Targeting Fibronectin-Binding Proteins in Staphylococcus aureus: In Silico Discovery and Pharmacokinetic Profiling of Novel Anti-Adhesion Inhibitors

Staphylococcus aureus is a highly virulent Gram-positive bacterium of global concern due to its potent virulence factors and antimicrobial resistance, causing severe morbidity and mortality. This study employed an anti-virulence approach that targets Fibronectin-binding proteins (FnBPs), key adhesion and immune-evasion determinants, offering an alternative to traditional antibiotics. Computational screening identified inhibitors, including Benzoic Acid (−8.61 kcal/mol), ML346 (−7.34 kcal/mol), and Gallic Acid (−7.29 kcal/mol), which showed strong binding potential. ADMET profiling confirmed good pharmacokinetic behavior and compliance with Lipinski’s Rule of Five. These results highlight small-molecule inhibitors of FnBPs that can disrupt a major virulence pathway in S. aureus, providing a computational foundation for anti-virulence therapy development requiring experimental validation.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-30
DOI
https://doi.org/10.5281/zenodo.23797277
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Targeting Fibronectin-Binding Proteins in Staphylococcus aureus: In Silico Discovery and Pharmacokinetic Profiling of Novel Anti-Adhesion Inhibitors

Usha Chouhan
5 links
Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
article

Targeting Fibronectin-Binding Proteins in Staphylococcus aureus: In Silico Discovery and Pharmacokinetic Profiling of Novel Anti-Adhesion Inhibitors

Usha Chouhan
article en

Abstract

Staphylococcus aureus is a highly virulent Gram-positive bacterium of global concern due to its potent virulence factors and antimicrobial resistance, causing severe morbidity and mortality. This study employed an anti-virulence approach that targets Fibronectin-binding proteins (FnBPs), key adhesion and immune-evasion determinants, offering an alternative to traditional antibiotics. Computational screening identified inhibitors, including Benzoic Acid (−8.61 kcal/mol), ML346 (−7.34 kcal/mol), and Gallic Acid (−7.29 kcal/mol), which showed strong binding potential. ADMET profiling confirmed good pharmacokinetic behavior and compliance with Lipinski’s Rule of Five. These results highlight small-molecule inhibitors of FnBPs that can disrupt a major virulence pathway in S. aureus, providing a computational foundation for anti-virulence therapy development requiring experimental validation.

Zenodo (CERN European Organization for Nuclear Research)
Good health and well-being
Openalex Percentile: Top 14%
Computational Drug Discovery Methods
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