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Updated: Apr 15, 2026

Author Spotlight: Advancing Antibiotic Resistance Research Using an Efflux-Deficient Bacterial Strain and a Single-Copy Gene Expression System
Published on: January 5, 2024
Whole-Genome Sequencing of Multidrug-Resistant Acinetobacter baumannii Local Isolate and Molecular Dynamics
Farha Anwer1, Sidra Anwar1, Abdur Rahman1
1Atta Ur Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.
Abstract:
Acinetobacter baumannii (A. baumannii) represents a major threat because of its multidrug resistance, achieved through its ability to control virulence, and its mechanisms of drug efflux resistance. In this study, we used a combined experimental-computational approach to create and evaluate antimicrobial peptides that targeted the two essential pathogenic proteins, BfmR and AbaQ. The genomic analysis of a clinical isolate showed an extensive resistome and virulence profile, which matched high-risk global lineages. This study conducted molecular docking of an experimental AMP (cathelicidin KR-12 screened from the literature) and a rationally designed synthetic AMP (modified KR-12 analog) with pathogenic proteins, followed by 200 ns molecular dynamics simulations to evaluate both the binding stability and inhibitory potential of the compounds. The disk diffusion assay and microdilution assay were performed against A. baumannii. The study used comparative trajectory analyses, including RMSD, RMSF, radius of gyration, solvent-accessible surface area, principal component analysis, and MM-PBSA free energy calculations, to show that the synthetic AMP created stable electrostatic and hydrogen-bond networks, which caused conformational locking, and reached lower energy states than the experimental peptide. The synthetic AMP showed significant inhibition in validation in vitro. Contrastingly, the experimental AMP had transient interactions and no specificity. The study demonstrates that rationally designed AMPs have therapeutic potential, while the results create a reliable in silico framework to combat multidrug-resistant A. baumannii.
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