Multi-Site Targeting Potential of 3CLpro Inhibitors: Unveiling Diverse Mechanisms Through Blind Docking and Brownian Dynamics Simulations

Objectives The objective of this study is to employ an integrated computational approach, combining blind ligand docking and Brownian Dynamics (BD) simulations, to elucidate the detailed inhibition mechanisms of the SARS-CoV-2 main protease (3CLpro), a critical enzyme for viral replication and a primary target for developing antiviral drugs, whose detailed inhibition mechanisms are yet to be fully elucidated. Material and Methods The methodology involved screening the ChEMBL database to identify seventy-three inhibitors of the 3CLpro enzyme, followed by blind docking to reveal potential binding sites on the 3CLpro monomer. Subsequently, structural analysis of the identified sites was performed to pinpoint key residues involved in functional aspects such as substrate binding, catalysis, and dimer stability. Finally, Brownian Dynamics (BD) simulations were carried out on 3CLpro monomers with an inhibitor bound at the identified sites to quantify the effect on the enzyme’s diffusional association rate constant and the structure of the encounter complex relative to the wild-type monomer. Results The screening and docking process successfully identified seven distinct clusters of ligand poses (binding sites) on the 3CLpro monomer, each consistently populated by at least 77% of the seventy-three identified inhibitors. Structural analysis of these sites identified key functional residues, including GLN110, MET165, GLU270 (substrate binding), CYS145, SER121 (catalysis), and THR292, GLY109, LYS5 (dimer stability), which functionally revealed four distinct inhibitory mechanisms: dimer interface disruption (sites 2, 3, and 7), direct active site inhibition (site 4), substrate exclusion (sites 1, 3, 5, and 6), and allosteric modulation (sites 1 and 7). Furthermore, BD simulations demonstrated that inhibitor binding at any of the seven sites resulted in ∼50% decrease in the diffusional association rate constant, a reduction in the radial distribution maxima, and a disruption of the encounter complex structure compared with the wild-type, strongly indicating that the modulation of 3CLpro association is primarily attributable to kinetic factors. Conclusion In conclusion, these integrated structural and dynamical insights provide a comprehensive and valuable framework for the rational design of effective 3CLpro inhibitors that can target multiple functional aspects of the enzyme simultaneously, thereby moving beyond the conventional, often simplistic, approach of inhibiting a single active site.

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Journal
JOURNAL of QASSIM UNIVERSITY FOR SCIENCE
Published
2025-12-24
DOI
https://doi.org/10.25259/jqus_21_2025
Primary Topic
Computational Drug Discovery Methods
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article
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article

Multi-Site Targeting Potential of 3CLpro Inhibitors: Unveiling Diverse Mechanisms Through Blind Docking and Brownian Dynamics Simulations

Karim M. ElSawy
JOURNAL of QASSIM UNIVERSITY FOR SCIENCE
Computational Drug Discovery Methods
article

Multi-Site Targeting Potential of 3CLpro Inhibitors: Unveiling Diverse Mechanisms Through Blind Docking and Brownian Dynamics Simulations

Karim M. ElSawy
article en

Abstract

Objectives The objective of this study is to employ an integrated computational approach, combining blind ligand docking and Brownian Dynamics (BD) simulations, to elucidate the detailed inhibition mechanisms of the SARS-CoV-2 main protease (3CLpro), a critical enzyme for viral replication and a primary target for developing antiviral drugs, whose detailed inhibition mechanisms are yet to be fully elucidated. Material and Methods The methodology involved screening the ChEMBL database to identify seventy-three inhibitors of the 3CLpro enzyme, followed by blind docking to reveal potential binding sites on the 3CLpro monomer. Subsequently, structural analysis of the identified sites was performed to pinpoint key residues involved in functional aspects such as substrate binding, catalysis, and dimer stability. Finally, Brownian Dynamics (BD) simulations were carried out on 3CLpro monomers with an inhibitor bound at the identified sites to quantify the effect on the enzyme’s diffusional association rate constant and the structure of the encounter complex relative to the wild-type monomer. Results The screening and docking process successfully identified seven distinct clusters of ligand poses (binding sites) on the 3CLpro monomer, each consistently populated by at least 77% of the seventy-three identified inhibitors. Structural analysis of these sites identified key functional residues, including GLN110, MET165, GLU270 (substrate binding), CYS145, SER121 (catalysis), and THR292, GLY109, LYS5 (dimer stability), which functionally revealed four distinct inhibitory mechanisms: dimer interface disruption (sites 2, 3, and 7), direct active site inhibition (site 4), substrate exclusion (sites 1, 3, 5, and 6), and allosteric modulation (sites 1 and 7). Furthermore, BD simulations demonstrated that inhibitor binding at any of the seven sites resulted in ∼50% decrease in the diffusional association rate constant, a reduction in the radial distribution maxima, and a disruption of the encounter complex structure compared with the wild-type, strongly indicating that the modulation of 3CLpro association is primarily attributable to kinetic factors. Conclusion In conclusion, these integrated structural and dynamical insights provide a comprehensive and valuable framework for the rational design of effective 3CLpro inhibitors that can target multiple functional aspects of the enzyme simultaneously, thereby moving beyond the conventional, often simplistic, approach of inhibiting a single active site.

JOURNAL of QASSIM UNIVERSITY FOR SCIENCEVol. 5
Qassim University (SA)
Openalex Percentile: Top 28%
Computational Drug Discovery Methods
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