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New combined Inverse-QSAR and molecular docking method for scaffold-based drug discovery.
- Source :
-
Computers in biology and medicine [Comput Biol Med] 2024 Sep; Vol. 180, pp. 108992. Date of Electronic Publication: 2024 Aug 10. - Publication Year :
- 2024
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Abstract
- Computer-aided drug discovery plays a vital role in developing novel medications for various diseases. The COVID-19 pandemic has heightened the need for innovative approaches to design lead compounds with the potential to become effective drugs. Specifically, designing promising inhibitors of the SARS-CoV-2 main protease (Mpro) is crucial, as it plays a key role in viral replication. Phytochemicals, primarily flavonoids and flavonols from medicinal plants, were screened. Fifty small molecules were selected for molecular docking analysis against SARS-CoV-2 Mpro (PDB ID: 6LU7). Binding energies and interactions were analyzed and compared to those of the anti-SARS-CoV-2 inhibitor Nirmatrelvir. Using these 50 structures as a training set, a QSAR model was built employing simple, reversible topological descriptors. An inverse-QSAR analysis was then performed on 2⁹ = 512 hydroxyl combinations at nine possible positions on the flavone and flavonol scaffold. The model predicted three novel, promising compounds exhibiting the most favorable binding energies (-8.5 kcal/mol) among the 512 possible hydroxyl combinations: 3,6,7,2',4'-pentahydroxyflavone (PF9), 6,7,2',4'-tetrahydroxyflavone (PF11), and 3,6,7,4'-tetrahydroxyflavone (PF15). Molecular dynamics (MD) simulations demonstrated the stability of the PF9/Mpro complex over 300 ns of simulation. These predicted structures, reported here for the first time, warrant synthesis and further evaluation of their biological activity through in vitro and in vivo studies.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 Elsevier Ltd. All rights reserved.)
- Subjects :
- Humans
Drug Discovery
Coronavirus 3C Proteases antagonists & inhibitors
Coronavirus 3C Proteases chemistry
Coronavirus 3C Proteases metabolism
Antiviral Agents chemistry
Antiviral Agents pharmacology
COVID-19 Drug Treatment
Flavonoids chemistry
Molecular Docking Simulation
Quantitative Structure-Activity Relationship
SARS-CoV-2 drug effects
Subjects
Details
- Language :
- English
- ISSN :
- 1879-0534
- Volume :
- 180
- Database :
- MEDLINE
- Journal :
- Computers in biology and medicine
- Publication Type :
- Academic Journal
- Accession number :
- 39128176
- Full Text :
- https://doi.org/10.1016/j.compbiomed.2024.108992