Your browser doesn't support javascript.
loading
Integrating virtual screening, pharmacoinformatics profiling, and molecular dynamics: identification of promising inhibitors targeting 3CLpro of SARS-CoV-2.
Mohammad, Abeer; Zheoat, Ahmed; Oraibi, Amjad; Manaithiya, Ajay; S Almaary, Khalid; Allah Nafidi, Hiba; Bourhia, Mohammed; Kilani-Jaziri, Soumaya; A Bin Jardan, Yousef.
Afiliación
  • Mohammad A; Department of Pharmacy, Al-Manara College for Medical Sciences, Maysan, Iraq.
  • Zheoat A; Advanced Medical and Dental Institute, University Sains Malaysia, Kepala Batas, Pulau, Penang, Malaysia.
  • Oraibi A; Department of Pharmacy, Al-Manara College for Medical Sciences, Maysan, Iraq.
  • Manaithiya A; Department of Pharmacy, Al-Manara College for Medical Sciences, Maysan, Iraq.
  • S Almaary K; Department of Pharmaceutical Sciences A, Faculty of Pharmacy of Monastir, University of Monastir, Monastir, Tunisia.
  • Allah Nafidi H; Research Unit for Bioactive Natural Products and Biotechnology UR17ES49, Faculty of Dental Medicine of Monastir, University of Monastir, Monastir, Tunisia.
  • Bourhia M; Department of Medicinal Chemistry, Jamia Hamdard, New Delhi, India.
  • Kilani-Jaziri S; Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia.
  • A Bin Jardan Y; Department of Food Science, Faculty of Agricultural and Food Sciences, Laval University, Quebec, QC, Canada.
Front Mol Biosci ; 10: 1306179, 2023.
Article en En | MEDLINE | ID: mdl-38516396
ABSTRACT

Introduction:

The pursuit of effective therapeutic solutions for SARS-CoV-2 infections and COVID-19 necessitates the repurposing of existing compounds. This study focuses on the detailed examination of the central protease, 3-chymotrypsin-like protease (3CLpro), a pivotal player in virus replication. The combined approach of molecular dynamics simulations and virtual screening is employed to identify potential inhibitors targeting 3CLpro.

Methods:

A comprehensive virtual screening of 7120 compounds sourced from diverse databases was conducted. Four promising inhibitors, namely EN1036, F6548-4084, F6548-1613, and PUBT44123754, were identified. These compounds exhibited notable attributes, including high binding affinity (ranging from -5.003 to -5.772 Kcal/mol) and superior Induced Fit Docking scores (ranging from -671.66 to -675.26 Kcal/mol) compared to co-crystallized ligands.

Results:

In-depth analysis revealed that F6548-1613 stood out, demonstrating stable hydrogen bonds with amino acids His41 and Thr62. Notably, F6548-1613 recorded a binding energy of -65.72 kcal/mol in Molecular Mechanics Generalized Born Surface Area (MMGBSA) simulations. These findings were supported by Molecular Dynamics simulations, highlighting the compound's efficacy in inhibiting 3CLpro.

Discussion:

The identified compounds, in compliance with Lipinski's rule of five and exhibiting functional molecular interactions with 3CLpro, present promising therapeutic prospects. The integration of in silico methodologies significantly expedites drug discovery, laying the foundation for subsequent experimental validation and optimization. This approach holds the potential to develop effective therapeutics for SARS-CoV-2.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Mol Biosci Año: 2023 Tipo del documento: Article País de afiliación: Irak Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Mol Biosci Año: 2023 Tipo del documento: Article País de afiliación: Irak Pais de publicación: Suiza