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In Silico design and molecular dynamics analysis of imidazole derivatives as selective cyclooxygenase-2 inhibitors.
- Source :
-
Computational biology and chemistry [Comput Biol Chem] 2025 Jan 09; Vol. 115, pp. 108341. Date of Electronic Publication: 2025 Jan 09. - Publication Year :
- 2025
- Publisher :
- Ahead of Print
-
Abstract
- Cyclooxygenase-2 (COX-2), a key enzyme in the inflammatory pathway, is the target for various nonsteroidal anti-inflammatory drugs (NSAIDs) and selective inhibitors known as coxibs. This study focuses on the development of novel imidazole derivatives as COX-2 inhibitors, utilizing a Structure-Activity Relationship (SAR) approach to enhance binding affinity and selectivity. Molecular docking was performed using Autodock Vina, revealing binding energies of -6.928, -7.187, and -7.244 kJ/mol for compounds 5b, 5d, and 5e, respectively. Molecular dynamics simulations using GROMACS provided insights into the stability and conformational changes of the protein-ligand complexes. Key metrics such as RMSD, RMSF, Rg, SASA, and hydrogen bond analysis were employed to assess the interactions. The binding free energy of the inhibitors was estimated using the MMPBSA method, highlighting compound 5b (N-[(3-benzyl-2-methylsulfonylimidazol-4-yl)methyl]-4-methoxyaniline) with the lowest binding energy of -162.014 kcal/mol. ADMET analysis revealed that compound 5b exhibited the most favorable pharmacokinetic properties and safety profile. Overall, this investigation underscores the potential of these novel imidazole derivatives as effective COX-2 inhibitors, with compound 5b emerging as the most promising candidate for further development.<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 © 2025. Published by Elsevier Ltd.)
Details
- Language :
- English
- ISSN :
- 1476-928X
- Volume :
- 115
- Database :
- MEDLINE
- Journal :
- Computational biology and chemistry
- Publication Type :
- Academic Journal
- Accession number :
- 39808951
- Full Text :
- https://doi.org/10.1016/j.compbiolchem.2025.108341