EnzyGen

Generative Enzyme Design Guided by Functionally Important Sites and Small-Molecule Substrates

Model Architecture

This repository contains code, data and model weights for ICML 2024 paper Generative Enzyme Design Guided by Functionally Important Sites and Small-Molecule Substrates

The overall model architecture is shown below:

Usage

1. Clone the Repository

Make sure you have git lfs installed

git clone https://huggingface.co/charlesnovak/EnzyGen
cd EnzyGen 

2. Set up the Conda Environment

Make sure you have Conda installed. Then run,

bash setup_conda.sh
conda activate enzygen

3. Prepare Input Data

Modify the provided data/input_example.json

4. Edit infer.sh for Your Task

Make sure paths are correctly provided and the EC numbers for the proteins in the input data are provided

5. Run Inference

bash infer.sh

Outputs

There are 5 items in the outputs directory

1. protein.txt refers to the designed protein sequence
2. src.seq.txt refers to the ground truth sequences
3. pdb.txt refers to the target PDB ID and the corresponding chain
4. pred_pdbs refers to the directory of designed pdbs
5. tgt_pdbs refers to the directory of target pdbs

Citation

@inproceedings{songgenerative,
  title={Generative Enzyme Design Guided by Functionally Important Sites and Small-Molecule Substrates},
  author={Song, Zhenqiao and Zhao, Yunlong and Shi, Wenxian and Jin, Wengong and Yang, Yang and Li, Lei},
  booktitle={Forty-first International Conference on Machine Learning}
}