COVID 19 SARS COV2 targets and small molecule data including insilico analysis

Welcome to the repository for the COVID-19 research data.

Corresponding Author: Girinath G. Pillai and few experts

Co-authors: Team of experts, scholars and students

To join dedicated Slack Discussion : https://join.slack.com/t/nyroindia/shared_invite/zt-ejes216c-QZzEK_G5tNKIjewbVj2IPA

We commit to conduct research analysis and all the findings and data will be open and anyone can use or help us improve the data.

The parameters for checkpoints are:

A) Pharmacophore Modelling - i) generate pharmacophore reference maps from XRay crystal geometry, ii) Generate all possible conformers of the dataset molecules for screening.

B) Virtual Screening - i) highest docking score within the dataset, ii) lowest clashes (interligand or intraligand), iii) interactions with key amino acid residues based on literature reports, PROSITE server and pocket finding algorithm like DoGSite or CASTp iv) optimal LE values and v) satisfactory interactions between small molecules and amino acids.

C) Selection - i) binding affinity range predictions, lowest among the dataset, ii) free binding energy calculation considering desolvation terms, lowest among the dataset and iii) torsion analysis - coverage of bonds in CSD database.

D) Optimization - i) pharmacokinetic properties to be generated from selected hits and an optimal balance of properties to be considered for candidate selection criteria.

E) For novel lead molecules - i) chemical space exploration on building blocks could be carried out, ii) on-demand synthesis and procurement.

If you prefer you could always cite https://github.com/giribio/COVID19

Feel free to create any issues in Github or feel free to contact me via Slack for any queries.

Thanks and let us fight against COVID-19 in all possible ways.