Network Pharmacology Guided Drug Repurposing and Molecular Modeling Identify Sulfasalazine as a Potential OXA-23...

The rapid emergence of carbapenem-resistant Acinetobacter baumannii has become a major health concern, primarily driven by the dissemination of class D β-lactamases, particularly OXA-23, which compromise the efficacy of last-line β-lactam antibiotics. Drug repurposing combined with structure-based computational approaches provides a promising strategy for accelerating the discovery of novel therapeutic candidates against multidrug-resistant pathogens. This study aimed to identify FDA-approved non-steroidal anti-inflammatory drugs (NSAIDS) with potential inhibitory activity against OXA-23 β-lactamase by using a comprehensive computational drug discovery workflow. Twenty-six FDA-approved NSAIDs were evaluated using an integrated computational pipeline comprising network pharmacology, KEGG pathway analysis, molecular docking, molecular dynamics simulations and ADMET profiling. KEGG pathway analysis confirmed the central role of OXA-23 in β-lactam resistance, while network pharmacology prioritized nine candidates NSAIDS for subsequent structure-based investigation. Molecular docking was performed using the crystal structure of OXA-23 β-lactamase (PDB ID: 4K0X), followed by molecular dynamics simulations to assess the stability of the protein-ligand complexes. Among the prioritized compounds, sulfasalazine demonstrated the most favorable predicted binding affinity (-8.3 kcal/mol), forming stable interactions with key catalytic residues, including SER126, VAL128, and LEU166 and exhibiting a more favorable docking profile than the reference drug imipenem (-5.7 kcal/mol). Molecular dynamics simulations supported the structural stability of the sulfasalazine OXA-23 complex throughout the simulation period. Furthermore, ADMET analysis indicated favorable pharmacokinetic characteristics including good oral bioavailability, high gastrointestinal absorption, low central nervous system penetration, and an acceptable predicted safety profile. This integrated computational study identifies sulfasalazine as a promising repurposing candidate for targeting OXA-23 β-lactamase in carbapenem-resistant A. baumannii. The findings demonstrate the utility of combining network pharmacology with molecular modeling to prioritize candidate therapeutics and provide a computational framework for accelerating antimicrobial drug discovery. Experimental validation is warranted to confirm the inhibitory activity and therapeutic potential of sulfasalazine against multidrug-resistant A. baumannii.