DeepDrugV

DeepDrugV constructs the voronoi diagram (VD) of protein binding site/pocket or ligand structure based on the 3D or 2D coordinate structure.

Requirements

1. Python 2.7+
2. numpy 1.14+
3. scipy 0.18+
4. Pandas 0.19+
5. scikit-spatial 0.12.0
6. matplotlib 2.0.2+
7. biopandas ; eg : pip/conda install biopandas

Getting started

1. copy/download the code from GitHub
2. If input is a 3D coordinate of protein/ligand, it will be projected to 2D plane employing perspective projection: Px= x/1-z, Py= y/1-z
3. Run deepdrugV.py with a .mol2 file (see Examples)

Examples

create a 2D image using mol2 file in 2D or 3D format

python deepdrugV.py -mol input.mol2 -out output.jpg -dpi integer 

-mol stands for the receptor, protein or ligand (MUST BE in a mol2 format)
-out is the name of the output file [OPTION](default is jpg format)
-dpi is the desired image quality [OPTION](default 120 dpi in 2.7 x 2.7 = 256 x 256 px)

creating a 2D image of voronoi using protein pocket file in mol2 3D format

python deepdrugV.py -mol 4v94E.mol2 -out Voronoi_2D_4v94E.jpg -dpi 120   

Voronoi image of ATP-binding site protein pocket colored by atom types:

chaperonin (4v94, chain E)

Contributors:

Rajiv Gandhi Govindaraj, Jeffrey Lemoine, Limeng Pu, and Michal Brylinski. "DeepDrugV"