Computational Repurposing of Adozelesin and Zolifodacin as Potential MepR-Binding Compounds Against Multidrug-Resistant Staphylococcus aureus M48. An Integrated Genomic and Structure Based Investigation

Multidrug-resistant Staphylococcus aureus represents a major clinical challenge because of the increasing prevalence of antimicrobial resistance and efflux-mediated resistance mechanisms. The MepR-MepA regulatory system is involved in the control of multidrug efflux in S. aureus, making MepR a relevant target for investigating compounds capable of modulating this regulatory system. In the present study, an integrated genomic and structure-based computational workflow was applied to S. aureus strain M48 to characterize antimicrobial resistance determinants and prioritize potential MepR-binding compounds. Whole-genome analysis using the Comprehensive Antibiotic Resistance Database (CARD) and Resistance Gene Identifier (RGI) identified the resistance-associated genetic repertoire of the strain, followed by comparative analysis of selected determinants. The MepR structure was evaluated using structural modelling and experimental structural information, and candidate binding regions were investigated through virtual screening and molecular docking. Adozelesin and zoliflodacin were prioritized based on their predicted interactions with MepR. Molecular-dynamics simulations were subsequently used to examine the structural behavior of the resulting complexes, while complementary physicochemical, pharmacokinetic, drug-likeness, and toxicity predictions were performed to characterize their computational ADMET profiles. Adozelesin showed a more favorable predicted docking score, whereas zoliflodacin displayed comparatively lower structural fluctuations and more persistent protein-ligand interactions during the simulated trajectory. These findings identify adozelesin and zoliflodacin as computationally prioritized MepR-binding candidates for further investigation. Importantly, the present study does not establish MepR inhibition or demonstrate functional effects on MepR-mediated repression or mepA expression. Experimental binding, DNA-binding, transcriptional, and antibacterial studies are required to determine the biological significance of the predicted interactions.

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Publication Details

Journal
Journal of Computational Biophysics and Chemistry
Published
2026-10-31
DOI
https://doi.org/10.1142/s2737416527500074
Primary Topic
Computational Drug Discovery Methods
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article
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article

Computational Repurposing of Adozelesin and Zolifodacin as Potential MepR-Binding Compounds Against Multidrug-Resistant Staphylococcus aureus M48. An Integrated Genomic and Structure Based Investigation

Shahzeb Alam, Abdullah F. Alasmari, Syed Shujait Ali, Metab Alharbi et al.
Journal of Computational Biophysics and Chemistry
Computational Drug Discovery Methods
article

Computational Repurposing of Adozelesin and Zolifodacin as Potential MepR-Binding Compounds Against Multidrug-Resistant Staphylococcus aureus M48. An Integrated Genomic and Structure Based Investigation

Shahzeb Alam, Abdullah F. Alasmari, Syed Shujait Ali, Metab Alharbi, Israr Hussain, Inam Ur Rahman, Arshad Iqbal, Shah Hussain
article en

Abstract

Multidrug-resistant Staphylococcus aureus represents a major clinical challenge because of the increasing prevalence of antimicrobial resistance and efflux-mediated resistance mechanisms. The MepR-MepA regulatory system is involved in the control of multidrug efflux in S. aureus, making MepR a relevant target for investigating compounds capable of modulating this regulatory system. In the present study, an integrated genomic and structure-based computational workflow was applied to S. aureus strain M48 to characterize antimicrobial resistance determinants and prioritize potential MepR-binding compounds. Whole-genome analysis using the Comprehensive Antibiotic Resistance Database (CARD) and Resistance Gene Identifier (RGI) identified the resistance-associated genetic repertoire of the strain, followed by comparative analysis of selected determinants. The MepR structure was evaluated using structural modelling and experimental structural information, and candidate binding regions were investigated through virtual screening and molecular docking. Adozelesin and zoliflodacin were prioritized based on their predicted interactions with MepR. Molecular-dynamics simulations were subsequently used to examine the structural behavior of the resulting complexes, while complementary physicochemical, pharmacokinetic, drug-likeness, and toxicity predictions were performed to characterize their computational ADMET profiles. Adozelesin showed a more favorable predicted docking score, whereas zoliflodacin displayed comparatively lower structural fluctuations and more persistent protein-ligand interactions during the simulated trajectory. These findings identify adozelesin and zoliflodacin as computationally prioritized MepR-binding candidates for further investigation. Importantly, the present study does not establish MepR inhibition or demonstrate functional effects on MepR-mediated repression or mepA expression. Experimental binding, DNA-binding, transcriptional, and antibacterial studies are required to determine the biological significance of the predicted interactions.

Journal of Computational Biophysics and Chemistry
Openalex Percentile: Top 14%
Computational Drug Discovery Methods
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