In Silico Prioritisation of Similarity-Selected Small Molecules Targeting the IsdB NEAT Domain of Staphylococcus aureus as a Potential Antivirulence Strategy
Warinda Prommachote, Manu Deeudom, Hridek Manimaran, Jittasak Khowsathit, Pimpisid Koonyosying, Bishant Pokharel, Yuvaraj Ravikumar, Somdet SrichairatanakoolThe increasing prevalence of multidrug-resistant Staphylococcus aureus (MRSA) has necessitated the development of alternative therapeutic strategies targeting bacterial virulence factors. This study employed an integrated in silico approach to identifying potential inhibitors of the iron-regulated surface determinant B Near-iron Transporter domain, a key protein involved in heme acquisition and pathogenicity. Virtual screening and molecular docking identified certain similarity-selected small molecules possessing strong binding affinities, with (4-(1-oxoisoindolin-2-yl)benzoic acid (TOP1) and (4-(2-oxochromen-3-yl)benzoic acid (TOP2) exhibiting the most favorable binding energies at −12.0 and −11.8 kcal/mol, respectively. Molecular dynamics simulations over 200 ns confirmed stable protein–ligand interactions that yielded reduced structural fluctuations in ligand-bound complexes when compared with the apo form. Molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) analysis revealed that van der Waals interactions were the primary contributors to binding, with TOP1 showing a more favorable overall binding energy. Drug-likeness and pharmacokinetic predictions indicated compliance with Lipinski’s rule of five and moderate bioavailability, although limited intestinal absorption was observed. Toxicity predictions indicated that both compounds are non-mutagenic but may exhibit hepatotoxicity. Notably, TOP1 exhibited potential nephrotoxicity, cardiotoxicity, and carcinogenicity, whereas TOP2 demonstrated a more favorable safety profile. These findings highlight a trade-off between binding affinity and safety, suggesting that TOP2 emerged as a computationally prioritized candidate for future experimental validation. Because the present findings represent computational predictions only, further orthogonal computational analyses and experimental studies are required to confirm the proposed binding modes, biological activity, and therapeutic potential of the identified compounds.