Augmenting a training dataset of the generative diffusion model for molecular docking with artificial binding pockets

---

Article

doi.org/10.1039/D3RA08147H

Data preparation

The model is trained to dock small molecules in a predefined binding pocket. Therefore, the input PDB file is expected to include only pocket residues. A general recommendation is to consider all the residues within 5-6 Å of any heavy atom of known ligand (15-30 residues) or equivalent pocket sizes for the binding sites defined by other methods. Refer to the examples/extract_pocket.py as basic pocket extraction script.

Usage

From source code

1. Install the recommended dependencies compatible to your hardware and operating system
   
   • Git LFS
     
   • Python >= 3.8
     
   • PyTorch >= 2.0
     
   • PyTorch Geometric (including torch_scatter and torch_cluster)
     
   • reduce
     
2. Clone the repository, navigate to the cloned folder, pull model weights
   git clone https://github.com/vtarasv/pocket-cfdm.git
cd pocket-cfdm/
git lfs pull
   
3. Install required packages
   pip install -r requirements.txt
   
4. Run the inference
   python predict.py --pdb my_pocket.pdb --sdf my_ligands.sdf --save_path my_ligands_docked.sdf --samples 16 --batch_size 16 --no_filter
   An increase of samples argument will lead to generation of higher alternative poses per docked molecule (better prediction quality for additional computational cost).
   Consider decreasing the batch_size if you face GPU memory-related errors.
   By default the results include only poses with acceptable quality. The no_filter flag allows to write all the generated poses despite their quality.
   The first script run will take some time to precompute and save in the cache required data distributions.

Docker image

1. Pull the docker image
   docker pull vtarasv/pocket-cfdm
2. Run the inference code using docker
   docker run -it --rm --gpus all -v '/home/':'/home/' vtarasv/pocket-cfdm -m predict --pdb /home/user/temp/my_pocket.pdb --sdf /home/user/temp/my_ligands.sdf --save_path /home/user/temp/my_ligands_docked.sdf