DistPepFold

DistPepFold is a computational tool using deep learning for peptide docking.

Copyright (C) 2023 Zicong Zhang, Jacob Verburgt, Yuki Kagaya, Charles Christoffer, Daisuke Kihara, and Purdue University.

License: GPL v3. (If you are interested in a different license, for example, for commercial use, please contact us.)

Contact: Daisuke Kihara (dkihara@purdue.edu)

For technical problems or questions, please reach to Zicong Zhang (zhan1797@purdue.edu).

Colab Notebook

Installation

System Requirements

GPU: any GPU supports CUDA with at least 12GB memory.
GPU is required for DistPepFold and no CPU version is available.

Pre-required software

Required

Python 3 : https://www.python.org/downloads/

Optional for protein structure visualization

Pymol (for map visualization): https://pymol.org/2/

Environment set up

1. Install git

2. Clone the repository in your computer

git clone  https://github.com/kiharalab/DistPepFold.git && cd DistPepFold

3. Build dependencies.

3.1 Install with anaconda (Recommended)

3.1.1 install anaconda.

3.1.2 Install dependency in command line

Make sure you are in the DistPepFold directory and then run

conda env create -f environment.yml

Each time when you want to run this software, simply activate the environment by

conda activate distpepfold
conda deactivate(If you want to exit) 

Usage

bash pred.sh