm+JMel/l4WXtDU56zqWR11n6uSDnmrW13PBZfr89VXfv/14kjuutr/l692s8zSIbigypVW8YqzszO+sDAOBCDggACC0QHE1LvQj8z6Vj+qZRaN7QspiY1LwK6srXXnVCaRTd2x8vdbi8Ph7lzSlraD4hjzFpeQXhy43ONJfbkQjjbeq7+zlz1sxyC+LJcYEuQc6swaxbA1IcRjWP+kM1zn77Z+rYTZ1vaOubDVb91dl3jFOjvKvRBolwCCsV3+0YwuS51Kb8QWH2IT4gzXbLQF0ednZ4JKYuP6QLRVfqROIhuXDOyLg3x8n8v+2+qrSMIbzW1ahPO4fagiHPN8Q3Dhq3POQhROPhMGyVVdmVWrJompw76te+0LQ9Wu1MterV0M+rt7hTMru5y79lvu8poHDQIQiJMAgjHOfWtl1oprPLfeM/3d/VbGrzqoFU0Xe4OU93J/sm6RZVxWq47f9n0+rY2uEtm4ZpY/AxsX48oCnGdRVCgO86t6n+t9aLO/IsJRnxXFL+taWRTlxpdKsy/J5AnYZmbRJutVjturvNV9UN91t1TIQiznYFwsaP7lgVzX5bbf9Etg4hVjOTnMEwLjCSAYOSGlCCiucW2rnyV9iKXpDbNcYVTHSoLx3Ea7mQ3b4taktbGpRDYuWcVsbcu79hbJHnkQt/wDY+yWs6pn4yDh2JaQqbqOqvfZkhwLLyTv8SEaNFefVsVJbEK0uk6ac5G/H+RRM3yvL/Gsupl6QUu8YpHd4xoIhE0AwRj2/gQ7OyVTULr+kJt9MFTwv01ik1qx+7L8XVob9QCoBDNyM1Jm0lgSbFg3VbELXTQ1FQNqH5inNaOs9j4vHJUkSF4HscUplv3856/3mVnUfu+GVMNWLPL1dfUS1Jd4rrNvo+7NSlQsdrI/lT3DTVkdiVd0vcv0B4F2CSAY2+Uf9ehy55SLakiJIIoksbGJLKYpi+bwQdNDwpHlTmYpLuuiOSxiYq19lndTldht2jWrzIe9KaE4PAebUVbu2qExKMOryrV5i1dnftZMIwNxa1I4WndEuT+uX2w/6cpB56RJBlXOZpl7LOO6NYjVz8DKPp+561Z12R3MZ8HIs4cGAQikQwDBmM5etrKSUOIalW3v8KF5UzSJjUtLWyvgHQ26fHjeFM0kOlyfMpX4rjIMHGE/sBtfQnF4AmKgB0W9RCn7AqFpJq77zzNeU9mg/l42RJEYR9dzCa2/fAxyWUvV8FpclcrwyUi/C4MEMYPkLG3GehZZdxOMxUDhG0uH57MpyDvn0s5eoRdqnbkZc9VK18zPzRaZPtdAAAIREUAwRrRZIU9V7ql6w+mz6cFPdf3qJLEZWNq6Zm2rZ/QWfBqbhOBVy12jum2jrAD5+pShP0BV3T+dpVXVBptpx021LaGY55WP8dQ5SPHzUCROUe6TS4dkfVcdz7Asz1XPd9n76sT4jUu6UnYebV7flKumizXZ7wtlf27ScisGEtBFMswqXlGZUGkQgECaBBCMae5rK6vSw5US4jTt2mfjTiQW9RZcsUd13GJtTNs0x3PpwAzHd8aQyMb1QfftphqCUBxmmLe+p/KCwJ5lWcUVRzfpOypmF0WXn4kywtGeG7k5P7cWVqhCHSahnQX7gs9nSIUYDEqTDCyHw98LEooSjDQIQCBdAgjGdPe2lZXt7O5n9RrrCLiDJj4qiY3LRRbNMOdyzND6ssWeNS+5Icllr4m9DG3dw/NpOklHiEJxmEE+OVCswtGuYXd3v3QyEPEITSy09bmZVFfVWm4V97a5HU8G7TI8rWiSu+rO3iCRmu+yTE24oJZhoGvzVseLl3YyV25cUMtS5HoIxEcAwRjfngU/Y5XeeH6jl1n+6rYiSWzqjpG/v8nSEy7n6bovy1nJP2SByRIgdOeyTLi+H4pcr61qf3lLmzjoZUjdFoNQHF6jtTJVFV11mVW5P8/ZhbUL4TjYBZsYRd8NShIkgai6lWp1Yx6r7HNb9+QtrzYDd5NzsS7z+gzKiyeEJmvj1SsLIUyFOUAAAh4IIBg9QJ7WIerENSqJjYLuZ2dmMgHjM8GKTVE+Mztjzm/0Jrqvxby/4wQMrrqDnXVRgiJGoThKOMr1LPRsorLCKOaqie8NhOPgVIjDNasLRi+Y+jt75tm1S0l/Tx70HS/30IGr5lxjMa/2JWYT57nqbxclM6qS4z4IxEsAwRjv3kUxc5VtuLBZTHS5SGLjEkrKNRvLxCalzKHMebHJUDa3leCpmNtdCkJxmFGoSWGsW6Stp1hmb8teO83CMe/mKxEzyCo6yLA7rUmC8uehTkmK4XMYggtqfk7Zy9Sl7uUssmU/N1wPAQjESwDBGO/eRTNzld4Y5xbmOomNSzB6OLp6pZu5XsnlKvZWNZGNfUhUVr7Ura7j9rhoQpgUheLwg6OSXMg1sW3Lh6w8+oxaoegz5nbahKMVMOc3Xuqqni/JoReF0+rKXuZl3EHfNSH+7tjst03FK9578iHz6ldeY95+261mdXkx9p9a5g+B5AggGE+nmP0AACAASURBVJPb0jAXpLjG86p51nvRMmPFix7wfMSB1CGzutgxnXm5qMaXBMZabhVrJPexOrFGiltZXexmqdx9ugnX2bsm7j3ITTV1oTjMsqiAbmIPLGu5jrednCl14VimVIYLwdTEefHdp30RKrfdMm7c+o7VyxiJ7lC+Y2VFPqKyQ6o71FBb29gyDz96xjz8t183R2+4ztx5/Jh5/U1HGxqNbiEAgbIEEIxliXF9LQJyWdJPztzcjIkpiYYWHVvNxnzCoIGbVL3yI3bj9XCs2pVt1SysdQAd3zx46TGo2Tf/Ql1QCfJQHvQcL/fA7nxmVNVYylQp9qGxTlE4VnWLRDgOPi7DZ0LfDQdZwW387fPr4ZQlaSNe8cmnz5qT9z9iFBj7lc9/2NfXGONAAAJjCCAYOR7eCagG2k/OXYwySUIMiWB8WbmmNaNs/gMj1rIGSMCo6UFvWl3x7EuVlcX5xl4GWbfHkKwvo75AUxCOgxdknezlRx13/EklObz/ALU0oM7EIN5z8F2RL1VTxoLra/qak5Jcac6+mwTjB04+ZH7ntlszF1UaBCDQPgEEY/t7MJUzUFzjufWe6TsoVdAGwEHij/lMILgot+BiDfk3+r4eqPMuiTG661blbq1c3c7sZdexfDKQC1v9KF+IVOUxfJ99mVDGFW/c2NZ9XVZyeSn4jFOswyRG4Zj3THD5mY6RRZ29H3dv/rtasbf6Hgmp1mnT8Yrj2Hzu1GnzwKnT5sRdtyMWmzqA9AuBCgQQjBWgTfMtijH460fPmMe+9InaGBTXqJpSEjcxNiXbuGq5+0J2wPbWkE9kowQkbQjYabE2jhKKw2dXMUhyU5VY2kggUVKdz2bdjKpWvGQWmYvxCMVhZrGIJR8W3FhY1Dn3Re9VXKBiHGdmZoLJMqsXoXKNbTJe8SA+ckP9xuNPmc9+5N3m6PWvKYqR6yAAAQ8EEIweIKc0xC/86u+b9c2L5gufusfc/NobnSxNFgPVbIyxWQubYjJ9Zg8dLkESwsN0ytbGIkIxf37tQ7GyiOpsT7Obal4gFE2WlHerHpWRM8bvCs05VLHUhjAvE9sX634fNO9hF1SxUGkSuavu7e+3Zm1sI15RjJ758U/Nu//4s0aJb0596h5z7atekdqWsx4IRE8AwRj9FvpbQBZX8LEHsy/za195jfnoiXc6G1wP1HJRjcXVbHjhvmoV5t3F5Mok62xozPLuiLFb2MoKxeFzkU8G49K9z9kHz2NHRUW0rBt5V1+PU/Q2VEjCUd9dg8Lz7WXlnKaSHPa34tzG6HCGNkILBgJ2wchrxneTWDz+3vuyUhqf+fDdiEXfG8B4EChIAMFYEBSXmSyuQO3G619j7v7gZ8yZL37c6Zd77HGNtnbWpf5e5mrrsvlKZONqztbauNCZNQc9GLkaq4l+6grF4Tm5julrYs2++hTbVaXon7ky8Yd1rVaSFblWKzlW6q1N4WitXCHFhaacWTXvjVKkDIzEm6yOAzG/k8XuNvGZ6Ci0YqVrmqqvOOkzfPe9f5E9RyhmkQYBCIRLAMEY7t4EN7M3/sb7zJ+//11ZbaQ3/uYfZjEGb7jldebYm29xOle58OnHMdbmsmajHqCWFE8yY1q1AFTdi9iEkmuhmOdW1MJWlXVs9+XFwezMTO0aobGtf9TZkEBoUhzYMW2pjJCSduV5pCYc62RBzb9UGJRH2nXm4q54RWVCpUEAAhCYRADBOIkQf88IPPOTZ83xP/iYeezLnzRPfPu75nN/9VUjF1WJxXvuuj1zJ3HZJBhlpWvijarLeR7UlxVKspRUqcmXT2QjV7HYY+CWDw/ic0KNR8sLRbn6Nmnhwk118KmxVnMl/VCTZV4xjrF+5l18rzRtcawjXFysr2wftiSHXJQ3t3czMR3b+bAZtZ9bqx9y4VJISyhKMNIgAAEIFCGAYCxCaYqvURC6xODprz1ulCFV/62m+kjKaKY4RtcWRotb2T6fW7sUXIxe0eNQtmajrdOlt/8SLSEksim61iLXycVKDyn9nf2ghIGNn/IdExqb9bXIHhe5Rud8+dC8EXedcftCRf+tf3dViqPIXEK9xrVwtO6QyuDrQrj45uaah4/5N5lI6EUhXd5dtc2SGT64MwYEINAMAQRjM1yj7/Wbjz+Vlc+QZVElNBSYLqvi/3rbG82NN1yXre/ekw9lfz/16RONrVelN57f6GUCKtY2qWajLf7emZdb3n5Udeaq7ImvBEGT5taWUByel6yvyqYq65riyVJueeajisHnhcHmtlzT2ytXE8I+uBBKVogPXF3j5umCh499taJMnjJNMh92V9UejyurJEutSnm0Fa/ogz1jQAACzRBAMDbDNcpeJQqf/M73suQ2N9901Lz1Tb80tnSGrlfzkQI79rhGWdeuXulmYtA+QMSWyMbloS5rfXU5dihCMb+mfPZbnfU2amm6ZDzclywiR5Y7hS3nxHteSbCKUGrSwtXkWSnSd/58yJVZ36uhZIu28aE+LbnWO0Vu/2rrWzsvCWNoq2RGkf3kGghAIHwCCMbw98jLDGUtfOLps5lQvON33+pFBJZdmGL5Lmz2oothsevM1ync3d3PSgfkXfLK8kjhep/WxhCF4ihhJbfdVOL56oqWvJAe9RCcwmegzBqKCkd71tsslVFmXXWutWs9SCjV6bvMvTb7r77b24zFtXGOSiSl/VeSHIlFKybLrIlrIQABCFx+ht3fjy2EnM1rgoAS2dz82hub6Nppnyq94fPNrcvJW9ewnb1905mbNeflaruTtgtiEX7W2ri3bzImrr+RYhCKw5wGbsyd7MGzStKkItybvMa19Tyf7GPa61lq3w4Sjla07O9JtIRjdWvyrNm+XSaEKTtfeZBctdx9IcNtGG6/OiN6+aTMuzQIQAACdQlgYaxLkPu9E1Bc4/lNxXuF8cM8CUA+46l9iGuyZuOk+YT6dyuS1rZ6TmL58nX99KY9FJe1ovzzFumYrGtNWresKJAV50LEWZSLnoFJ1+WFY393z8zPzmQZfmN8yTBprUX/nheOmxd3zHbD8e9tuKAWYaH6jYpXnFVNJhoEIACBmgQQjDUBcnt7BCS+1rf67U1gzMj5Mg0DF6XRb/tVs1HF7VUPLTZB0wR4PQAfWe5mdSerWpJGCfQm5uqrT/sAHFp22eH1W+4+CsGTUfVF+jbBSn934Lngo46jr7NfZ5x82Ra9MHJdkiMfh60SUCE14hVD2g3mAoE0CCAY09jHqV2FXDpVesO1G2NVoMOueMruOkkI2vIKKWQxrMpt+D6l/19dVJKg4pkyUxOKw0ysBbYME1f7Ma4f++A87sVIE/MYdsvcuLjTxDBB9zls3Soa4xj0ohxPrgkm+n5SDcPQYkT1WZQbqqyLNAhAAAIuCSAYXdKkr1YIKK7x3HrP6A17Wy1fYLpKIhs91CiLauhWJJ988y6Z46yNqQvFPPOQ3FTzL0e0P23F4+YzZk6LO6bNOivX00nlSbA4Dj5BroRjqC6ovuorqhbz+saWufaV1/j8OWAsCECgZQIIxpY3gOHdEFBco9yC9MbXZ3Odoc9mDT230UuutELVfTnIAjtNQnGYXduxfHpolhUjJIE2DRlV826WRdzYXYmkqp/dEO8TEyWC0XetPEB0houUsbFx54qdHyXS21yrrJ36TDYdr3jy/kfMw4+eMa/+mZdnmdR/57Zbza/c8ro2l87YEICAJwIIRk+gGcYPAdXjUh27pluTYmVUzcam1xN6/3nLmmLk7MPetGWCHN6nwTnslHLdrbPX+URCoT0023W1mS2zDttJ99qXUxIsZYvBIxxH0z3UmTVLhwdZRMcllmoykdOkfZ/0d1/xit/9/g/Nbe/6U3Pq0yfM6286ap58+qw5/p6T5swXPx5kGa5J3Pg7BCBQjgCCsRwvro6AgFzj5KI6KXaw7FJsIhtZVvo7e42mrS/qjll2DTFfr4e2ly12siXIkhxaoom22L4oBuayREFNuIbalxiyyMQi0vNW2FjmPOoM1a1lme8T4Tj6UzruJYO1phex6Pr8Dhi4oC4YfTZ9tGd+/FNz62/9kXn0wQ+ZG2+4Lhvybe/4Y/OGX/5v5o7jx3xMgTEgAIEWCSAYW4TP0M0RcBnXWCWRjauVWQvSNNdsHLbm7u3vZ1Y1ZZfFdffFk5avZ7m22XfywiTv5lk1a62rz0LVfmLOqCpLul5QuU6ugnCcLBytJ8NBcaJVz6OL+zqq+7jSNfNzsy66K9TH6a89bk5+9m/MysqSOfWpe8w3v/VtIxdVa3Es1AkXQQAC0RJAMEa7dUy8CAG5p8pNtUqrm8imypij7gk5fburNY7qZ5Lbr038oYdp7XEomXKbZFKkb2VwlKC+mLkuVuNirenagypJnIrM0/c1y4fns9i1GJLA2Hg5H54Min+LhYuvM2MT2xgzE9x50X4pE6rPJtfTZ37yrPnoPe/IhKLiGOWWeufxY9n/pUEAAukTQDCmv8dTv0I9NMt9saigyCeycf1mv85mTEvNxklCMc/QhztmnT1r69585lC9NCnjplonVq6t9RYdN4aMqlasNOVePIoVFscBleFQAHkzhCSoJRQ1H59NQvHW3/zDKyyJ9558KJvCR0+80+dUGAsCEGiRAIKxRfgM7Y+AsuCpXuO4uMa8UCmaOc/fCgYjpVyzsYxQHOauOJ6rlrvmUhZjV/zlgO/98z2etU5r3EkupXX4+15X3fEkDBQPOzc3MzbZSd1xytxvyyK06QI5zcJxHP+2ufgqmTHqvI6KXfzm40+Zuz/4GfN//vepMkecayEAgYgJIBgj3jymXo6ASm88v9HLUqnbph9iW4Q5loQeeng5stw1+3v75kIJy2k5Wv6udilU5HZ4uDuXZcotY1Xzt9p2RrIvGka5qbpMqtLO6qqPqhcN1r1vXJbM6iNMvtNatfQ99Nya+2Rdk2fw0ivaFkhV5lznnqLljIZLcsgDpenvmW5n1hxZ6niNVxxmqVhFZUU9cdftZnnpsPngfZ83K8uLmdWRBgEITAcBBON07DOrzBGQmFBqerl+6cdYb/T1w+86q2rT0O1DTqziyKVQzLPOx3xibXyRTN4dU1z6O0oeNPgMKEnOdu5FStNnN7T+bZbMvX2TsfD1XRB6mZLUhaO1NOs8ls2k66N8i6+SGUU+j4pb/MbjT5mz3//hIDPq776VchpFwHENBBIhgGBMZCNZRnkCFzZ7peuZlR+l2TtirNnYlFAcJh27oG7q5Fj3ttmZmSwpTqj1FJta/7h+fSVSii37bIrC0ZULcBPCMROyS12zuDDXxseAMSEAAQi8hACCkUMxtQRUeiMUF7A6mxBLzUZfQhFr48GnKW/RUgbO1aVOZl2vmk21zrkN+V69bFg6JDY7ztmEXAR+0p6kIhxtYiGX3/9WOOpFjGLg5blSpbUZr1hlvtwDAQhMBwEE43TsM6s8gIDiGs+/4KIaOyTFQK0uds3aVs+ohlgorQ2hOMraKAEQGhtfezSuTIMtNyE31aoPub7W4XOcvDja3FZ5nmoCwM45pVjRWIWjjz3QGMpkOqifWe6Fg+5RvOLs7IzPo85YEIAABCYSQDBORMQFIRF44tvfNf/6ne9lAfdvv+1WZ1OTW976Vt9Zf211FFL8XghCMb8PTRS2b2ufi45rH5AVp/j8es8oW/CoFmLW0KJrbPq6fFKaqqUuZNGSGKhjeWp6nVX6j0k4WsudrOl1xX8RVmXZhBSvWGR9XAMBCEwXAQTjdO13tKtVau977/t8Vjz45puOmm/8079lgfcu60Ap251KbxSt1xgyzDZrNto4sFCzzg6EbMe4sBqFegb0sLp8aN5orXoZUtRyaLOpUp7kpTubL1FSNKOqFSmy+Euo+Eqm4/tclhVHvufXhAtq0TXk2SjZ2vA50BlRpl69UKBBAAIQCJUAgjHUnWFeVxBQzacbr3+NueP4sezfZWn8vffeZ8588eNOM7UprvHces/0D7DExLQtvms22hie3d390hkHfXO1pUnk+TWpPqHvudUdTyJRYlEPp1UT2tgYvpRFdVXO+SQn485OmyKl6trq3heacJQYU5zu4Dup3fqs+ZIc+n3ZvDh4gfDy1W6rJTPq7jn3QwAC00EAwTgd+xz9Ktc2tszq8uLldei/f/Etd5hHH/yQufGG65yuT3GNa1v9LBlI7M0KI63j/EavEetpTEJxeD99i+omz5Nry24+mVJRi1qT6wutb8tb1sO8GLH/LqtuVcEe2lrLzicE4RjyZ1tzu3q1a5QghwYBCEAgBgIIxhh2iTm+hICKCB9/z0nzz3//uSuEpEtUch1SjcMUWhMlJvKWFnE6KD4udH6xZJk9iGPTJRrsPqtuY9tWmhDPUj6j6vzsTFbX0mX2zRDXXHRObQnH0K27xCsWPUFcBwEIhEIAwRjKTjCPUgQeOHXaSDSe+vSJUveVvVhxjXJRTSH2KOS6Y2X3pYnrQ7ZIjFrvi9kYZ0vFKVZlh5vqweTERnGxahLVPpKqVN3HNu7zJRzzSb/kJRJaG3wHLxjVz6VBAAIQiIkAgjGm3WKulwn8wq/+vvnsR//AvP6mo41TSSmusY41rYkC1Y1vXskB8nxCtpraWn6DJBr+XKctn4XObGZ91wuVaW7DZRr29vcz4agSN1UzqqbM0wrHww1kjBVzlbNQKEHRJE8+WXfmZsxVK8Qr+mTOWBCAgDsCCEZ3LOmpAQJKbvPwVx4zn/3Iuy/3Lsvi3ff+hfmXf/jLLPnNV7/+rSx7atPWRj0gy001hVamZuM0CMXhPbVxaHr43LgYzp6HUqpEFhJldtzbN2Zts5+EBb7s59qK9lECpUpG1bLjx3y9a+EYuguqhKw+LzQIQAACsRJAMMa6c4nP+/TXHjdyO732ldeYO373rebm1954ecWKXVzf2DLK4LKysmSOvfmW7H8+mgSjXJ1SKL0xqWbjNArF/BkKyZpmsz3u74WVgdaWKClboNzHZ7WpMbQXV690TX9HyW7Gl8pIJc63KZZ1haMrN/um1qd+JRQlGH00vUBVO3rDdY3F9vtYB2NAAALhEUAwhrcnUzsj1Vp88jvfy4Siai1KKF77qle8hMfb3vHH2Q/iW9/0S1cISV/glNxF9RpTiGsUs0Fs2vzlwu75JCpkxzSmzdqEdi+USEWWvO1+eC6gL8anzSXvhmktWWVqW+ozZs+QROaFRF44ufy+tS9n5PlQlO04C6/LuVXty4rZ+bnZql0Uvk9Zw9/9wc+Ys9//YfaSVR43f/7+d5lfueV1hfvgQghAAALjCCAYOR/BEJCb6erK0oFCMZiJGmNUeuP5jZ5RcfoUmn2g3dnbN4q1If7qpbu6fHjeLC74E0USJyrmvbG9E2RM1jChvBtmarUt85Ys7UdVD4NptMiW+X7MvyAZJxxXFztGcbTPB5qQTC94jix1vNVX1EvWh//26+YrD/1Z9pL17A9+ZI7/wccu/3eZPeBaCEAAAqMIIBg5FxCoQSCFuMb8Q5oKSqs1VbOxBuogbrWxe02WmLBxikrcofi42CzZ9uXDxSwhT3VxFcKG5y1frkpl+MoYGgK/qnM4SDjG4ILaRsmMN/7G+8yx//nL5s7jxy4j/y//47j5wqfuacULp+q+cx8EIBAuAQRjuHvDzCIhoIf6C5u9ylaHtpZ50ENZEzUb21pjU+M2wUhiVLFxslpPio1ral2u+s3HpsWaTTUv3LUfrlvd+D3X8wmxv/x31HZvL7MqhnqetJ8vW+pmXgi+m+L6j17/GnPirtuzoeWi+otvucM8+uCHzI03XOd7OowHAQgkSADBmOCmsiT/BFR6w5UFounZF3H7sok9LvX3siQ/tJcSmJQ0qCiz/H7EcobKrO3I8iA7ZCxuqvkYXh9zJmZ4/GnKhNhix3Q7EmKDpE+hlc3wGa84ipZ1QZWVUfH/Tzx91pz+x3/KMonTIAABCLgggGB0QZE+IPBCXON5JSbp+auLVwZ8EaGY769OzcYy84r9WlvQfm2rZ2QFKdq0H7JGyJIV4kNw0XUUuS5fpiRkN9U2E6lMe1biUedo2AW17HdYkbNZ9xrFGStecXZ2pm5Xte6XVfHhR89k8YvffPwpc8fxY1e4qNbqnJshAIGpJ4BgnPojAADXBPTwvx6QVa7uQ5at2bh+sR/cm33Xe1e1P2ttVF3CIvGfEibLh+azlwtNuDtWXUeT9+Vj90I7S/YzovW37Q5shePublglVJo8G6P6Hs7enL+m7neaq7W0Ea+Yn7tE4r8+ffaKbKh3K1vqD36UJbxZXV50tVT6gQAEppwAgnHKDwDLb4ZAb0cuqpdajWt0+VDlyv2yGdrh9GqtjZvbfbO5/VJL86HOrFld6iQRp1iVuq0pKYOM4tFUpqbNZuNRQ8tGa18qpJA8qMz+lhHvLr/jys5R9RVlXWyzqRTVvfd9PpvCyvJiJhTVTn3qnpElqdqcK2NDAAJxE0Awxr1/zD5gAoprPLfeMzbzqK+pNvkQNe6tv6/1hT5OXhDZGDi7JzOzM1k9xdgynzbB3Lqpyo1XFseqpSqqzs26O4acZGjaMqpWzYLa5Hfe8PlqO15x1Hl/8umzWe3FV//My8mKWvULgfsgAIGxBBCMHBAINEhA9RqVNEaZVJtuvh6a7IO+YtFGWdGaXmcs/VtX3v7uXlbbMvU4xar7MqhvOW8OsspW7XfcfapxKQteLPVGpyGjqt2TOomfmv4OXDo0bzTPtuMVm/hM0CcEIACBcQQQjJwPCHggIHEl97smWtMPSaPmbDMXzs3NZMWzfVuHmuDouk9ZY+Wyplg0cfKRcdP1Gnz1lz9P61s7Ri7dTTT7skNZNmOMHbWf9c58uOUlyu5b3gX1wpYbS3MT34ltxyuW5cr1EIAABFwSQDC6pElfEBhDQA/BclF15Y7YxENR2Q1soh5h2TmEdr2t35d3dbTF7LcuYZUdt1824Ut/Rwlf3IgHjZda6ZJUMqra2qNNeSu4+I4cuKAuGM2VBgEIQGBaCSAYp3XnWXcrBFzENbp4CHK5eM1HBeenvWaj5dDfUUzezkteDOTLlISQ7MXlGXDd16TkQWXGSzkjrRWOys4bW2ysCxfUoueg6nemXMmvWuma+bnZokNxHQQgAIEkCSAYk9xWFhU6AQkGvVUv06o+9JQZo+q1VgwtdGYzF1VXVtSq8/F5X35fisTE5WsSblwsdwZ8rqvtsfJnSp+Xsm6q05RoyFq120ogVOastJlxucx3qOIVlQmVBgEIQAACxiAYOQUQaImABKMS4kyK/yvzkNPSUi4POxBDXa8JTNpaswSNainqYb1sQpu6YqitNbcxbpW6hNqTxYW5LNmU4hWnocWQUTUU1+xJ36kSihKMNAhAAAIQGBBAMHISINAiAdWgU73GURa5SQ81LU577NBtWhB8MbEWHYkR1e+bJPoPmlfbpSV88XIxjnVTVRzoQZZZe/amueh9Xjj6zDw7aY99uqBOmov9+/B3rOKOX76KC2pRflwHAQhMDwEE4/TsNSsNlIBKbzy/0cuKuavFKhSH8aZYs9EKPJe1+158wI+nzENbHyVrmVXJkmH3XytIylp721pL0+PazLPdzktZNT12vv8YYpw1x2tWF7JsxjQIQAACEHgpAQQjpwICgRBQVsi5mRmjB7xUHnqbzoLoa+vy5QyaitEUq6uWB8mDXGYI9cXI5zhiZePLVIbjyHLHxBC/55ORHWuYVdlY0DpzjsU1mJIZdXaZeyEAgWkggGCchl1mjdEQUJH3Zy9cquziGOJC8zX2YqtFKKGoWCZZtHyJeBWyP9ydy+p2+ny4D/HsjJuTzpWy8y505syW6pwWiAeObY0u55svxeHjcxiiC+owz+y7aambxbvSIAABCEDgYAIIRk4HBAIjoNIbz62ll2nUxqCdl/ttQ4XZXW6ltY5Y91OXfU/qaxriQCcxGPf34RhSiXo99BfJUltn3BTu1cuP1cXmLLKDuoXdLNmQXrKE2uw8KZkR6g4xLwhAICQCCMaQdoO5QOAFAoprPL/ZN9u9tDI8xhDPZMWIyzjFqgdbIntxYT5zUZXL5bS3fHzv8EsVK7LFyIcFLfa9yCcRUsbmqomb8hxszcvQz+uh7pw5stQxs7PELMZ+jpk/BCDghwCC0Q9nRoFAJQJ6Q7++1a90b8g3ycIRWs1GCY7VF+quhVQE3QohFWeXddbFg33IZ+OguVkxoiypm9sHv0jJ17l0JYRi5FVkzsOlOOrUBQ3xMz2KQZPximd/8CPz5NNnzbWvvMY88fRZc+Ku24tsA9dAAAIQCJ4AgjH4LWKC005A7psqvZGaUIilJlso589ahEIqleCDjbUqaiy9QBlVgmZ4HlYIKRY0dGuXD4aTxshnn1Vt2DLW7JhcUJUoSdbFJtsDp06bz506bV5/01Fz6tMnmhyKviEAAQh4I4Bg9IaagSBQnYDiGs+t90x/d796JwHema+b10bSEiXm0AOkainGUOB92twurUtu1f3J81ISIdU9pR1MIM9L2WcnxRrb/Qk9QZPPeEVZGI+/52QmFiUaaRCAAARSIIBgTGEXWYM3AmsbW+abjz+VuR294ZbXmV+55XXexlZco97+b11KK65RAG3NRl9JS2ycoiwpclssYrXyttEFBkrd2mgf8F3FkVo3VUpvFDhcxph8RtVRwjGmzMdKiKQXQ77iFSUW1Yati/rd+OtHz2R/u/P4McRksaPIVRCAQCAEEIyBbATTCJ/AMz/+qTn+3vvMzTcdNa9+5TXm4b/9uvmdX3+TueP4Ma+Tl8DRG/3Umo+ajXYMV0KkzT3QQ/uR5a5R3o6UkrzYcgyKI93uu0v0k4/Xmza33qrn1Art/OclFhdUrbnJeMVRTA+yLp7+2uPm3pMPZTGNim/82P2PmF978y3efzuqngPugwAEIIBg5AxAoCABxabogcC+ObYPAZ/9yLu9Who1XbmKyUU1ge79bgAAIABJREFUNsvYJNQ2lqozP+NUBOWza/qyYk5aq6u/q0zCyuGOmZQMxtV4TfVjxbxcg+WC2lTMrk1uJKFdxO2yqfXG1K+1aPd2djPr4/PrvaDdeweidsHoTPlso6yL8kq59Tfed8XLxSe+/V1z3/2PmK98/sM+p8dYEIAABCoTQDBWRseN00bg5P2PmGd+8qyRQLRNb42VDe+xL33CO45U4xoF0lXNRj04qj6fXFCVMCWGOMUqB6kpoV1lLmXv0R7JbVDC12f9UZt06VJ/L0uM05RALcsjxOvzGYQ7c7MvvJxoTtTXYdCZmzFXrXSNr/qKyoy6vrGVTXlU7KJeNOrlYv43Qv/9wBf+zjz25U/WWSr3QgACEPBGAMHoDTUDxU7AWhT/+e8/Z1aXF7PlyE311t/6I/OFT91jbn7tja0sUe6pclNNreVrNlZ5oM8Xdw+5gLjLfbMi6GJv19QpkeByTuP6CmGPUo8HrbuXwy6o+Yyqob2E0YsHZUL12SQY9TJR3idHf+5nr7AaWuviibt/2xx78y2XpyVhefT611B2w+dGMRYEIFCLAIKxFj5uniYC+vF/2zv/JEtYENqPvwSjEuKkaCUpW9/tUGc2q6eYQpxilc+XfaBXnctzG2G6DloX4bk5t67HVXjpnnwSF9xUX6Ro40lHWX7LZlStujdF75NQlGBsq0kwypqoZsMWlOjmAx970Jz58icvv2Qki2pbO8S4EIBAHQIIxjr0uHfqCKi+1t997XFz6lP3mGtf9Yps/fo3uaW2XXNLJQNUrzG1uEYxLlKz0YqQzgsxVilyKPOBCzUzqKyKchNWtt/QXIRtdtDd3X3TRpmXMvvb5LXWBXV/bzKHSRlVm5yn+vZZMqPIWhS2oMQ2avJKUXK0fKziQVlUi/TNNRCAAATaIoBgbIs840ZJ4HKm1P/68+aj739XtgbFMa4sLwbhXqTSG89v9DLrWmpNVqCrV7pmb19ZQXuXran5hDahuci1vQd598G2k/3ka25qn0IW9NZNVYmEYnDtdXnO7IsGeS1sbhcv4WNf6vR3FBPqZ3+7nVlzZKnjLV6xLGcbsnDmix/PXjDq5eJfS0A+9GeXXziW7ZPrIQABCLRBAMHYBnXGjJqAFY12EYpF+eiJd152OQphcanGNYptvmajsqke6s5ddj8NgX2Ic2g7wYt1bYxJ0Icktn2dqXEuqEXnMIhLtVl7m0uM47tkRtH1D1+XJbg5ddqsr2+alZWlLGmafjNoEIAABGIigGCMabeYazAEFM/4r0+fNctLh1tLdjMJhlz+Lmy+aImbdH1Mf1dc4/LheaNMsT4za8bEaNRcxUzuoL6sjdZdMOZ4UutyKcu2akOGbBmtej6t9be/s+8kY2y+5uWg3Is74ZjFmy51s3McS9PvhTKpWlfVWObNPCEAAQhYAghGzgIEEiaQmqDKuzWqVt/iwrxxXbMx4eOQLU216ZQgxJU4GMVLD/XLh+azcia+xGnT+5Z3U3UpgJqe96T+m6zjaYWjzoJiQuvGrIYWrziJLX+HAAQgkAoBBGMqO8k6IHAAAcU1nt/sm+1e8Xik0GCOi1O0LnBrWz2z3UsvdrOpvZAAkuCW+3Jvxx03m6VW4iC1ciapuam6cEEtcj5tEp352ZnK502u54pXnJ2dKTIk10AAAhCAgEMCCEaHMOkKAiET0MP7+lY/5CmOnFuR+DfXLnXRQao4YcttOJFQle7yoj51N2FrpRUnWVBjc1O1ljq9YFE5Hl+takbVWOIVfXFkHAhAAAK+CSAYfRNnPAi0SECWJJXeiKFeY76ou+IxizyUK7ZRLnbPr4dZf7DFrR87tHW3rGql1V7J7VBW7NSsiuPAWXfOi71dp3F6TZ6TEMqa5IXjOMEtYSv3aVkXaRCAAAQg0B4BBGN77BkZAq0QUFzjufWe6e/utzL+pEFtWv+qiVKK1GycNIdp/Hu+EHtRq5m1KoqXr1IKoe3Niwle5jJrXchu0faFSigWYPtSSMzWL/aveJFFvGJoJ535QAAC00wAwTjNu8/ap5aA4hr1cCvLXSgt79JY10J4UM3GUNYa8jystXFzuz+2Dp+NgVTyobrJTELmUXRuVQR30b7rXmfFV4hxpaMyqiq2Vq7oxCvW3XnuhwAEIOCGAILRDUd6gUCUBJTtUUlP2mx6mF06NJ+5krqu09dUYpc2efkYe5z4SaFURpMMrYV8lNWsyXEP6tu6C8uCF7L10wpH1XDU/0+DAAQgAIFwCCAYw9kLZgKBVggorlEuqkViBF1P0EfsmxKUXL3SzR6WfSb4cM2qjf4k4lcXu8ZaG4skIGpjnqGNmbeaSai1YYG1GV0XOoOY3jY+32X2ZfAiYiEr+0KDAAQgAIGwCCAYw9oPZgOBVgj4jmu0sUtV4xTLQrIPz9RsLEvOZNYeCe7O3GyW1Eb19GJImlR+pe7vyFtq17d2nJYvGTfbkF1QR827Mzdjrlrpmvm5WfebQI8QgAAEIFCbAIKxNkI6gEA6BOSeKjfVppqtx6ZSakUTq7ici7WYtWX1cbkWH33l3YXXNvtG5Q2UEXTjYnNnxMe6fI/h0011EIM6n32+XNbXbIqZ5qpMqDQIQAACEAiXAIIx3L1hZhBohYAEo1w3XVqR8gltXMcploVEzcZixPJlTWypjLyb47kNSpcUI/niVcuH540SukxKKFS2X12vvXnZYsfMzM4YifvQXVA1ZwlFCUYaBCAAAQiETQDBGPb+MDsItEJgZ3c/q9fo4qFTcW/dzsCdcXM7nKys1GwcfbTy4v6g8gvWYqYsu3rB4PLlQisH3uOgeSu7KzfV2FxQKZnh8cAxFAQgAAEHBBCMDiDSBQRSJKDSG89v9IziDKs033GKVeZIzcYrqdmi7kXEvbU2ys03FvfHKmekqXvs2evv7NWKC7WJiOqWomlqncP96uXRkaVO4/GKTz591vz89a8xZ7//Q3P0huvM6vKiryUyDgQgAIHkCCAYk9tSFgQBtwTKxjXGVnZBwufIctcorlIP3dNoLbNuuru7+1lpkzKWZZ/xeW5Pdhi9Fa17OTxbawnWv5fds7ZWrhhYCVwf7eT9j5iHHz1jVpYOmzNf/iSC0Qd0xoAABJIlgGBMdmtZGATcEZDr4YXN8WIq78qoGKrtipZJd7Mu19O01mx0USoDa2O5szZ8tY0/7MzPZnVRJyWrsaViVK7DxpfWm0Gzd2frW+qaxYW5Zgca6v0XfvX3zdt//U3mzuPHvI7LYBCAAARSI4BgTG1HWQ8EGiKg0hujYtokFPUgKHfGthPa1F26tY5OQ83GJizBEjJXLXfNpf6eUSbaabTW1jmDstauLM6bvX1zYOIaK/APii+tM34T97YVr/jAqdPm4b/9OtbFJjaVPiEAgakjgGCcui1nwRCoTkBxjedlPewNktfkM2nKClnGlbH6LJq9M7aC51VoWNHRVOyhsoEe7s4VspZVmX/q91g31a1LO5eTCuXdhmOphXmoO5fFK87K39tjW9vYMrf+xvvMnb/3a+btt916xcjf/f4PzVe//i1z7SuvMc/85Flz4q7bPc6MoSAAAQjESQDBGOe+MWtjzBt/8w/NzTcdNR898c7LPJTo4Ph7TpozX/pE9kBAa4aAxGF3fiZLiBNL/FRZErZmYxMlEMrOxdX1Nt7QhytjjALHFWcX/eTdfPUZk8hXRtqQMg2PW6fPeMXheci6ePprj5vHvvSJkVNUbKNiHCUmEYwuTit9QAACqRNAMKa+wwmv796TD5knnj57xUOBxKLaqU+fSHjlYSxN1sT/d347abfDVGo2FimV0dSpstayta2ekasvrRyBq1a6ZmF+NrPeKylT6FZ8nTXVV5R10Wd75sc/Nf/5f5/LMqPKuvjn73+X+ZVbXnegYHzgC38XvbuqhLFejB578y2X1/nNx5/KfhfvOH6MRD8+DyBjQSBxAgjGxDc45eXpAeHW3/qjzMKoH0y5Gt32rj/NxOLrbzqa8tKDWZviGs+t90x/dz+YOTUxkdhKF+QZ5N2G20qQYoW35iU32NBFTxNnqGyfYnb1yovxoBJgK4c7Ju+mWrbPpq9vK15R6zr7gx9lVkOV0ZCI+srnPzxyudZdNYVkONajRkl9JBD1m/i2d/7JSFfcpvee/iEAgbQJIBjT3t/kVyeL4vr6ZvZwoIeFbzz+1IFuSMnDaGmBimtc2+obuamm3Kw7ZyxugdaqODc3E4xIq1pCIuVzNWptEvnLh+bNxvaOkfuwbSFno106NJ+5zfqOVxzmJ1dUWd7ecMvrRrqbppYM53OnTmfr1YtS/QauLC/iYTNtXxisFwIeCCAYPUBmiOYI6OFArqlf+NQ95t0f/Awp1JtDPbFnCSmVBEi55Ws2hmwpsyVChgVHCHuDtXH8LhTJgqpstHL7VAvhHLYZr3gQTblmDrukpmRdzK9bVkVZWF8ty+pDf4YraghfdMwBAokRQDAmtqHTuBwlv/nPnzxLgeYANl/14+SimrrLYag1G5soldHUscLaeCXZKiVdBomZ5Ka6ezmbalP7NarfwZwXjARsyE0vFpURdX1jK0kvFFkYZWlUaEY+CVzIe8LcIACBuAggGOPaL2Y7goD9sSTjXRjHY1riGvMxZnLJbbtZy1RMtTBjsdg2vbcHuaAWGVcM5Q66uDCf1b7Mu7AWub/qNR3V3Fzpmvm52apdeLtPsX2f+6uvZplTUxNVNo5RMYwSjcr6OlxKxBtoBoIABJIlgGBMdmunZ2FyPbr7g58xjz74IXPjDddNz8IDX6ncU+WmmnILoWZj3jIl3jFad1MsYVL03MtCqPU/t1bPMp939V3f2jGy9jfVJFCtS2xTYzTRr4Tjvfd93hy9/jVJlNPQeo6/977L8Zo2nvHMFz9urn3VK5pASJ8QgMCUEkAwTunGp7RsSmmEu5sSMLK+7aedRDV74F9d7BqfNRvzCVBUbmEn8ky1dj2d+ZksFjb29Uz6VFqh77ompk3OpBImsji6/uxJKEowxtwUy7i6vBjzErK567dPrrb5uMVR/xb9QlkABCDQOgEEY+tbwATqENAP/y++5Q5KaQxBtG+ebWznqb94f/ZWvY2mB//n1i5Fafkqw8tnofoQSmWUYVPmWit4FJe3cTFNC7WNgZWga6I2Zd5N1dVLjDZLZpQ5P1wLAQhAAALuCSAY3TOlR48ElBlO/8sXLvY4fJBD2bTy77/rdvPfbzqaZZEVo8e+9InW5qvSG89v9Eyv35ybXGuLGxp4kMxlPste6dot0JbK6HbquzCGwmvUPEIuH1GHm9b1ssWO6czPGlmFm3YfduWmqvN2ZKkTRbxinf3hXghAAAIQGE0AwcjJgEBiBOSSpMQH1qL43e//0Nz2rj81Z770iaygdZttGuIaxbeJmo02McqgcHvaNS/tGW3avdLnZ6EpF9Qia6jDMcSSGUXWzDUQgAAEIOCOAILRHUt6gkCQBBTjcutv/mEQglGA5Gp4YbPnPLYqNPjWmjQ3N1OrVl7e1VUZUJu2SoXIceXwIDFME1ZbH+tt0upcZv7LhwfZVIu4qWbnd6lrFhfmygzBtRCAAAQgkCABBGOCm8qSIJAnoCyyH/jYg+Zf/uEvgwGj0ht1s0IGs5gJE7H1Bs/LJbdk5soYS2U0tS91rGRNzWlSv9aFeGZ2xqxt9oMQ+3ZOcouVxX/UmSRecdLO8ncIQAAC00UAwThd+81qp5DAyfsfyQpWh1bQWXGN5zeV9CN998p8zcYimSvtA7tiPqfRqjjuYzqwks0Fb21s0wW1yNecBLgynu7s7V8hZg9157J4xdnZmSLdcA0EIAABCEwBAQTjFGwyS5xuAm97xx+bE3f/tnn9TUezwtUPnDp9RRr2tulIEK0HUPi+aQ5FazZiVZy8E/MqGr/cNZcyQe2+dMTkGYy/wu5hDOVOrAVcsbEzMzNGc6dBAAIQgAAE8gQQjJwHCCRMQPGLVjBKKN5801Fzx+++NbiiznKLU+kN1zXjQtzagWvlS2s2xuhy2TZfK3bWtnqNlKcouz5ZFVeXOmZ/bz8qy7AE+CtedsjopQYNAhCAAAQgMEwAwciZgEDCBB5+9IyRS+rRn/tZ85mPvDs4oZhHr7jGc+s904+8AH2R42QT2eztm8y6unxo3qReKqMIlyrX5FkqTrStlw5W8F+8tJuJxVga8Yqx7BTzhAAEINAeAQRje+wZGQKNE3jmxz81T37ne9HUqVRc49pWP8ukOg3t5atds9CZMxd7u5lYplUnYK2NRTKAVh9l9J3WBTW2RE6qF6q5E6/o+kTQHwQgAIG0CCAY09pPVgOBJAhsbu9kGRxTbflMlbIwyo1Ra56W+opN7Wu+UL1KcDRdgiRf8uTCVnixlOM4U1+xqVNIvxCAAATSI4BgTG9PWREEkiCguEZZ3Zp+6PcNS5YwZaJUdlgrEF3VbPS9llDH82FtVF1I1YdUspiYhP7ABXXBKG6RBgEIQAACEChCAMFYhBLXQAACrRBIKa6xSKmM0JK4tLLpjgZt0toYqwtqR9llV7pmfm7WEWW6gQAEIACBaSCAYJyGXWaNEIicgNxT5bIZaytTKqNszcZYmfiatyyBq4svzUpbZXwr+rd7YZbzGLcmxSuq7iINAhCAAAQgUJYAgrEsMa6HAARaISDBqIQ4bWXBrLLoIlbFg/pdXewYiZ3YEqlU4dT0PXL5VSkT1aLXy4edCpl4Dy/MZdlsN7Z3jDKhxtQkFCUYfTTVel3f2DIry4vm2ldek9V/pUEAAhCAQNwEEIxx7x+zh8BUEdCDvuo1hh7XKIGi+DYJPiVfUTxmlXZQzcYqfXGPMbb0hbLwbpQofRGreG+jZMbaxpa577N/Y05//VvmxF23m7ffditHDwIQgAAEIieAYIx8A5k+BKaNgEpvPL/RM71+NRHWNC9ZouSC6qoeXyh1Bpvm5qt/K+YXOrOZtXGcmM+7oMq6HVNTXc8jS51W4hVV+/XsD35kTn36REzImCsEIAABCBxAAMHI0YAABKIkEFpcoy2VoQf1JtxIBwlx5mtZLKPc6IYmba2NB8UjxuyC2mbJjCefPmuOv+dkJhbz7qiyPN578iFz9PrXZFbH1eXFhnaWbiEAAQhAwDUBBKNrovQHAQh4IyDXwgubvdbjGl1bFQ8CqFIIV690jURObBYvb4eixECjXIfz/9aE8C8xvdKXZuVZlrpmcWGu9L2ubpBYVOziR0+884oun/nxT82T3/leZnn8xj/9m7nz937NHHvzLa6GpR8IQAACEGiQAIKxQbh0DQEINE9ApTfaerCXVXF1qZMlU/FRKF40raDpzM94G7P5XWx3hLy1UXGnrtyJfa6qjXjF4fU9/OgZ88AX/s6c+fInx1oQJRrf9s4/MWe++HFz7ate4RMTY0EAAhCAQAUCCMYK0LgFAhAIi4DiGs9v9s12z1/2SsUpHurOtZY109ZsXL/Yjy5rZ1inZzAb7adcfvf296Nz+9U5VLzirN5ceG7W1fTX3nyL+cDHHjRv//U3mTuPHxs7C93zi2+5wzz64IfMjTdc53nGDAcBCEAAAmUJIBjLEuN6CEAgWALrF3fMesPJSeqUynANjpqN9YlmbpyLHTM3N7DYiqnKUFzqx1Frsc14RUtfcYsfOPmQ+c+fPGv++e8/NzE+8d6PPWi+8fhTEy2R9XeXHiAAAQhAwAUBBKMLivQBAQgEQ0BZL1V6o4l6jbJCKV5RwjSkWny27MPz671KNQaD2TzPE7Hif5QL6vLh+azu4vnNXhYzGlqzwlbWxVDaA6dOm9P/+E/mK5//8BWiURbFs9//ofnq179lnnj6bDbdz37k3VkCHBoEIAABCIRPAMEY/h4xQwhAoCQBxTWeW++ZfoUC7aOGyse4bW7vBFkHUnOUZWzr0o7Z3Pbnmltya4K53Ir/cXUyQy1pEkK84kEbKXFoM6CqvMaT3/6uOfvv/2GO/tzPmqM3XJdlTiXZTTAfAyYCAQhAoBABBGMhTFwEAQjERkBxjcokqkyqVVvTpTKqzuug++ReqSyqarI2NmFldT1n3/3ZPZ2ZnTFrm/1C4t/Gi25u91sX44qzlNhtI16xzF5JOCqxjZpKbChzKg0CEIAABOIkgGCMc9+YNQQgUJCALIKq2Vi2+SqVUXZeRa6nZuNoSrYsSZUsqNbaqJ59ZcQdXkUI8YpFzl/+Guum+ju//qas/iINAhCAAATiI4BgjG/PmDEEIFCSgOIa5aK6u7c/8c7YrIoHLYiajVeSsS6odeM827A2DlxQF4z2NMYma+N99z+S1WD8wqdPTEyKE+MamTMEIACBlAkgGFPeXdYGAQhcJlAkrlFiYHFhPpk4QFuzcaEzm7moFhHMqR0Zaxnc3d3PkhW5YODT2tiZmzFXrXTN/Nxs9FujbKqKYaRBAAIQgEBcBBCMce0Xs4UABGoSkHuq3FTzzZan6O+olIIbUVFzmk5vH7jXdsy01Wy0yYqquKAW2YCmrY2KV1QiIxoEIAABCECgTQIIxjbpMzYEINAKAQlGJcRRUphQS2W4BjNtNRvtvj631qxlVVbcI8tdMzvjNrZRQlGCkQYBCEAAAhBomwCCse0dYHwIQKAVAju7+0YRYZf6u0laFQ+CmnrNxry1+MILLwV8HLBD3VlzZKlrNrZ3zMbFKy3YZcYPuWRGmXVwLQQgAAEIpEMAwZjOXrISCECgAoFn1y6ZXj+8wuwVllL4FuuqKUtrSjUb5Xq7fKi9GNR8zKhcn5VsqUzrdiQ6O0nEK5ZZN9dCAAIQgEDYBBCMYe8Ps4MABDwQGBXX6GHYVofI12xsq0yESwC+XFCLzNkK8u2eYmIHrs+TWowlMyatib9DAAIQgEAaBBCMaewjq4AABGoS2Lq0ay5sTl+xe5sZtopFrCZyJ7dbF84y4szJwBM6sdZGuapKkB9kbdR1L1vqmsWFOR/TYgwIQAACEIBAaQIIxtLIuAECEEiVgEpvNJ0kJUR2sdZstC6oihtUJtQQ2zhrI/GKIe4Yc4IABCAAgWECCEbOBAQgAIEcgb29fXN+s2+2e2EKkKY2K7aajTZ5TwwCf5S18VB3LotXnFV6VRoEIAABCEAgYAIIxoA3h6lBAALtEVA9xvWtfnsTaGlkW7Nxc1v1KsMTzdYq11RtxSaxW2vj3p4xSnBDgwAEIAABCMRAAMEYwy4xRwhAoBUCijt7bu1SoaQlrUywoUElyo4sd8zu7r7xWZpi0nJsvGXILqjj1iCuqq8o6yINAhCAAAQgEAsBBGMsO8U8IQCBVggorvHces/0dwukumxlhs0NGkrNxrxLZwwuqKN2hHjF5s4pPUMAAhCAQLMEEIzN8qV3CEAgAQKKa1zb6htlUp221nbNxphdUO1ZWTo0b1T2g3jFafv0sF4IQAACaRBAMKaxj6wCAkkSeObHPzUPf+Uxc+Ku24NYnwrdq/zEtDVZ+I4sd43ys/is2SgXVIktiXWVzYixUV8xxl1jzhCAAAQgkCeAYOQ8QAACwRI4/bXHzb0nHzJ3Hj9m7jh+LIh5Kq5RLqq7e9PnojoQcB1zfqN3YF1BF5skq6IscnNzM14Fqou52z4GltEFo5IlNAhAAAIQgEDMBBCMMe8ec4dA4gRO3v+IefLb3zVn//0/zJkvftxc+6pXBLHiaY5rzNdsXL/Yd54QKAUX1M7cjLlqpWvm58iEGsQHlklAAAIQgEAtAgjGWvi4GQIQaJKArIuvv+moefLps+aJp8+ax770iSaHK9233FPlpjptramajbIqqqyH3F5lyY2xyYVWmVBpEIAABCAAgVQIIBhT2UnWAQEIQAACEIAABCAAAQhAwDEBBKNjoHQHAQhAAAIQgAAEIAABCEAgFQIIxlR2knVAAAIQgAAEIAABCEAAAhBwTADB6Bgo3UEAAhCAAAQgAAEIQAACEEiFAIIxlZ1kHRCAAAQgAAEIQAACEIAABBwTQDA6Bkp3EIAABCAAAQhAAAIQgAAEUiGAYExlJ1kHBCAAAQhAAAIQgAAEIAABxwQQjI6B0h0EIAABCEAAAhCAAAQgAIFUCCAYU9lJ1gEBCEAAAhCAAAQgAAEIQMAxAQSjY6B0BwEIQAACEIAABCAAAQhAIBUCCMZUdpJ1QAACEIAABCAAAQhAAAIQcEwAwegYKN1BAAIQgAAEIAABCEAAAhBIhQCCMZWdZB0QgAAEIAABCEAAAhCAAAQcE0AwOgZKdxCAAAQgAAEIQAACEIAABFIhgGBMZSdZBwQgAAEIQAACEIAABCAAAccEEIyOgdIdBCAAAQhAAAIQgAAEIACBVAggGFPZSdYBAQhAAAIQgAAEIAABCEDAMQEEo2OgdAcBCEAAAhCAAAQgAAEIQCAVAgjGVHaSdUAAAhCAAAQgAAEIQAACEHBMAMHoGCjdQQACEIAABCAAAQhAAAIQSIUAgjGVnWQdEIAABCAAAQhAAAIQgAAEHBNAMDoGSncQgAAEIAABCEAAAhCAAARSIYBgTGUnWQcEIAABCEAAAhCAAAQgAAHHBBCMjoHSHQQgAAEIQAACEIAABCAAgVQIIBhT2UnWAQEIQAACEIAABCAAAQhAwDEBBKNjoHQHAQhAAAIQgAAEIAABCEAgFQIIxlR2knVAAAIQgAAEIAABCEAAAhBwTADB6Bgo3UEAAhCAAAQgAAEIQAACEEiFAIIxlZ1kHRCAAAQgAAEIQAACEIAABBwTQDA6Bkp3EIAABCAAAQhAAAIQgAAEUiGAYExlJ1kHBCAAAQhAAAIQgAAEIAABxwQQjI6B0h0EIAABCEAAAhCAAAQgAIFUCCAYU9lJ1gEBCEAAAhCAAAQgAAEIQMAxAQSjY6B0BwEIQAACEIAABCAAAQhAIBUCCMZUdpJ1QAACEIAABCAAAQhAAAIQcEwAwegYKN1BAAIQgAAEIAABCEAAAhBIhQCCMZWdZB0QgAAEIAABCEAAAhCAAAQcE0AVPXOnAAAD8klEQVQwOgZKdxCAAAQgAAEIQAACEIAABFIhgGBMZSdZBwQgAAEIQAACEIAABCAAAccEEIyOgdIdBCAAAQhAAAIQgAAEIACBVAggGFPZSdYBAQhAAAIQgAAEIAABCEDAMQEEo2OgdAcBCEAAAhCAAAQgAAEIQCAVAgjGVHaSdUAAAhCAAAQgAAEIQAACEHBMAMHoGCjdQQACEIAABCAAAQhAAAIQSIUAgjGVnWQdEIAABCAAAQhAAAIQgAAEHBNAMDoGSncQgAAEIAABCEAAAhCAAARSIYBgTGUnWQcEIAABCEAAAhCAAAQgAAHHBBCMjoHSHQQgAAEIQAACEIAABCAAgVQIIBhT2UnWAQEIQAACEIAABCAAAQhAwDEBBKNjoHQHAQhAAAIQgAAEIAABCEAgFQIIxlR2knVAAAIQgAAEIAABCEAAAhBwTADB6Bgo3UEAAhCAAAQgAAEIQAACEEiFAIIxlZ1kHRCAAAQgAAEIQAACEIAABBwTQDA6Bkp3EIAABCAAAQhAAAIQgAAEUiGAYExlJ1kHBCAAAQhAAAIQgAAEIAABxwQQjI6B0h0EIAABCEAAAhCAAAQgAIFUCCAYU9lJ1gEBCEAAAhCAAAQgAAEIQMAxAQSjY6B0BwEIQAACEIAABCAAAQhAIBUCCMZUdpJ1QAACEIAABCAAAQhAAAIQcEwAwegYKN1BAAIQgAAEIAABCEAAAhBIhQCCMZWdZB0QgAAEIAABCEAAAhCAAAQcE0AwOgZKdxCAAAQgAAEIQAACEIAABFIhgGBMZSdZBwQgAAEIQAACEIAABCAAAccEEIyOgdIdBCAAAQhAAAIQgAAEIACBVAggGFPZSdYBAQhAAAIQgAAEIAABCEDAMQEEo2OgdAcBCEAAAhCAAAQgAAEIQCAVAgjGVHaSdUAAAhCAAAQgAAEIQAACEHBMAMHoGCjdQQACEIAABCAAAQhAAAIQSIUAgjGVnWQdEIAABCAAAQhAAAIQgAAEHBNAMDoGSncQgAAEIAABCEAAAhCAAARSIYBgTGUnWQcEIAABCEAAAhCAAAQgAAHHBBCMjoHSHQQgAAEIQAACEIAABCAAgVQIIBhT2UnWAQEIQAACEIAABCAAAQhAwDEBBKNjoHQHAQhAAAIQgAAEIAABCEAgFQIIxlR2knVAAAIQgAAEIAABCEAAAhBwTADB6Bgo3UEAAhCAAAQgAAEIQAACEEiFAIIxlZ1kHRCAAAQgAAEIQAACEIAABBwTQDA6Bkp3EIAABCAAAQhAAAIQgAAEUiGAYExlJ1kHBCAAAQhAAAIQgAAEIAABxwQQjI6B0h0EIAABCEAAAhCAAAQgAIFUCPx/of5K7wE81VsAAAAASUVORK5CYII=", - "text/html": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "show_pharmacophoric_descriptors(p4_table,show_vectors=True)" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "id": "b4180062-3a74-48bb-954e-dbedd5fb70c2", "metadata": { "tags": [] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " PyMOL not running, entering library mode (experimental)\n" - ] - } - ], + "outputs": [], "source": [ - "save_pharmacophore_to_pymol(p4_table,out_file='Example/analysis/pharmacophore_all_descriptors.pse')" + "save_pharmacophore_to_pymol(p4_table,out_file='example_files/analysis/pharmacophore_all_descriptors.pse')" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 6, "id": "23b44433-a70f-41c1-9b90-083b85054fd6", "metadata": { "tags": [] }, "outputs": [], "source": [ - "save_pharmacophore_to_json(p4_table,out_file='Example/analysis/pharmacophore_all_descriptors.json')" + "save_pharmacophore_to_json(p4_table,out_file='example_files/analysis/pharmacophore_all_descriptors.json')" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "id": "d20a5bb9-3c23-41f5-9113-342c75936212", "metadata": { "tags": [] @@ -1815,7 +638,7 @@ " 0.5\n", " orange\n", " 3.0\n", - " 0.120000\n", + " 0.360000\n", " \n", " \n", " 2\n", @@ -1827,7 +650,7 @@ " 0.5\n", " orange\n", " 3.0\n", - " 0.120000\n", + " 0.360000\n", " \n", " \n", " 3\n", @@ -1839,15 +662,15 @@ " 0.5\n", " orange\n", " 2.0\n", - " 0.080000\n", + " 0.160000\n", " \n", " \n", " 4\n", " HydrogenAcceptor\n", " 4.0\n", - " 14.119200\n", - " -0.52190\n", - " 22.537800\n", + " 12.081500\n", + " 0.42060\n", + " 24.291500\n", " 0.5\n", " orange\n", " 1.0\n", @@ -1857,9 +680,9 @@ " 5\n", " HydrogenAcceptor\n", " 5.0\n", - " 12.081500\n", - " 0.42060\n", - " 24.291500\n", + " 14.119200\n", + " -0.52190\n", + " 22.537800\n", " 0.5\n", " orange\n", " 1.0\n", @@ -1887,7 +710,7 @@ " 0.5\n", " white\n", " 2.0\n", - " 0.285714\n", + " 0.571429\n", " \n", " \n", " 8\n", @@ -1905,9 +728,9 @@ " 9\n", " HydrogenDonor\n", " 3.0\n", - " 10.203000\n", - " 0.24720\n", - " 25.711200\n", + " 7.452600\n", + " -0.74090\n", + " 20.904200\n", " 0.5\n", " white\n", " 1.0\n", @@ -1917,9 +740,9 @@ " 10\n", " HydrogenDonor\n", " 4.0\n", - " 7.452600\n", - " -0.74090\n", - " 20.904200\n", + " 10.203000\n", + " 0.24720\n", + " 25.711200\n", " 0.5\n", " white\n", " 1.0\n", @@ -1929,9 +752,9 @@ " 11\n", " Hydrophobic\n", " 1.0\n", - " 13.796500\n", - " -2.54690\n", - " 24.245400\n", + " 10.224300\n", + " -0.77370\n", + " 22.504100\n", " 1.0\n", " green\n", " 1.0\n", @@ -1941,9 +764,9 @@ " 12\n", " Hydrophobic\n", " 2.0\n", - " 10.224300\n", - " -0.77370\n", - " 22.504100\n", + " 13.796500\n", + " -2.54690\n", + " 24.245400\n", " 1.0\n", " green\n", " 1.0\n", @@ -1970,25 +793,25 @@ "1 HydrogenAcceptor 1.0 9.469333 0.78140 20.912233 0.5 orange \n", "2 HydrogenAcceptor 2.0 6.886800 0.40150 17.738200 0.5 orange \n", "3 HydrogenAcceptor 3.0 10.215450 5.01375 25.263100 0.5 orange \n", - "4 HydrogenAcceptor 4.0 14.119200 -0.52190 22.537800 0.5 orange \n", - "5 HydrogenAcceptor 5.0 12.081500 0.42060 24.291500 0.5 orange \n", + "4 HydrogenAcceptor 4.0 12.081500 0.42060 24.291500 0.5 orange \n", + "5 HydrogenAcceptor 5.0 14.119200 -0.52190 22.537800 0.5 orange \n", "6 HydrogenAcceptor 6.0 8.507000 -3.44600 27.187000 0.5 orange \n", "7 HydrogenDonor 1.0 11.624950 5.67260 23.094300 0.5 white \n", "8 HydrogenDonor 2.0 9.050500 5.00120 22.914200 0.5 white \n", - "9 HydrogenDonor 3.0 10.203000 0.24720 25.711200 0.5 white \n", - "10 HydrogenDonor 4.0 7.452600 -0.74090 20.904200 0.5 white \n", - "11 Hydrophobic 1.0 13.796500 -2.54690 24.245400 1.0 green \n", - "12 Hydrophobic 2.0 10.224300 -0.77370 22.504100 1.0 green \n", + "9 HydrogenDonor 3.0 7.452600 -0.74090 20.904200 0.5 white \n", + "10 HydrogenDonor 4.0 10.203000 0.24720 25.711200 0.5 white \n", + "11 Hydrophobic 1.0 10.224300 -0.77370 22.504100 1.0 green \n", + "12 Hydrophobic 2.0 13.796500 -2.54690 24.245400 1.0 green \n", "13 Hydrophobic 3.0 9.948000 -5.50000 26.143000 1.0 green \n", "\n", " weight balance \n", - "1 3.0 0.120000 \n", - "2 3.0 0.120000 \n", - "3 2.0 0.080000 \n", + "1 3.0 0.360000 \n", + "2 3.0 0.360000 \n", + "3 2.0 0.160000 \n", "4 1.0 0.040000 \n", "5 1.0 0.040000 \n", "6 1.0 0.040000 \n", - "7 2.0 0.285714 \n", + "7 2.0 0.571429 \n", "8 1.0 0.142857 \n", "9 1.0 0.142857 \n", "10 1.0 0.142857 \n", @@ -1997,55 +820,49 @@ "13 1.0 0.333333 " ] }, - "execution_count": 9, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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", 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], "source": [ - "concensus,links=compute_concensus_pharmacophore(p4_table,save_data_per_descriptor=True,out_folder='Example/analysis/')\n", + "concensus,links=compute_concensus_pharmacophore(p4_table,save_data_per_descriptor=True,out_folder='example_files/analysis/',cmap_plots=\"binary_r\")\n", "concensus" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 8, "id": "f72c4947-56c6-4e90-bd55-ada6ae0690a5", "metadata": { "tags": [] @@ -2054,42 +871,42 @@ { "data": { "text/plain": [ - "array([[ 0. , 7.85252891, 9.15865598, 8.52722908, 6.00928998,\n", - " 10.55527041, 7.5849763 , 10.1845986 , 7.61931931, 10.25784306,\n", - " 7.68393888],\n", - " [ 7.85252891, 0. , 7.55941581, 7.04944059, 2.84885788,\n", - " 9.0035123 , 5.22144952, 8.43535958, 5.11982078, 8.7526874 ,\n", - " 4.95283595],\n", - " [ 9.15865598, 7.55941581, 0. , 0.66255546, 5.35807925,\n", - " 9.63913655, 6.55340164, 9.48075752, 6.22426134, 9.64278695,\n", + "array([[ 0. , 4.15425734, 10.55527041, 8.59358854, 0.64017448,\n", + " 4.36893551, 0.41423497, 4.46072 , 9.36536003, 9.0035123 ,\n", + " 9.63913655],\n", + " [ 4.15425734, 0. , 7.5849763 , 4.44092272, 3.70206775,\n", + " 0.34854284, 3.95074704, 0.44199327, 6.11361602, 5.22144952,\n", + " 6.55340164],\n", + " [10.55527041, 7.5849763 , 0. , 6.00928998, 10.1845986 ,\n", + " 7.61931931, 10.25784306, 7.68393888, 8.52722908, 7.85252891,\n", + " 9.15865598],\n", + " [ 8.59358854, 4.44092272, 6.00928998, 0. , 8.12551569,\n", + " 4.25425587, 8.37603852, 4.17352922, 4.74940299, 2.84885788,\n", + " 5.35807925],\n", + " [ 0.64017448, 3.70206775, 10.1845986 , 8.12551569, 0. ,\n", + " 3.93982458, 0.36719665, 4.01744379, 9.17657352, 8.43535958,\n", + " 9.48075752],\n", + " [ 4.36893551, 0.34854284, 7.61931931, 4.25425587, 3.93982458,\n", + " 0. , 4.18875454, 0.20579189, 5.79003988, 5.11982078,\n", + " 6.22426134],\n", + " [ 0.41423497, 3.95074704, 10.25784306, 8.37603852, 0.36719665,\n", + " 4.18875454, 0. , 4.27844934, 9.34327172, 8.7526874 ,\n", + " 9.64278695],\n", + " [ 4.46072 , 0.44199327, 7.68393888, 4.17352922, 4.01744379,\n", + " 0.20579189, 4.27844934, 0. , 5.80816981, 4.95283595,\n", " 6.24266231],\n", - 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" 4.27844934],\n", - " [ 7.68393888, 4.95283595, 6.24266231, 5.80816981, 4.17352922,\n", - " 4.46072 , 0.44199327, 4.01744379, 0.20579189, 4.27844934,\n", + " [ 9.36536003, 6.11361602, 8.52722908, 4.74940299, 9.17657352,\n", + " 5.79003988, 9.34327172, 5.80816981, 0. , 7.04944059,\n", + " 0.66255546],\n", + " [ 9.0035123 , 5.22144952, 7.85252891, 2.84885788, 8.43535958,\n", + " 5.11982078, 8.7526874 , 4.95283595, 7.04944059, 0. ,\n", + " 7.55941581],\n", + " [ 9.63913655, 6.55340164, 9.15865598, 5.35807925, 9.48075752,\n", + " 6.22426134, 9.64278695, 6.24266231, 0.66255546, 7.55941581,\n", " 0. ]])" ] }, - "execution_count": 10, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -2100,7 +917,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "id": "6f681aef-0cdf-48aa-8150-f729fbddc0cd", "metadata": { "tags": [] @@ -2109,19 +926,19 @@ { "data": { "text/plain": [ - "array([[ 8. , 10. , 0.39391824, 2. ],\n", - " [ 5. , 9. , 0.85088643, 2. ],\n", - " [ 6. , 11. , 1.02721302, 3. ],\n", - " [ 7. , 12. , 1.46525639, 3. ],\n", - " [ 2. , 3. , 1.65383046, 2. ],\n", - " [ 1. , 4. , 5.66896962, 2. ],\n", + "array([[ 5. , 7. , 0.39391824, 2. ],\n", + " [ 0. , 6. , 0.85088643, 2. ],\n", + " [ 1. , 11. , 1.02721302, 3. ],\n", + " [ 4. , 12. , 1.46525639, 3. ],\n", + " [ 8. , 10. , 1.65383046, 2. ],\n", + " [ 3. , 9. , 5.66896962, 2. ],\n", " [13. , 14. , 12.86957278, 6. ],\n", " [15. , 16. , 13.03958151, 4. ],\n", - " [ 0. , 18. , 15.39238901, 5. ],\n", + " [ 2. , 18. , 15.39238901, 5. ],\n", " [17. , 19. , 21.35398639, 11. ]])" ] }, - "execution_count": 11, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -2132,34 +949,34 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "id": "11e6d11b-9d90-4f9d-ad07-7d9707f9a73f", "metadata": { "tags": [] }, "outputs": [], "source": [ - "save_pharmacophore_to_pymol(concensus,out_file='Example/analysis/pharmacophore_concensus.pse',select='concensus')" + "save_pharmacophore_to_pymol(concensus,out_file='example_files/analysis/pharmacophore_concensus.pse',select='concensus')" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "id": "fa3f2774-0c10-4b1b-88d3-b5d040b7a0a0", "metadata": { "tags": [] }, "outputs": [], "source": [ - "save_pharmacophore_to_json(p4_table,out_file='Example/analysis/pharmacophore_concensus.json')" + "save_pharmacophore_to_json(concensus,out_file='example_files/analysis/pharmacophore_concensus.json')" ] } ], "metadata": { "kernelspec": { - "display_name": "PyPharmer", + "display_name": "Chem3", "language": "python", - "name": "pypharmer" + "name": "chem3" }, "language_info": { "codemirror_mode": { @@ -2171,7 +988,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.13" + "version": "3.12.5" } }, "nbformat": 4, diff --git a/tutorials/ReceptorLigandPharmacophores.ipynb b/tutorials/ReceptorLigandPharmacophores.ipynb index bd6d419..b4e61d4 100644 --- a/tutorials/ReceptorLigandPharmacophores.ipynb +++ b/tutorials/ReceptorLigandPharmacophores.ipynb @@ -12,16 +12,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "5c492224-9174-4d92-8aed-f5888a32472d", "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ConPhar tools imported successfully\n" + ] + } + ], "source": [ - "from conphar.Receptor import search_uniprot, fetch_structure\n", + "from conphar.Structures import search_uniprot, fetch_structure\n", "\n", - "from conphar.Pharmacophore import get_ligand_receptor_pharmacophore\n", + "from conphar.Pharmacophores import get_ligand_receptor_pharmacophore\n", "\n", "import pandas as pd\n", "import os" @@ -29,12 +37,128 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "d951b563-5529-418a-a75c-54e7e1f360f9", "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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ACCESIONENTRY_idSTATUSSCOREEXISTENCEPROTEIN_nameFUNCTIONGENE_nameGENE_idREFSEQ...BIOCYCINTERPROPFAMFEATURE_active_siteFEATURE_siteFEATURE_bindingCATALYTIC_activityRHEALENGTHSEQUENCE
0P0DTD1R1AB_SARS2reviewed5.0Evidence at protein levelReplicase polyprotein 1ab (pp1ab) (ORF1ab poly...FUNCTION: [Replicase polyprotein 1ab]: Multifu...repNaNNaN...NaNIPR027351;IPR046443;IPR046440;IPR046442;IPR050...PF13087;PF16251;PF11501;PF12379;PF12124;PF1163...ACT_SITE 1674; /note=\"For PL-PRO activity\"; /e...SITE 180..181; /note=\"Cleavage; by PL-PRO\"; /e...BINDING 200; /ligand=\"Zn(2+)\"; /ligand_id=\"ChE...CATALYTIC ACTIVITY: [RNA-directed RNA polymera...RHEA:21248 RHEA:13065 RHEA:13065 RHEA:67020 RH...7096MESLVPGFNEKTHVQLSLPVLQVRDVLVRGFGDSVEEVLSEARQHL...
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1 rows × 34 columns

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" + ], + "text/plain": [ + " ACCESION ENTRY_id STATUS SCORE EXISTENCE \\\n", + "0 P0DTD1 R1AB_SARS2 reviewed 5.0 Evidence at protein level \n", + "\n", + " PROTEIN_name \\\n", + "0 Replicase polyprotein 1ab (pp1ab) (ORF1ab poly... \n", + "\n", + " FUNCTION GENE_name GENE_id \\\n", + "0 FUNCTION: [Replicase polyprotein 1ab]: Multifu... rep NaN \n", + "\n", + " REFSEQ ... BIOCYC INTERPRO \\\n", + "0 NaN ... NaN IPR027351;IPR046443;IPR046440;IPR046442;IPR050... \n", + "\n", + " PFAM \\\n", + "0 PF13087;PF16251;PF11501;PF12379;PF12124;PF1163... \n", + "\n", + " FEATURE_active_site \\\n", + "0 ACT_SITE 1674; /note=\"For PL-PRO activity\"; /e... \n", + "\n", + " FEATURE_site \\\n", + "0 SITE 180..181; /note=\"Cleavage; by PL-PRO\"; /e... \n", + "\n", + " FEATURE_binding \\\n", + "0 BINDING 200; /ligand=\"Zn(2+)\"; /ligand_id=\"ChE... \n", + "\n", + " CATALYTIC_activity \\\n", + "0 CATALYTIC ACTIVITY: [RNA-directed RNA polymera... \n", + "\n", + " RHEA LENGTH \\\n", + "0 RHEA:21248 RHEA:13065 RHEA:13065 RHEA:67020 RH... 7096 \n", + "\n", + " SEQUENCE \n", + "0 MESLVPGFNEKTHVQLSLPVLQVRDVLVRGFGDSVEEVLSEARQHL... \n", + "\n", + "[1 rows x 34 columns]" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data=search_uniprot(query='P0DTD1')\n", "data" @@ -42,12 +166,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "1e5a6c5f-f7c6-48e2-8b88-e798a6f7cbbd", "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['5R7Y', '5R7Z', '5R80', '5R81', '5R82', '5R83', '5R84', '5R8T', '5RE4', '5RE5', '5RE6', '5RE7', '5RE8', '5RE9', '5REA', '5REB', '5REC', '5RED', '5REE', '5REF', '5REG', '5REH', '5REI', '5REJ', '5REK']\n" + ] + }, + { + "data": { + "text/plain": [ + "2025" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "Mpro_PDB=data.PDB.iloc[0].split(';')\n", "print (Mpro_PDB[:25])\n", @@ -56,16 +198,193 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "320e64da-1684-4bc3-a374-35f7366f8789", "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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refined_RMSDrefined_num_atomsn_cyclesraw_RMSDraw_num_atomsaligment_scoren_residues_alignedlig_n_atoms
5R7Y0.0000002363.00.00.0000002363.01635.0304.013.0
5R7Z0.1117241998.05.00.3617632363.01635.0304.016.0
5R800.1817362026.05.00.4627632363.01635.0304.014.0
5R810.2535752059.05.00.4683262363.01635.0304.015.0
5R820.1320952039.05.00.4069722363.01635.0304.011.0
5R830.1251611974.05.00.3686682363.01635.0304.016.0
5R840.2553362025.05.00.5966372355.01635.0304.016.0
5R8T0.1499372007.05.00.3953792358.01635.0304.00.0
5RE40.2203532127.05.00.4282542363.01635.0304.011.0
5RE50.2252442032.05.00.4512512363.01635.0304.018.0
\n", + "
" + ], + "text/plain": [ + " refined_RMSD refined_num_atoms n_cycles raw_RMSD raw_num_atoms \\\n", + "5R7Y 0.000000 2363.0 0.0 0.000000 2363.0 \n", + "5R7Z 0.111724 1998.0 5.0 0.361763 2363.0 \n", + "5R80 0.181736 2026.0 5.0 0.462763 2363.0 \n", + "5R81 0.253575 2059.0 5.0 0.468326 2363.0 \n", + "5R82 0.132095 2039.0 5.0 0.406972 2363.0 \n", + "5R83 0.125161 1974.0 5.0 0.368668 2363.0 \n", + "5R84 0.255336 2025.0 5.0 0.596637 2355.0 \n", + "5R8T 0.149937 2007.0 5.0 0.395379 2358.0 \n", + "5RE4 0.220353 2127.0 5.0 0.428254 2363.0 \n", + "5RE5 0.225244 2032.0 5.0 0.451251 2363.0 \n", + "\n", + " aligment_score n_residues_aligned lig_n_atoms \n", + "5R7Y 1635.0 304.0 13.0 \n", + "5R7Z 1635.0 304.0 16.0 \n", + "5R80 1635.0 304.0 14.0 \n", + "5R81 1635.0 304.0 15.0 \n", + "5R82 1635.0 304.0 11.0 \n", + "5R83 1635.0 304.0 16.0 \n", + "5R84 1635.0 304.0 16.0 \n", + "5R8T 1635.0 304.0 0.0 \n", + "5RE4 1635.0 304.0 11.0 \n", + "5RE5 1635.0 304.0 18.0 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "matrix=pd.DataFrame()\n", "for pdb in Mpro_PDB[:10]:\n", - " data=fetch_structure(target=pdb,target_chain='A',reference='5R7Y',reference_chain='A',output_folder='Example',extract_ligands=True)\n", + " data=fetch_structure(target=pdb,target_chain='A',reference='5R7Y',reference_chain='A',output_folder='example_files/',extract_ligands=True)\n", " matrix=pd.concat([matrix,data])\n", "matrix" ] @@ -80,15 +399,15 @@ "outputs": [], "source": [ "for file in os.listdir('Example/receptor/'):\n", - " get_ligand_receptor_pharmacophore(receptor=f\"Example/receptor/{file}\",ligand=f\"Example/ligand/{file.split('_')[0]}_lig.sdf\",out=f\"Example/pharmacophores/{file.split('_')[0]}\")" + " get_ligand_receptor_pharmacophore(receptor=f\"Example/receptor/{file}\",ligand=f\"Example/ligand/{file.split('_')[0]}_lig.sdf\",out=f\"exexample_files/pharmacophores/{file.split('_')[0]}\")" ] } ], "metadata": { "kernelspec": { - "display_name": "PyPharmer", + "display_name": "Chem3", "language": "python", - "name": "pypharmer" + "name": "chem3" }, "language_info": { "codemirror_mode": { @@ -100,7 +419,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.13" + "version": "3.12.5" } }, "nbformat": 4,