Computational Identification of Potential Novel Allosteric IHF Inhibitors Using QSAR Modeling to Inhibit...

Area of Science:

• Computational chemistry
• Drug discovery
• Microbiology

Background:

• Antibiotic resistance spread via plasmids is a major health threat.
• No drugs currently target plasmid-mediated conjugation, creating a therapeutic gap.
• Integration Host Factor (IHF) is crucial for plasmid transfer and a potential drug target.

Purpose of the Study:

• Develop a predictive computational model for anti-conjugation agents.
• Identify small molecules that inhibit IHF function.
• Reduce plasmid transfer and the dissemination of antibiotic resistance genes.

Main Methods:

• 3D-QSAR modeling using QuBiLS-MIDAS descriptors.
• Pharmacophore clustering for compound selection.
• Molecular docking and dynamics simulations of IHF-ligand complexes.
• Validation using cross-validation, Tropsha's criteria, and Y-scrambling.

Main Results:

• A validated QSAR model (Q²=0.82, R²=0.90) predicted compound activity.
• Allosteric inhibition site showed more favorable binding energies than the DNA-binding site.
• Molecular dynamics confirmed stable allosteric interactions, inducing conformational changes in catalytic residues.

Conclusions:

• Allosteric inhibition of IHF is a novel anti-conjugation strategy.
• Identified potential drug candidates targeting IHF's allosteric site.
• Findings support developing new agents to combat horizontal gene transfer and restore antibiotic efficacy.