Statine-based peptidomimetics as SARS-CoV-2 Papain-like protease inhibitors: in Silico and in vitro studies

We investigated statin-based peptidomimetic compounds as inhibitors of SARS-CoV-2 papain-like protease (PLpro) by in silico methods, including molecular docking/dynamic simulations and ADMET prediction, as well as enzymatic in vitro assays. Five compounds (LQMed 426, 428, 430, 431, and 432) were identified as having promising interactions with the active site and an allosteric site of PLpro. The docking poses in the active site revealed that the compounds interacted with the catalytic triad (Cys111, His272, and Asp286). Compound 426 stood out for forming significant hydrophobic interactions and hydrogen bonds. In molecular dynamic (MD) simulations, there was a tendency for the compounds to migrate to a pocket in the ubiquitin-like (Ubl) domain region, indicating possible allosteric inhibition. Principal component analysis (PCA) and free energy landscape (FEL) plot showed significant differences in the conformational stability of protein-ligand complexes. Complex 432 had the highest stability (PC1: 24.9%, PC2: 10.5%) with restricted movements, while complex 430 had the lowest stability and the highest PC1, indicating broader movements. Complexes 426 and 428 had intermediate stability. FEL analysis confirmed that complex 432 had multiple minimum energy clusters, suggesting a greater likelihood of stable enzyme-ligand complex. In vitro assays demonstrated that all compounds inhibited PLpro activity by at least 50%, with IC<sub>50</sub> values ranging from 0.85 µM to 4.06 µM. Compounds 426 and 432 were the most promising, with IC<sub>50</sub> of 0.85 µM and 1.46 µM, respectively, values comparable to the GRL-0617 reference inhibitor. Binding free energy analysis indicated that compounds 430 and 431 showed significant affinity for the allosteric site (-27 kcal/mol and - 14 kcal/mol, respectively), while compound 428 showed reduced stability. In addition, in silico pharmacokinetics and toxicity (ADMET) prediction revealed that statine-based compounds are promising compared to GRL-0617 due to the low potential of inhibition of CYP's family and toxicity risk. Overall, the tested compounds, especially 426 and 432, showed potential as inhibitors of SARS-CoV-2 PLpro and may act by non-competitive or mixed mechanisms, making them promising candidates for developing antivirals against CoViD-19.

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Journal
Scientific Reports
Published
2025-07-20
DOI
https://doi.org/10.1038/s41598-025-11599-2
Citations
2
Primary Topic
Computational Drug Discovery Methods
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article
Field-Weighted Citation Impact
3.01

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article

Statine-based peptidomimetics as SARS-CoV-2 Papain-like protease inhibitors: in Silico and in vitro studies

Priscila Goes Camargo, Luiza R.S. Dias, Larissa Esteves Carvalho Constant, Carlos Rangel Rodrigues et al.
2 citations
Scientific Reports
Computational Drug Discovery Methods
3.01
article

Statine-based peptidomimetics as SARS-CoV-2 Papain-like protease inhibitors: in Silico and in vitro studies

Priscila Goes Camargo, Luiza R.S. Dias, Larissa Esteves Carvalho Constant, Carlos Rangel Rodrigues, Pedro Henrique Rodrigues de Alencar Azevedo, Magaly Girão Albuquerque, Diego Allonso, Camilo Henrique da Silva Lima, Estela M.F. Muri, R Pimentel, Samya Ali Abdel Fattah Costa
article en
2 citations

Abstract

We investigated statin-based peptidomimetic compounds as inhibitors of SARS-CoV-2 papain-like protease (PLpro) by in silico methods, including molecular docking/dynamic simulations and ADMET prediction, as well as enzymatic in vitro assays. Five compounds (LQMed 426, 428, 430, 431, and 432) were identified as having promising interactions with the active site and an allosteric site of PLpro. The docking poses in the active site revealed that the compounds interacted with the catalytic triad (Cys111, His272, and Asp286). Compound 426 stood out for forming significant hydrophobic interactions and hydrogen bonds. In molecular dynamic (MD) simulations, there was a tendency for the compounds to migrate to a pocket in the ubiquitin-like (Ubl) domain region, indicating possible allosteric inhibition. Principal component analysis (PCA) and free energy landscape (FEL) plot showed significant differences in the conformational stability of protein-ligand complexes. Complex 432 had the highest stability (PC1: 24.9%, PC2: 10.5%) with restricted movements, while complex 430 had the lowest stability and the highest PC1, indicating broader movements. Complexes 426 and 428 had intermediate stability. FEL analysis confirmed that complex 432 had multiple minimum energy clusters, suggesting a greater likelihood of stable enzyme-ligand complex. In vitro assays demonstrated that all compounds inhibited PLpro activity by at least 50%, with IC<sub>50</sub> values ranging from 0.85 µM to 4.06 µM. Compounds 426 and 432 were the most promising, with IC<sub>50</sub> of 0.85 µM and 1.46 µM, respectively, values comparable to the GRL-0617 reference inhibitor. Binding free energy analysis indicated that compounds 430 and 431 showed significant affinity for the allosteric site (-27 kcal/mol and - 14 kcal/mol, respectively), while compound 428 showed reduced stability. In addition, in silico pharmacokinetics and toxicity (ADMET) prediction revealed that statine-based compounds are promising compared to GRL-0617 due to the low potential of inhibition of CYP's family and toxicity risk. Overall, the tested compounds, especially 426 and 432, showed potential as inhibitors of SARS-CoV-2 PLpro and may act by non-competitive or mixed mechanisms, making them promising candidates for developing antivirals against CoViD-19.

Scientific ReportsVol. 15(1)
Universidade Federal do Rio de Janeiro (BR), Universidade Federal Fluminense (BR), Czech Academy of Sciences, Institute of Biophysics (CZ)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Centro Nacional de Processamento de Alto Desempenho em São Paulo
Clean water and sanitation
Openalex Percentile: Top 8%
Computational Drug Discovery Methods
3.01
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