Computational study on peptidomimetic inhibitors against SARS-CoV-2 main protease

The emergence outbreak caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has received significant attention on the global risks. Due to itscrucial role in viral replication, the main protease 3CL(pro) is an important target for drug discovery and development to combat CO...

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Main Authors: Somboon, Tuanjai, Mahalapbutr, Panupong, Sanachai, Kamonpan, Maitarad, Phornphimon, Lee, Vannajan Sanghiran, Hannongbua, Supot, Rungrotmongkol, Thanyada
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Published: Elsevier 2021
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spelling my.um.eprints.286362022-03-30T08:06:48Z http://eprints.um.edu.my/28636/ Computational study on peptidomimetic inhibitors against SARS-CoV-2 main protease Somboon, Tuanjai Mahalapbutr, Panupong Sanachai, Kamonpan Maitarad, Phornphimon Lee, Vannajan Sanghiran Hannongbua, Supot Rungrotmongkol, Thanyada QC Physics QD Chemistry The emergence outbreak caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has received significant attention on the global risks. Due to itscrucial role in viral replication, the main protease 3CL(pro) is an important target for drug discovery and development to combat COVID-19. In this work, the structural and dynamic behaviors as well as binding efficiency of the four peptidomimetic inhibitors (N3, 11a, 13b, and 14b) recently co-crystalized with SARS-CoV-2 3CL(pro) were studied and compared using all-atom molecular dynamics (MD) simulations and solvated interaction energy-based binding free energy calculations. The per-residue decomposition free energy results suggested that the key residues involved in inhibitors binding were H41, M49, L141-C145, H163-E166, P168, and Q189-T190 in the domains I and II. The van der Waals interaction yielded the main energy contribution stabilizing all the focused inhibitors. Besides, their hydrogen bond formations with F140, G143, C145, H164, E166, and Q189 residues in the substrate-binding pocket were also essential for strengthening the molecular complexation. The predicted binding affinity of the four peptidomimetic inhibitors agreed with the reported experimental data, and the 13b showed the most efficient binding to SARS-CoV-2 3CL(pro). From rational drug design strategies based on 13b, the polar moieties (e.g., benzamide) and the bulky N-terminal protecting groups (e.g, thiazole) should be introduced to P1' and P4 sites in order to enhance H-bonds and hydrophobic interactions, respectively. We hope that the obtained structural and energetic information could be beneficial for developing novel SARS-CoV-2 3CL(pro) inhibitors with higher inhibitory potency to combat COVID-19. (C) 2020 Elsevier B.V. All rights reserved. Elsevier 2021 Article PeerReviewed Somboon, Tuanjai and Mahalapbutr, Panupong and Sanachai, Kamonpan and Maitarad, Phornphimon and Lee, Vannajan Sanghiran and Hannongbua, Supot and Rungrotmongkol, Thanyada (2021) Computational study on peptidomimetic inhibitors against SARS-CoV-2 main protease. Journal of Molecular Liquids, 322. ISSN 0167-7322, DOI https://doi.org/10.1016/j.molliq.2020.114999 <https://doi.org/10.1016/j.molliq.2020.114999>. 10.1016/j.molliq.2020.114999
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic QC Physics
QD Chemistry
spellingShingle QC Physics
QD Chemistry
Somboon, Tuanjai
Mahalapbutr, Panupong
Sanachai, Kamonpan
Maitarad, Phornphimon
Lee, Vannajan Sanghiran
Hannongbua, Supot
Rungrotmongkol, Thanyada
Computational study on peptidomimetic inhibitors against SARS-CoV-2 main protease
description The emergence outbreak caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has received significant attention on the global risks. Due to itscrucial role in viral replication, the main protease 3CL(pro) is an important target for drug discovery and development to combat COVID-19. In this work, the structural and dynamic behaviors as well as binding efficiency of the four peptidomimetic inhibitors (N3, 11a, 13b, and 14b) recently co-crystalized with SARS-CoV-2 3CL(pro) were studied and compared using all-atom molecular dynamics (MD) simulations and solvated interaction energy-based binding free energy calculations. The per-residue decomposition free energy results suggested that the key residues involved in inhibitors binding were H41, M49, L141-C145, H163-E166, P168, and Q189-T190 in the domains I and II. The van der Waals interaction yielded the main energy contribution stabilizing all the focused inhibitors. Besides, their hydrogen bond formations with F140, G143, C145, H164, E166, and Q189 residues in the substrate-binding pocket were also essential for strengthening the molecular complexation. The predicted binding affinity of the four peptidomimetic inhibitors agreed with the reported experimental data, and the 13b showed the most efficient binding to SARS-CoV-2 3CL(pro). From rational drug design strategies based on 13b, the polar moieties (e.g., benzamide) and the bulky N-terminal protecting groups (e.g, thiazole) should be introduced to P1' and P4 sites in order to enhance H-bonds and hydrophobic interactions, respectively. We hope that the obtained structural and energetic information could be beneficial for developing novel SARS-CoV-2 3CL(pro) inhibitors with higher inhibitory potency to combat COVID-19. (C) 2020 Elsevier B.V. All rights reserved.
format Article
author Somboon, Tuanjai
Mahalapbutr, Panupong
Sanachai, Kamonpan
Maitarad, Phornphimon
Lee, Vannajan Sanghiran
Hannongbua, Supot
Rungrotmongkol, Thanyada
author_facet Somboon, Tuanjai
Mahalapbutr, Panupong
Sanachai, Kamonpan
Maitarad, Phornphimon
Lee, Vannajan Sanghiran
Hannongbua, Supot
Rungrotmongkol, Thanyada
author_sort Somboon, Tuanjai
title Computational study on peptidomimetic inhibitors against SARS-CoV-2 main protease
title_short Computational study on peptidomimetic inhibitors against SARS-CoV-2 main protease
title_full Computational study on peptidomimetic inhibitors against SARS-CoV-2 main protease
title_fullStr Computational study on peptidomimetic inhibitors against SARS-CoV-2 main protease
title_full_unstemmed Computational study on peptidomimetic inhibitors against SARS-CoV-2 main protease
title_sort computational study on peptidomimetic inhibitors against sars-cov-2 main protease
publisher Elsevier
publishDate 2021
url http://eprints.um.edu.my/28636/
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score 13.15806