Protein-Protein Interaction Stabilizers from MD Simulation-Derived Pharmacophores
Mohd Ibrahim1, Martin Zacharias1
1Physics Department and Center for Functional Protein Assemblies, Technical University of Munich, 85748 Garching, Germany.
Journal of Chemical Information and Modeling
|May 1, 2026
Summary
This study introduces PPIS-MDPharma, a novel workflow to discover protein-protein interaction (PPI) stabilizers. It uses molecular dynamics simulations to identify drug candidates for treating diseases caused by disrupted cellular processes.
Area of Science:
- Biochemistry and Structural Biology
- Computational Chemistry
- Drug Discovery
Background:
- Protein-protein interactions (PPIs) are vital for cellular functions.
- Dysregulated PPIs are implicated in various diseases.
- Stabilizing PPIs with small molecules is a therapeutic strategy.
Purpose of the Study:
- To develop an efficient workflow for identifying PPI stabilizers.
- To leverage molecular dynamics (MD) simulations and pharmacophore screening.
Main Methods:
- Extracting pharmacophore features (hydrogen bonding, electrostatic, hydrophobic, aromatic) from MD simulations.
- Rapid pharmacophore screening of a 50-million compound database.
- Rescoring candidates using MMGBSA.
Main Results:
- Identified numerous PPI stabilizer candidates for seven protein complexes.
- Top-ranked ligands showed MMGBSA scores comparable to known stabilizers.
- The workflow is computationally efficient compared to docking methods.
Conclusions:
- The PPIS-MDPharma workflow effectively identifies PPI stabilizers.
- This approach offers a promising, efficient tool for drug discovery targeting PPIs.
- Enables development of novel therapeutics for various diseases.
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