GeoPacker

GeoPacker is a tool package using a simplified geometric deep learning coupled ResNet for protein side-chain modeling. Particularly, GeoPacker overcomes the limitation of large-scale rotamer-free protein sequence design due to the admirable efficiency and accuracy.

The dependent packages for GeoPacker are listed in the requirement.txt.

INSTALLATION

1. Users can download it by git clone https://github.com/PKUliujl/GeoPacker.git (without pretrained model's parameters in the model directory due to the large size), alternatively, it is available to access our disk with Access Code MBYd to get these files;
2. Modify the PATH of python interpreter in the first line in run_GeoPacker.py;
3. chmod u+x run_GeoPacker.py;
4. Add the directory PATH including run_GeoPacker.py to your environment PATH, and then type/run run_GeoPacker.py in any directory for friendly usage.

Before using GeoPacker, please check whether the dependent packages are available in your environment (see requirement.txt). If not, using pip or conda to install them.

USAGE

usage: run_GeoPacker.py [-h] [--purpose {0,1}] [--model_identity {pdb30,pdb60}] [--inputPATH INPUTPATH] --inputfile INPUTFILE --pdbname PDBNAME  
                        --chainID CHAINID [--seqfile SEQFILE] [--outputfile OUTPUTFILE] [--outputPATH OUTPUTPATH]  

To better use GeoPacker for protein side-chain modeling, please add some of these parameters  

optional arguments:  
    -h, --help            show this help message and exit  
    --purpose {0,1}       0 for repacking while 1 for designed sequence. default: 0
    --model_identity {pdb30,pdb60}
                          model trained on different pair-wise sequence identity dataset. default: pdb60
    --inputPATH INPUTPATH, -iP INPUTPATH    
                          the directory path containing the pdb file. default: './'  
    --inputfile INPUTFILE, -i INPUTFILE  
                          a pdb file under inputPATH, eg. 1a12.pdb/1a12_A.pdb  
    --pdbname PDBNAME     a protein name, eg. 1A12/1a12  
    --chainID CHAINID     a protein chain to be packed, eg. A  
    --seqfile SEQFILE     a fasta format file including the sequences to be designed  
    --outputPATH OUTPUTPATH, -oP OUTPUTPATH  
                          the directory path of the outputfile. default: inputPATH
    --outputfile OUTPUTFILE, -o OUTPUTFILE  
                          the name of output file. default: pdbname_chainID_repacked.pdb for repacking 
                          and pdbname_chainID_design.pdb for design
  

EXAMPLE

For repacking,

      run_GeoPacker.py --inputPATH example/ -i 3MPC_A.pdb --pdbname 3MPC  --chainID A   

For design,

      run_GeoPacker.py --purpose 1 --inputPATH example/ -i 3MPC_A.pdb --pdbname 3MPC --chainID A --seqfile  example/seqfile

Attention, do not use following commands for design, otherwise, error will be reported:

      run_GeoPacker.py --purpose 1 --inputPATH example/ -i example/3MPC_A.pdb --pdbname 3MPC --chainID A --seqfile  example/seqfile
      run_GeoPacker.py --purpose 1 --inputPATH example/ -i 3MPC_A.pdb --pdbname 3MPC --chainID A --seqfile  seqfile
      run_GeoPacker.py --purpose 1  -i example/3MPC_A.pdb --pdbname 3MPC --chainID A --seqfile  example/seqfile

To rebuild pseudo CB atoms given protein backbone atoms (i.e. C, N, O, CA),

      run_CBbuilder.py Inputfile(pdb format) chainID Outputfile(pdb format)

An example to rebuild pseudo CB atoms:

      run_CBbuilder.py example/3MPC_A.pdb A example/3MPC_A.CB.pdb

Reminder: Only the regular pdb format files are accepted as inputs.

Feel free to contact me via email at liujl@stu.pku.edu.cn for other issues.

ACKNOWLEDGEMENT

A part of the code used to reconstruct the side chain atomic coordinates were taken from PeptideBuilder and opus-rota4 and modified to meet our requirements.

CITATION

If you find GeoPacker useful in your research, please cite it:

@article{liu2022geopacker,
  title={GeoPacker: a novel deep learning framework for protein side-chain modeling},
  author={Liu, Jiale and Zhang, Changsheng and Lai, Luhua},
  journal={Protein Science},
  pages={e4484},
  year={2022},
  publisher={Wiley Online Library}
}