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.

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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