Machine learning-based QSAR and LB-PaCS-MD guided design of SARS-CoV-2 main protease inhibitors.
Bioorg Med Chem Lett
; 110: 129852, 2024 Sep 15.
Article
en En
| MEDLINE
| ID: mdl-38925524
ABSTRACT
The global outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 virus had led to profound respiratory health implications. This study focused on designing organoselenium-based inhibitors targeting the SARS-CoV-2 main protease (Mpro). The ligand-binding pathway sampling method based on parallel cascade selection molecular dynamics (LB-PaCS-MD) simulations was employed to elucidate plausible paths and conformations of ebselen, a synthetic organoselenium drug, within the Mpro catalytic site. Ebselen effectively engaged the active site, adopting proximity to H41 and interacting through the benzoisoselenazole ring in a π-π T-shaped arrangement, with an additional π-sulfur interaction with C145. In addition, the ligand-based drug design using the QSAR with GFA-MLR, RF, and ANN models were employed for biological activity prediction. The QSAR-ANN model showed robust statistical performance, with an r2training exceeding 0.98 and an RMSEtest of 0.21, indicating its suitability for predicting biological activities. Integration the ANN model with the LB-PaCS-MD insights enabled the rational design of novel compounds anchored in the ebselen core structure, identifying promising candidates with favorable predicted IC50 values. The designed compounds exhibited suitable drug-like characteristics and adopted an active conformation similar to ebselen, inhibiting Mpro function. These findings represent a synergistic approach merging ligand and structure-based drug design; with the potential to guide experimental synthesis and enzyme assay testing.
Palabras clave
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Antivirales
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Inhibidores de Proteasas
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Diseño de Fármacos
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Compuestos de Organoselenio
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Relación Estructura-Actividad Cuantitativa
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Isoindoles
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Simulación de Dinámica Molecular
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Aprendizaje Automático
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Proteasas 3C de Coronavirus
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SARS-CoV-2
Idioma:
En
Revista:
Bioorg Med Chem Lett
Asunto de la revista:
BIOQUIMICA
/
QUIMICA
Año:
2024
Tipo del documento:
Article