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drlcomplex's Introduction

Deep reinforcement learning for protein complex modeling Write by PyTorch

Dependencies

  • PyRosetta==4
  • numpy>=1.20.2
  • pandas>=1.2.5
  • tqdm==4.61.1
  • scipy>=1.6.2
  • seaborn>=0.11.2
  • setuptools>=44.0.0
  • imageio>=2.10.1
  • matplotlib>=3.4.2
  • tensorflow==1.15

Installation

The package is tested using Python 3.6 and 3.7. To install the software, please follow the instructions below:

  • Install the above dependencies
  • Download and install PyRosetta (http://www.pyrosetta.org/dow)
  • Install the package following the instruction below:
git clone [email protected]:jianlin-cheng/DeepRLP.git

(If fail, try username) git clone https://github.com/jianlin-cheng/DeepRLP.git

cd DeepRLP
pip install -r requirements.txt


Alternatively, environment.yml files are provided to install the required packages using pip or conda.

Basic Usage

  1. Reconstructing the dimer structure using true structure

python ./scripts/true_structure/dqn_docking.py <initial_pdb> <native_strcuture>

  1. Reconstructing the dimer structure using true/predicted contacts

python ./scripts/predicted_contacts/dqn_docking.py <path_to_the_DeepRLP_tool> <initial_start> <res_file> <out_dir> <target_name>

โ€ƒ

A video demonstrating how DRLComplex reconstructs the dimer structure using true interchain contacts:

drl_final_rewards_faster.mp4

drlcomplex's People

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es15326 avatar jianlin-cheng avatar zhenpingli avatar

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