Tags

Type your tag names separated by a space and hit enter

Computational discovery of small drug-like compounds as potential inhibitors of SARS-CoV-2 main protease.
J Biomol Struct Dyn. 2020 Jul 14 [Online ahead of print]JB

Abstract

A computational approach to in silico drug discovery was carried out to identify small drug-like compounds able to show structural and functional mimicry of the high affinity ligand X77, potent non-covalent inhibitor of SARS-COV-2 main protease (MPro). In doing so, the X77-mimetic candidates were predicted based on the crystal X77-MPro structure by a public web-oriented virtual screening platform Pharmit. Models of these candidates bound to SARS-COV-2 MPro were generated by molecular docking, quantum chemical calculations and molecular dynamics simulations. At the final point, analysis of the interaction modes of the identified compounds with MPro and prediction of their binding affinity were carried out. Calculation revealed 5 top-ranking compounds that exhibited a high affinity to the active site of SARS-CoV-2 MPro. Insights into the ligand - MPro models indicate that all identified compounds may effectively block the binding pocket of SARS-CoV-2 MPro, in line with the low values ​​of binding free energy and dissociation constant. Mechanism of binding of these compounds to MPro is mainly provided by van der Waals interactions with the functionally important residues of the enzyme, such as His-41, Met-49, Cys-145, Met-165, and Gln-189 that play a role of the binding hot spots assisting the predicted molecules to effectively interact with the MPro active site. The data obtained show that the identified X77-mimetic candidates may serve as good scaffolds for the design of novel antiviral agents able to target the active site of SARS-CoV-2 MPro. Communicated by Ramaswamy H. Sarma.

Authors+Show Affiliations

Institute of Bioorganic Chemistry, National Academy of Sciences of Belarus, Minsk, Republic of Belarus.Institute of Bioorganic Chemistry, National Academy of Sciences of Belarus, Minsk, Republic of Belarus.United Institute of Informatics Problems, National Academy of Sciences of Belarus, Minsk, Republic of Belarus.United Institute of Informatics Problems, National Academy of Sciences of Belarus, Minsk, Republic of Belarus.United Institute of Informatics Problems, National Academy of Sciences of Belarus, Minsk, Republic of Belarus.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32662333

Citation

Andrianov, Alexander M., et al. "Computational Discovery of Small Drug-like Compounds as Potential Inhibitors of SARS-CoV-2 Main Protease." Journal of Biomolecular Structure & Dynamics, 2020, pp. 1-13.
Andrianov AM, Kornoushenko YV, Karpenko AD, et al. Computational discovery of small drug-like compounds as potential inhibitors of SARS-CoV-2 main protease. J Biomol Struct Dyn. 2020.
Andrianov, A. M., Kornoushenko, Y. V., Karpenko, A. D., Bosko, I. P., & Tuzikov, A. V. (2020). Computational discovery of small drug-like compounds as potential inhibitors of SARS-CoV-2 main protease. Journal of Biomolecular Structure & Dynamics, 1-13. https://doi.org/10.1080/07391102.2020.1792989
Andrianov AM, et al. Computational Discovery of Small Drug-like Compounds as Potential Inhibitors of SARS-CoV-2 Main Protease. J Biomol Struct Dyn. 2020 Jul 14;1-13. PubMed PMID: 32662333.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Computational discovery of small drug-like compounds as potential inhibitors of SARS-CoV-2 main protease. AU - Andrianov,Alexander M, AU - Kornoushenko,Yuri V, AU - Karpenko,Anna D, AU - Bosko,Ivan P, AU - Tuzikov,Alexander V, Y1 - 2020/07/14/ PY - 2020/7/15/entrez PY - 2020/7/15/pubmed PY - 2020/7/15/medline KW - COVID-19 KW - Coronavirus SARS-CoV-2 KW - SARS-CoV-2 inhibitors KW - antiviral drugs KW - main protease KW - molecular docking KW - quantum chemical calculations KW - virtual screening SP - 1 EP - 13 JF - Journal of biomolecular structure & dynamics JO - J. Biomol. Struct. Dyn. N2 - A computational approach to in silico drug discovery was carried out to identify small drug-like compounds able to show structural and functional mimicry of the high affinity ligand X77, potent non-covalent inhibitor of SARS-COV-2 main protease (MPro). In doing so, the X77-mimetic candidates were predicted based on the crystal X77-MPro structure by a public web-oriented virtual screening platform Pharmit. Models of these candidates bound to SARS-COV-2 MPro were generated by molecular docking, quantum chemical calculations and molecular dynamics simulations. At the final point, analysis of the interaction modes of the identified compounds with MPro and prediction of their binding affinity were carried out. Calculation revealed 5 top-ranking compounds that exhibited a high affinity to the active site of SARS-CoV-2 MPro. Insights into the ligand - MPro models indicate that all identified compounds may effectively block the binding pocket of SARS-CoV-2 MPro, in line with the low values ​​of binding free energy and dissociation constant. Mechanism of binding of these compounds to MPro is mainly provided by van der Waals interactions with the functionally important residues of the enzyme, such as His-41, Met-49, Cys-145, Met-165, and Gln-189 that play a role of the binding hot spots assisting the predicted molecules to effectively interact with the MPro active site. The data obtained show that the identified X77-mimetic candidates may serve as good scaffolds for the design of novel antiviral agents able to target the active site of SARS-CoV-2 MPro. Communicated by Ramaswamy H. Sarma. SN - 1538-0254 UR - https://www.unboundmedicine.com/medline/citation/32662333/Computational_discovery_of_small_drug_like_compounds_as_potential_inhibitors_of_SARS_CoV_2_main_protease_ L2 - http://www.tandfonline.com/doi/full/10.1080/07391102.2020.1792989 DB - PRIME DP - Unbound Medicine ER -
Try the Free App:
Prime PubMed app for iOS iPhone iPad
Prime PubMed app for Android
Prime PubMed is provided
free to individuals by:
Unbound Medicine.