Mechanistic insights into the noncovalent inhibition of SARS-CoV-2 PLpro: a multiscale computational study

The papain-like protease of SARS-CoV-2 (PLpro2) is integral to viral polyprotein cleavage and the modulation of host immune responses, positioning it as a critical target for antiviral drug development. Here, we elucidate the molecular mechanisms governing the noncovalent inhibition of PLpro2 through a comprehensive computational approach, including molecular docking, extensive molecular dynamics (MD) simulations, binding free energy calculations (MM/GBSA and SIE), principal component and free energy landscape (PCA/FEL) analyses, and protein-ligand interaction fingerprinting (ProLIF). We assessed a structurally diverse set of noncovalent inhibitors for their capacity to induce conformational rearrangements and stabilize key structural motifs of PLpro2, with particular emphasis on the BL2 loop. Notably, XR3 and A19 exhibited superior experimental and predicted binding affinities, which can be attributed to favorable contacts with essential residues Tyr268 and Gln269, the attenuation of loop dynamics, and the stabilization of energetically favorable conformational states. By contrast, less potent inhibitors were associated with increased conformational heterogeneity, fragmented free energy landscapes, and diminished interactions with critical loop residues. Therefore, our integrative analysis delineates the structural and energetic determinants underpinning noncovalent PLpro2 inhibition, underscoring the central roles of loop immobilization and π-stacking interactions in the rational design of next-generation PLpro2 inhibitors.

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Publication Details

Journal
Journal of Computer-Aided Molecular Design
Published
2026-02-05
DOI
https://doi.org/10.1007/s10822-026-00763-z
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
45.17

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article

Mechanistic insights into the noncovalent inhibition of SARS-CoV-2 PLpro: a multiscale computational study

Jéssica de Oliveira Araújo, Renan Patrick da Penha Valente, Hendrik Gerhardus Kruger, Flávio Vinícius da Silva Ribeiro et al.
1 citations
Journal of Computer-Aided Molecular Design
Computational Drug Discovery Methods
45.17
article

Mechanistic insights into the noncovalent inhibition of SARS-CoV-2 PLpro: a multiscale computational study

Jéssica de Oliveira Araújo, Renan Patrick da Penha Valente, Hendrik Gerhardus Kruger, Flávio Vinícius da Silva Ribeiro, José Rogério A. Silva
article en
1 citations

Abstract

The papain-like protease of SARS-CoV-2 (PLpro2) is integral to viral polyprotein cleavage and the modulation of host immune responses, positioning it as a critical target for antiviral drug development. Here, we elucidate the molecular mechanisms governing the noncovalent inhibition of PLpro2 through a comprehensive computational approach, including molecular docking, extensive molecular dynamics (MD) simulations, binding free energy calculations (MM/GBSA and SIE), principal component and free energy landscape (PCA/FEL) analyses, and protein-ligand interaction fingerprinting (ProLIF). We assessed a structurally diverse set of noncovalent inhibitors for their capacity to induce conformational rearrangements and stabilize key structural motifs of PLpro2, with particular emphasis on the BL2 loop. Notably, XR3 and A19 exhibited superior experimental and predicted binding affinities, which can be attributed to favorable contacts with essential residues Tyr268 and Gln269, the attenuation of loop dynamics, and the stabilization of energetically favorable conformational states. By contrast, less potent inhibitors were associated with increased conformational heterogeneity, fragmented free energy landscapes, and diminished interactions with critical loop residues. Therefore, our integrative analysis delineates the structural and energetic determinants underpinning noncovalent PLpro2 inhibition, underscoring the central roles of loop immobilization and π-stacking interactions in the rational design of next-generation PLpro2 inhibitors.

Journal of Computer-Aided Molecular DesignVol. 40(1)
Universidade Estadual de Campinas (UNICAMP) (BR), Instituto Federal de Educação, Ciência e Tecnologia do Pará (BR), Universidade Federal do Pará (BR), University of KwaZulu-Natal (ZA)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Affordable and clean energy
Openalex Percentile: Top 1%
Computational Drug Discovery Methods
45.17
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