Requirements:
- python (I used 3.9.12)
- autodockvina
- vina
Download the code or simply run
git clone https://github.com/erfantoloue/AutoDocker.git
Convert and clean your PDB receptor structure using AutoDockTools into a PDBQT format and put it in the receptor directory. Mention its name in the config.txt file.
Download your ligands structures from any chemical databases. The format should be in SDF and all of them should be in the ligands directory. My recommendation is the ZINC database which is designed for molecular docking/virtual screening and the ligands are optimized as well.
Use AutoDockTools software to determine the exact grid dimensions and grid center for your receptor. This is highly crucial as it will increase the accuracy of the results.
Exhaustiveness refers to the level of thoroughness with which the docking algorithm explores the conformational space of the ligand-receptor complex to search for potential binding poses.
N_poses also refers to the number of poses that you may want for each of the docking results. When docking a lot of ligands into one receptor, I usually put it on 1, so that analyzing the results would be easier.
After finalizing the parameters run
python dock.py
It will first turn the first .sdf file into a .pdbqt file. Consecutively, the ligand will be docked into the receptor. This process will be repeated for each ligand. The docking results will be available in the docking_result directory.
Attention: Use a HPC (High Perfomance Computing) unit or a server if you want higher exhaustiveness or if you have a lot of ligands.