In-silico screening for identification of potential inhibitors against SARS-CoV-2 transmembrane serine protease 2 (TMPRSS2)

Abstract

A new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a respiratory infection out broke in December 2019 in Wuhan, Hubei province, China, resulted in pandemic conditions worldwide. COVID-19 spread swiftly around the world over with an alert of an emergency for an adequate drug. Therefore, in this research, we repurposed the FDA-approved medicines to find the prominent drug used to cure the COVID infected patients. We performed homology modeling of the transmembrane serine protease 2 (TMPRSS2), responsible for the viral entry. The prediction of the transmembrane region and the Conserved Domain in TMPRSS2 protein was made for docking. 4182 FDA-approved compounds from the ZINC database were downloaded and used for the calculation of physicochemical properties. Two thousand eight hundred fifteen screened compounds were used for molecular docking against the modelled protein structure. From which top hit compounds based on binding energy were extracted. At 1^st site pose, ZINC3830554 showed the highest binding energy -12.91kcal/mol by forming Salt Bridge at LYS143, Hydrogen bond at ALA8, VAL45, HIS47, SER142, ASN277, ASN359, and TRP363. The hydrophobic Interactions at PHE3, LEU4, ALA7, ALA8, ALA139, PRO197, and PHE266. In the 2^nd site pose, ZINC203686879 shows the highest binding energy (-12.56 kcal/mol) and forms a hydrophobic interaction with VAL187, VAL189, HIS205, LYS301, GLN347, TRP370 and hydrogen bond was at GLY300, THR302, GLN347, SER350 residues. These hit compounds were subjected to stability checks between the protein-ligand complex through the dynamics simulation (MD), and binding free energy was calculated through the Molecular Mechanics energies combined with Poisson-Boltzmann (MM/PBSA) method. We hope that hit compounds would be an efficient inhibitor that can block the TMPRSS2 activity and resist the entry of the SARS-CoV-2 virus into targeted human cells by reducing the virus's infectivity and transmissibility.

Keywords: Drug repositioning; Molecular Docking; SARS-CoV-2; Transmembrane serine protease 2; Virtual screening.

Graphical abstract

Fig. 1

Description of the In-silico virtual screening workflow of the iterative process to find a potent inhibitor for TMPRSS2.

Fig. 2

Binding pocket site (A.) showing 1st site on pocket 1, pocket two found in Metapocket tool, and 2^nd site is substrate binding site & Triad of the active catalytic site (B.) The amino acid present in the 2nd site is the substrate binding site (Yellow color) and the Triad of the active catalytic site (Magenta color).

Fig. 3

Screened virtual hit compounds binding in selected 1^st site on pocket 1, pocket two and 2^nd site are substrate binding sites and Triad of the active catalytic site.

Fig. 4

(A) Three clusters were formed by hit compounds found in the 1^st site and (B) Two clusters were formed by hit compounds found in the 2^nd site based on the Hierarchical Clustering method.

Fig. 5

RMSD for protein and selected hit compounds for 20ns MD simulation. (A) RMSD for hit compounds found in 1st site and (B) RMSD for hit compounds found in 2nd site.