EDM-Dock

Code for our paper [Deep Learning Model for Flexible and Efficient Protein-Ligand Docking]()

Installation

git clone https://github.com/MatthewMasters/EDM-Dock
cd EDM-Dock
conda env create -f environment.yaml -n edm-dock
conda activate edm-dock
python setup.py install

Usage

Dock your own molecules using the pre-trained model

Step 1: Prepare a dataset using the following format

dataset_path/
    sys1/
        protein.pdb
        ligand.sdf
        box.csv
    sys2/
        protein.pdb
        ligand.sdf
        box.csv
    ...

The box.csv file defines the binding site box and should have six comma-seperated values:

center_x, center_y, center_z, width_x, width_y, width_z

Step 2: Prepare the features using the following command

python scripts/prepare.py --dataset_path [dataset_path]

Step 3: Download DGSOL

Since DGSOL does not have an MIT license, it's code is included in a seperate repository (https://github.com/MatthewMasters/DGSOL.git). Once you have downloaded DGSOL independently, update the path at the top of edmdock/utils/dock.py to reflect the path on your system. Remember to rebuild the package by issuing the command python setup.py install.

Step 4: Run Docking

By default this will run the docking including the minimization process. You can turn off minimization for much faster docking, however it may generate unrealistic molecular structures by editing the last line in runs/paper_baseline/config.yml.

python scripts/dock.py --run_path runs/paper_baseline --dataset_path [dataset_path]

The final docked poses are saved in the folder runs/paper_baseline/results as [ID]_docked.pdb.

Train model using your own dataset

Step 1: Prepare a dataset using the format described above

Step 2: Prepare the features using the following command

python scripts/prepare.py --dataset_path [dataset_path]

Step 3: Write a configuration file

An example can be found at runs/paper_baseline/config.yml

Step 4: Begin training with the following command

python scripts/train.py --config_path [config_path]

Reference

Under Review