RUS  ENG
Full version
JOURNALS // Matematicheskaya Biologiya i Bioinformatika // Archive

Mat. Biolog. Bioinform., 2023 Volume 18, Issue 1, Pages 15–32 (Mi mbb506)

This article is cited in 1 paper

Bioinformatics

Application of virtual screening and molecular modeling technologies to identify potential SARS-CoV-2 main protease inhibitors

A. M. Andrianova, K. V. Fursb, A. V. Goncharb, L. H. Aslanyanc, A. V. Tuzikovb

a Institute of Bioorganic Chemistry, National Academy of Sciences of Belarus, Minsk, Republic of Belarus
b United Institute of Informatics Problems, National Academy of Sciences of Belarus, Minsk, Republic of Belarus
c Institute for Informatics and Automation Problems of National Academy of Sciences of Republic of Armenia, Yerevan, Armenia

Abstract: A virtual screening of the molecular library of biologically active compounds was carried out to identify potential inhibitors of SARS-CoV-2 main protease (Mpro) which plays an important role in the process of virus replication. Using molecular docking and molecular dynamics, the binding energy of these compounds to the catalytic site of the enzyme was assessed, resulting in six molecules that exhibited high chemical affinity for SARS-CoV-2 Mpro. This is evidenced by the low values of the binding free energy of the ligand/Mpro complexes comparable with those predicted for the potent non-covalent SARSCoV-2 Mpro inhibitor using the identical computational protocol. Based on the data obtained, it was concluded that the identified compounds have a good therapeutic potential for inhibiting the catalytic activity of the enzyme and form promising basic structures for the development of new effective drugs against COVID-19.

Key words: SARS-CoV-2, main protease, virtual screening, molecular docking, molecular dynamics, antiviral drugs.

Received 27.01.2023, 12.02.2023, Published 22.02.2023

DOI: 10.17537/2023.18.15



© Steklov Math. Inst. of RAS, 2024