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March 12, 2026Open Access

Computational Identification of Potential Novel Allosteric IHF Inhibitors Using QSAR Modeling to Inhibit Plasmid-Mediated Antibiotic Resistance

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Authors

OSOscar Saurith-CoronellOSOlimpo Sierra-HernandezJMJuan David Rodríguez Macías

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Overview

This computational study identifies potential IHF inhibitors in plasmid-mediated antibiotic resistance, suggesting novel therapeutic strategies.

Key Points

  • The study aims to develop a computational model to identify small molecules that inhibit the IHF protein, reducing plasmid-mediated antibiotic resistance.
  • Developed a 3D-QSAR model using a dataset of 65 anti-plasmid compounds.
  • Validated the model with leave-one-out cross-validation and Y-scrambling.
  • Evaluated compounds through pharmacophore clustering and molecular docking at IHF's DNA-binding and allosteric sites.
  • Conducted 200 ns molecular dynamics simulations to assess the stability of the most promising complexes.
  • QSAR model showed strong predictive performance with R2 = 0.90.
  • Allosteric binding energies were more favorable (up to -12.15 kcal/mol) than DNA-binding sites.
  • Molecular dynamics confirmed stability with lower RMSD fluctuations for allosteric complexes.
  • Dynamic cross-correlation analysis indicated conformational changes in key residues affected by allosteric binding.

Cite This Study

Saurith-Coronell et al. (2026) studied this question.

synapsesocial.com/papers/69b25b5496eeacc4fcec9f25https://doi.org/10.3390/ijms27062526
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