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Published on: December 27, 2016
In Silico Prioritisation of Similarity-Selected Small Molecules Targeting the IsdB NEAT Domain of Staphylococcus
Warinda Prommachote1,2, Manu Deeudom3, Hridek Manimaran4
1Department of Biochemistry, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand.
Abstract:
The 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.
Insights
Researchers identified potential inhibitors for multidrug-resistant Staphylococcus aureus (MRSA) using computational methods. Compound TOP2 showed promising binding affinity and a favorable safety profile, making it a priority for further study.
Area of Science:
- Computational chemistry
- Drug discovery
- Microbiology
Background:
- Rising prevalence of multidrug-resistant Staphylococcus aureus (MRSA) necessitates novel therapeutic strategies.
- Targeting bacterial virulence factors, like heme acquisition proteins, is a promising approach.
- The iron-regulated surface determinant B (ISDB) Near-iron Transporter domain is crucial for MRSA pathogenicity.
Purpose of the Study:
- To identify potential small molecule inhibitors of the ISDB Near-iron Transporter domain using an integrated in silico approach.
- To evaluate the binding affinity, stability, and drug-likeness of identified compounds.
- To predict the pharmacokinetic and toxicity profiles of candidate inhibitors.
Main Methods:
- Virtual screening and molecular docking were employed to identify potential binders.
- Molecular dynamics simulations (200 ns) assessed protein-ligand complex stability.
- MM/PBSA analysis determined binding energy contributions.
- In silico tools predicted drug-likeness, pharmacokinetics, and toxicity.
Main Results:
- Two compounds, TOP1 and TOP2, exhibited strong binding affinities (-12.0 and -11.8 kcal/mol).
- Molecular dynamics confirmed stable interactions, with reduced fluctuations in ligand-bound states.
- MM/PBSA analysis indicated van der Waals forces as key contributors, favoring TOP1.
- Drug-likeness and pharmacokinetic predictions were generally favorable, with some limitations.
- Toxicity predictions revealed TOP2 had a more favorable safety profile than TOP1.
Conclusions:
- TOP2 is a computationally prioritized candidate for further experimental investigation due to its balance of binding affinity and safety.
- A trade-off exists between binding affinity and predicted safety profiles for the identified compounds.
- Further computational and experimental studies are required to validate these findings and assess therapeutic potential.
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