visualise.ipynb

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  {
   "source": [
    "# Visualisation example\n",
    "\n",
    "This is a quick notebook to demonstrate the 2D descriptors computed by RDKit for ligands for two targets: trypsin and thrombin. We compare the distribution of binding affinity data for both targets, as well as the overlap of the molecules in the data sets. We examine the distribution of several physically-meaningful descriptors and decide how to handle outliers."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "import json\n",
    "\n",
    "import pandas as pd\n",
    "import seaborn as sns \n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "plt.style.use('fivethirtyeight')"
   ],
   "cell_type": "code",
   "metadata": {},
   "execution_count": 7,
   "outputs": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "trypsin_data = pd.read_csv('./chembl_data/try1_extracted_chembl_data.csv', index_col=0)\n",
    "thrombin_data = pd.read_csv('./chembl_data/thrb_extracted_chembl_data.csv', index_col=0)\n",
    "\n",
    "with open('./chembl_data/try1_ligands_descriptors.json') as f:\n",
    "    trypsin_features = json.load(f)\n",
    "  \n",
    "with open('./chembl_data/thrb_ligands_descriptors.json') as f:\n",
    "    thrombin_features = json.load(f)\n",
    "\n",
    "trypsin_features = pd.DataFrame.from_dict(trypsin_features, orient='index')\n",
    "thrombin_features = pd.DataFrame.from_dict(thrombin_features, orient='index')"
   ]
  },
  {
   "source": [
    "Due to similarities in their active site, trypsin and thrombin share many ligands. Let's visualse the proportion of ligands in our data set that bind to both targets."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Text(0, 0.5, 'Number of ligands')"
     },
     "metadata": {},
     "execution_count": 9
    },
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "n_trypsin = len(trypsin_data.index)\n",
    "n_thrombin = len(thrombin_data.index)\n",
    "n_shared = len(trypsin_data.index.intersection(thrombin_data.index))\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6,6))\n",
    "sns.barplot(['Trypsin', 'Thrombin', 'Shared'], [n_trypsin, n_thrombin, n_shared], ax=ax)\n",
    "ax.set_xlabel('Target')\n",
    "ax.set_ylabel('Number of ligands')\n"
   ]
  },
  {
   "source": [
    "Next, let's look at the distribution of the binding affinities for our ligands. pChEMBL is the negative base-10 logarithm of the binding constant, so a difference of one unit corresponds to an order of magnitude difference in binding energy. "
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Text(0.5, 1.0, 'Thrombin')"
     },
     "metadata": {},
     "execution_count": 58
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 864x432 with 2 Axes>",
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6), sharex=True, sharey=True)\n",
    "\n",
    "trypsin_data['pchembl_value'].hist(density=True, bins=range(2, 12), ax=ax1)\n",
    "thrombin_data['pchembl_value'].hist(density=True, bins=range(2, 12), ax=ax2)\n",
    "\n",
    "ax1.set_xlabel('pChEMBL value')\n",
    "ax2.set_xlabel('pChEMBL value')\n",
    "\n",
    "ax1.set_ylabel('Proportion of molecules')\n",
    "\n",
    "ax1.set_title('Trypsin')\n",
    "ax2.set_title('Thrombin')\n"
   ]
  },
  {
   "source": [
    "Both datasets span a good range of values. Now let's look at some of the properties of the molecules. \n",
    "\n",
    "Lipinski's rule of five is a rule of thumb often used to guide drug discovery. It states that a compound that violates more than one of the following conditions is unlikely to be orally available in humans:\n",
    "\n",
    "- No more than 5 hydrogen bond donors (the total number of nitrogen–hydrogen and oxygen–hydrogen bonds)\n",
    "- No more than 10 hydrogen bond acceptors (all nitrogen or oxygen atoms)\n",
    "- A molecular mass less than 500 daltons\n",
    "- An octanol-water partition coefficient (log P) that does not exceed 5\n",
    "\n",
    "For instance, let's look at the molecular weights of the molecules in our data set."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Text(0.5, 1.0, 'Thrombin')"
     },
     "metadata": {},
     "execution_count": 14
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 864x432 with 2 Axes>",
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6))\n",
    "\n",
    "trypsin_features['MolWt'].hist(ax=ax1, bins=25)\n",
    "thrombin_features['MolWt'].hist(ax=ax2, bins=25)\n",
    "\n",
    "ax1.set_xlabel('Molecular weight')\n",
    "ax2.set_xlabel('Molecular weight')\n",
    "\n",
    "ax1.set_ylabel('Number of molecules')\n",
    "\n",
    "ax1.set_title('Trypsin')\n",
    "ax2.set_title('Thrombin')"
   ]
  },
  {
   "source": [
    "Looks like we have some outliers with incredibly high molecular weight in our data! Let's be generous and restrict our data to molecules with a weight of less than 1000 Da."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "(15, 78)"
     },
     "metadata": {},
     "execution_count": 98
    }
   ],
   "source": [
    "len(trypsin_features[trypsin_features['MolWt'] > 1000]), len(thrombin_features[thrombin_features['MolWt'] > 1000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Text(0.5, 1.0, 'Thrombin')"
     },
     "metadata": {},
     "execution_count": 15
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 864x432 with 2 Axes>",
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     },
     "metadata": {}
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6), sharex=True, sharey=True)\n",
    "\n",
    "trypsin_features[trypsin_features['MolWt'] < 1000]['MolWt'].hist(ax=ax1, bins=25)\n",
    "thrombin_features[thrombin_features['MolWt'] < 1000]['MolWt'].hist(ax=ax2, bins=25)\n",
    "\n",
    "ax1.set_xlabel('Molecular weight')\n",
    "ax2.set_xlabel('Molecular weight')\n",
    "\n",
    "ax1.set_ylabel('Numberof molecules')\n",
    "\n",
    "ax1.set_title('Trypsin')\n",
    "ax2.set_title('Thrombin')"
   ]
  },
  {
   "source": [
    "Similarly, we can check for outliers in other properties. For example, the water-octanol partition coefficient, log P. First, let's look at all of the data."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Text(0.5, 1.0, 'Thrombin')"
     },
     "metadata": {},
     "execution_count": 16
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 864x432 with 2 Axes>",
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6))\n",
    "\n",
    "trypsin_features['MolLogP'].hist(ax=ax1, bins=25)\n",
    "thrombin_features['MolLogP'].hist(ax=ax2, bins=25)\n",
    "\n",
    "ax1.set_xlabel('Calculated log P')\n",
    "ax2.set_xlabel('Calculated log P')\n",
    "\n",
    "ax1.set_ylabel('Number of molecules')\n",
    "\n",
    "ax1.set_title('Trypsin')\n",
    "ax2.set_title('Thrombin')"
   ]
  },
  {
   "source": [
    "Looks like we have some outliers with large (negative) log P. First, let's drop the molecular weight outliers:"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Text(0.5, 1.0, 'Thrombin')"
     },
     "metadata": {},
     "execution_count": 17
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 864x432 with 2 Axes>",
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6), sharex=True, sharey=True)\n",
    "\n",
    "trypsin_features[trypsin_features['MolWt'] < 1000]['MolLogP'].hist(density=True, ax=ax1, bins=25)\n",
    "thrombin_features[thrombin_features['MolWt'] < 1000]['MolLogP'].hist(density=True, ax=ax2, bins=25)\n",
    "\n",
    "ax1.set_xlabel('Calculated log P')\n",
    "ax2.set_xlabel('Calculated log P')\n",
    "\n",
    "ax1.set_ylabel('Proportion of molecules')\n",
    "\n",
    "ax1.set_title('Trypsin')\n",
    "ax2.set_title('Thrombin')"
   ]
  },
  {
   "source": [
    "Or the flexibility of the molecule, captured by the number of rotatable bonds."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Text(0.5, 1.0, 'Thrombin')"
     },
     "metadata": {},
     "execution_count": 21
    },
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6))\n",
    "\n",
    "trypsin_features['NumRotatableBonds'].hist(ax=ax1, bins=25)\n",
    "thrombin_features['NumRotatableBonds'].hist(ax=ax2, bins=25)\n",
    "\n",
    "ax1.set_xlabel('Number of rotatable bonds')\n",
    "ax2.set_xlabel('Number of rotatable bonds')\n",
    "\n",
    "ax1.set_ylabel('Number of molecules')\n",
    "\n",
    "ax1.set_title('Trypsin')\n",
    "ax2.set_title('Thrombin')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "Text(0.5, 1.0, 'Thrombin')"
     },
     "metadata": {},
     "execution_count": 23
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 864x432 with 2 Axes>",
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6), sharex=True, sharey=True)\n",
    "\n",
    "trypsin_features[trypsin_features['MolWt'] < 1000]['NumRotatableBonds'].hist(ax=ax1, bins=25)\n",
    "thrombin_features[thrombin_features['MolWt'] < 1000]['NumRotatableBonds'].hist(ax=ax2, bins=25)\n",
    "\n",
    "ax1.set_xlabel('Number of rotatable bonds')\n",
    "ax2.set_xlabel('Number of rotatable bonds')\n",
    "\n",
    "ax1.set_ylabel('Numberof molecules')\n",
    "\n",
    "ax1.set_title('Trypsin')\n",
    "ax2.set_title('Thrombin')"
   ]
  },
  {
   "source": [
    "Looks like we still have some outliers. For reference, the protein-ligand docking tool AutoDock Vina struggles in terms of both speed and accuracy when docking molecules with more than ~15 rotatable bonds. As with molecular weight, here we might be generous and impose a limit of 20 rotatable bonds."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}