Awesome
<div align="center">Generative Diffusion Models for Antibody Design, Docking, and Optimization
<!-- [](https://papers.nips.cc/paper/2020) --> </div>Official <a href="https://pytorch.org/get-started/locally/"><img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-ee4c2c?logo=pytorch&logoColor=white"></a> implementation of Generative Diffusion Models for Antibody Design, Docking, and Optimization.
The wet experiment data used to validate our pipeline is available at wet_experiment_data.zip
Quick start
Installation
git clone git@github.com:pengzhangzhi/ab_opt.git
Antibody optimization pipeline
want to use it online? Check out the colab version of the antibody optimization pipeline.
Running the pipeline in local
git clone git@github.com:pengzhangzhi/ab_opt.git- Go the AbDock
- Follow the README to install the env
- Open notebook ab_opt.ipynb
- specify pdb file which contains an antibody-antigen complex structure
- specify the heavy chain ID and the residue indices to be designed
AbDesign
Please take a look at the AbDesign on reproducing the training and evaluation of the AbDesign.
AbDock
Please refer to the AbDock on how to reproduce the training and evaluation of the AbDock and the antibody optimization pipeline.
Credits <a name = "credits"></a>
This codebase is based on the following repositories, we thank the authors for their great work.