Requirements [Libraries]:- 

pandas==1.0.1
numpy 
matplotlib
scikit-learn
seaborn


The .py file should be be placed in a working folder and executed in python 3 environment. 
The program is expected to run for a few hours with variation based on Internet speed and CPU speed. 
Strong Internet connection is mandatory for a successful run. 
The Final Output in the end is top 30 drug leads identified with PubChem CIDs.

The dependency packages for running the automated virtual screening part of the Code involves the following


openbabel 2.4.1 
mgltools  1.5.4
autodock-vina 1.1.2-4

Since autodock-vina can only be programmatically accessed in a Linux environment, this requires this part of the code be run in 
a Linux OS

While compiling the program from the working directory files to be kept in the working directory are the following 

configCLpro.txt
configPLpro.txt
1p9u.pdbqt
6w9c.pdbqt

They can be doownloaded from this GitHub Repository