Skip to main navigation Skip to search Skip to main content

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

  • Oscar Saurith-Coronell
  • , Olimpo Sierra-Hernandez
  • , Juan David Rodríguez-Macías*
  • , José R. Mora
  • , Noel Perez-Perez
  • , Jackson J. Alcázar
  • , Ricardo Olimpio de Moura
  • , Igor José dos Santos Nascimento
  • , Edgar A. Márquez Brazón*
  • , Yovani Marrero-Ponce
  • *Corresponding author for this work
  • Universidad del Norte
  • Universidad Libre
  • Universidad del Desarrollo
  • Universidade Estadual da Paraíba
  • Universidad Panamericana (UP)

Research output: Contribution to journalArticlepeer-review

Abstract

The rapid spread of antibiotic resistance through plasmid-mediated conjugation remains a primary global health concern. Despite its critical role in horizontal gene transfer, no approved drugs currently target this process, leaving a critical therapeutic gap. Integration Host Factor (IHF), a DNA-binding protein essential for plasmid replication and mobilization, emerges as a promising yet underexplored target for anti-conjugation strategies. This work aimed to develop a predictive computational model and identify small molecules that disrupt IHF function, thereby reducing plasmid transfer and limiting resistance gene dissemination. A curated dataset of 65 compounds with reported anti-plasmid activity was analyzed using a 3D-QSAR model based on algebraic descriptors computed with QuBiLS-MIDAS. The model was validated through leave-one-out cross-validation (Q2 = 0.82), Tropsha’s criteria, and Y-scrambling. Representative compounds were selected via pharmacophore clustering and evaluated through molecular docking at both the DNA-binding site and a predicted allosteric pocket of IHF. The most promising complexes underwent 200 ns molecular dynamics simulations to assess stability and interaction patterns. The QSAR model demonstrated strong predictive performance (R2 = 0.90). Docking simulations revealed more favorable binding energies at the allosteric site (up to −12.15 kcal/mol) compared to the DNA-binding site. Molecular dynamics confirmed the stability of these interactions, with allosteric complexes showing lower RMSD fluctuations and consistent binding energy profiles. Dynamic cross-correlation analysis revealed that allosteric ligand binding induces conformational changes in key catalytic residues, including Pro65, Pro61, and Leu66. These alterations may compromise DNA recognition and disrupt the initiation of replication. To our knowledge, this is the first computational study proposing allosteric inhibition of IHF as an anti-conjugation strategy. These findings provide a foundation for experimental validation and the development of novel agents to prevent horizontal gene transfer, offering a promising approach to restoring antibiotic efficacy against multidrug-resistant pathogens.

Original languageEnglish
Article number2526
JournalInternational Journal of Molecular Sciences
Volume27
Issue number6
DOIs
StatePublished - Mar 2026

Keywords

  • Integration Host Factor
  • QSAR modeling
  • antibiotic resistance
  • computational drug design
  • molecular docking
  • molecular dynamics
  • plasmid conjugation

Fingerprint

Dive into the research topics of 'Computational Identification of Potential Novel Allosteric IHF Inhibitors Using QSAR Modeling to Inhibit Plasmid-Mediated Antibiotic Resistance'. Together they form a unique fingerprint.

Cite this