Akademik Veri Yönetim Sistemi
Letters in Drug Design and Discovery, cilt.22, sa.11, 2025 (SCI-Expanded, Scopus)
Methicillin-resistant Staphylococcus aureus (MRSA) remains a critical global health threat, necessitating the development of novel antimicrobial agents. Dihydrofolate reductase (DHFR) represents a validated therapeutic target for antibacterial drug discovery. Objective: This study identifies novel DHFR inhibitors with enhanced efficacy against MRSA through integrated computational drug design. Structure-based pharmacophore modeling used the Staphylococcus aureus DHFR crystal structure (PDB: 3FYV) complexed with AR-102. Virtual screening of ZINC, MolPort, ChemSpace, and ChEMBL databases identified 94 potential inhibitors. Comprehensive ADMET profiling narrowed the selection to 10 optimal candidates through K-means clustering and multi-parameter optimization. The top five compounds underwent 50 ns molecular dynamics (MD) simulations using GROMACS. Results: PubChem-44362961 emerged as the most promising candidate. This compound exhibited excellent drug-likeness (QED: 0.8699), favorable ADMET score (0.775), and zero toxicity. Molecular docking revealed critical hydrogen bonds with ALA7 and multiple hydrophobic interactions. MD simulations confirmed superior stability with the lowest mean RMSD (0.116 nm ± 0.018 nm) and optimal protein-ligand complex stability. Ligand 1 maintained key interactions observed in the reference compound while demonstrating enhanced conformational stability. This integrated computational pipeline successfully identified PubChem-44362961 as a potential lead compound for MRSA treatment. The compound retains the successful inhibition mechanism of AR-102 while offering optimized pharmacokinetic properties. These findings provide a rational foundation for developing next-generation DHFR inhibitors against antimicrobial-resistant pathogens. Future experimental validation and structure-activity relationship studies are warranted to advance this compound toward clinical development.