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Path sampling challenges in large biomolecular systems: RETIS and REPPTIS for ABL-imatinib kinetics
Wouter Vervust1, Daniel T Zhang2, Enrico Riccardi3
1IBiTech - BioMMedA Research Group, Ghent University, Gent, Belgium.
Biophysical Journal
|April 25, 2025
Summary
Predicting drug-protein interaction kinetics is vital for personalized medicine. This study used path sampling to analyze imatinib dissociation from Abelson kinase, facing challenges with complex energy landscapes and convergence for improved drug efficacy predictions.
Area of Science:
- Computational chemistry and molecular dynamics
- Pharmacology and drug discovery
- Biophysics and structural biology
Background:
- Accurate prediction of drug-protein interaction kinetics is essential for drug efficacy and personalized medicine.
- Protein mutations, common in diseases like chronic myeloid leukemia, can alter drug residence times and treatment outcomes.
- Imatinib is a key drug for chronic myeloid leukemia, targeting Abelson tyrosine kinase.
Purpose of the Study:
- To investigate the dissociation kinetics of imatinib from Abelson tyrosine kinase (ABL) and its mutants using advanced path sampling methods.
- To assess the applicability and limitations of replica exchange transition interface sampling for complex biological systems.
- To identify challenges and propose future directions for improving kinetic predictions of drug dissociation.
Main Methods:
- Application of replica exchange transition interface sampling and its partial path variant.
- Investigation of imatinib dissociation from ABL and relevant mutants.
- Utilizing computational efficiency strategies like asynchronous replica exchange.
Main Results:
- The complex free energy landscape of ABL-imatinib dissociation, characterized by metastable states and multiple unbinding pathways, posed significant convergence challenges.
- Despite employing advanced computational techniques, full convergence for the dissociation process remained elusive.
- The study highlights the difficulties in applying path sampling methods to high-dimensional biological systems.
Conclusions:
- Path sampling methods offer a bias-free alternative to traditional approaches but face convergence issues in complex biological systems.
- Enhanced initialization strategies, advanced Monte Carlo moves, and machine learning-derived reaction coordinates are needed for improved kinetic predictions.
- This work critically assesses path sampling for drug dissociation kinetics, informing future computational drug discovery efforts.
