Genome-Guided Computational Profiling of Selected Antibiotics for Repurposing against Multiple Resistance Proteins in Multidrug-Resistant Stenotrophomonas maltophilia
This study utilizes an integrated computational workflow, including homology modeling, molecular docking, and molecular dynamics simulations, to identify kanamycin C as the most promising cross-target candidate for interacting with key resistance proteins (AAC(6′)-Ib4, DfrA14, and L1 metallo-β-lactamase) in multidrug-resistant *Stenotrophomonas maltophilia*, thereby generating testable hypotheses for antibiotic repurposing while emphasizing that these findings remain predictive rather than clinically confirmed.