xxffliu / 3d-generative-sbdd

💊 A 3D Generative Model for Structure-Based Drug Design (NeurIPS 2021)

A 3D Generative Model for Structure-Based Drug Design

🚧 Work in progress...

Installation

Dependency

The code has been tested in the following environment:

Package	Version
Python	3.8.12
PyTorch	1.10.1
CUDA	11.3.1
PyTorch Geometric	2.0.3
RDKit	2020.09.5
OpenBabel	3.1.0

Install via Conda YML FIle (CUDA 11.3)

conda env create -f env_cuda113.yml
conda activate SBDD-3D

Install Manually

conda create --name SBDD-3D python=3.8
conda activate SBDD-3D

conda install pytorch=1.10.1 torchvision torchaudio cudatoolkit=11.3 -c pytorch
conda install pyg -c pyg -c conda-forge
conda install easydict -c conda-forge
conda install rdkit openbabel python-lmdb -c conda-forge
conda install tensorboard -c conda-forge

Datasets

Please refer to README.md in the data folder.

Sampling

Sampling for Pockets in the Testset

To sample molecules for the i-th pocket in the testset, please first download the trained models following README.md in the pretrained folder. Then, run the following command:

python sample.py ./configs/sample.yml --data_id {i}  # Replace {i} with the index of the data. i is between 0 and 99 for the testset.

Sampling for Other Pockets

🚧 Work in progress...

Training

🚧 Work in progress...

Citation

@inproceedings{luo2021sbdd,
    title={A 3D Generative Model for Structure-Based Drug Design},
    author={Shitong Luo and Jiaqi Guan and Jianzhu Ma and Jian Peng},
    booktitle={Thirty-Fifth Conference on Neural Information Processing Systems},
    year={2021}
}