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A Python package to calculate pKa values for proteins

Project description

INSTALLATION (using PyPI)

Simply use the command pip install pkaani

INSTALLATION (from source code)

Navigate to this repository for the source code: https://github.com/isayevlab/pKa-ANI/tree/main

Prior to the installation of pKa-ANI, users should make sure they have installed conda.

To install pKa-ANI, navigate to the directory of the source that you've downloaded and;

conda env create -f pkaani_env.yaml

This will create a conda environment named pkaani and install all required packages. After the environment is created;

conda activate pkaani 
python setup.py install

PREREQUISITES:

  • miniconda/anaconda

If pkaani_env.yaml is not used, users should make sure the following packages are installed.

  • python=3.8
  • numpy
  • scipy
  • pytorch
  • torchani=2.2.0
  • scikit-learn=1.0.2
  • ase
  • joblib
  • ambertools
  • setuptools=58.2.0

Other libraries the system may require : os,math,sys,io,csv,getopt,shutil,urllib.request,warnings

USAGE

pKa-ANI requires PDB files to have H atoms that are added with default ionization states of residues: ASP, GLU, LYS, TYR, HIE.

Due to this reason, input PDB file(s) are prepared before the calculation of pKa values (output PDB file 'PDBID_pkaani.pdb').

We would like to warn users, that our models are trained to predict pKa values for apo-proteins. Due to this, any residue that is not an aminoacid is removed from PDB file(s) during the preparation.

Example command line usages:

  • If PDB file doesnt exist, it is downloaded and prepared for pKa calculations.
pkaani -i 1BNZ
      
pkaani -i 1BNZ.pdb
  • Multiple files can be given as inputs
pkaani -i 1BNZ,1E8L
  • If a specific directory is wanted:
pkaani -i path_to_file/1BNZ
      
pkaani -i path_to_file/1BNZ,path_to_file/1E8L

Arguments:

-h: Help

-i: Input files. Inputs can be given with or without file extension (.pdb). 
    If PDB file is under a specific directory (or will be downloaded) the path                 
    can also be given as path_to_file/PDBFILE. Multiple PDB files can be given 
    by using "," as separator (i.e. pkaani -i 1BNZ,1E8L).

CITATION

Gokcan, H.; Isayev, O. Prediction of Protein p K a with Representation Learning. Chem. Sci. 2022, 13 (8), 2462–2474. https://doi.org/10.1039/D1SC05610G.

LICENSING

Please read LICENSE file.

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