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
If pkaani_env.yaml
is not used, users should make sure the following packages are installed.
Other libraries the system may require : os,math,sys,io,csv,getopt,shutil,urllib.request,warnings
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.
pkaani -i 1BNZ
pkaani -i 1BNZ.pdb
pkaani -i 1BNZ,1E8L
pkaani -i path_to_file/1BNZ
pkaani -i path_to_file/1BNZ,path_to_file/1E8L
-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).
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.
Please read LICENSE file.