Recent progress in molecular simulation methods for drug binding kinetics

Abstract

Due to the contribution of drug-target binding kinetics to drug efficacy, there is a high level of interest in developing methods to predict drug-target binding kinetic parameters. During the review period, a wide range of enhanced sampling molecular dynamics simulation-based methods has been developed for computing drug-target binding kinetics and studying binding and unbinding mechanisms. Here, we assess the performance of these methods considering two benchmark systems in detail: mutant T4 lysozyme-ligand complexes and a large set of N-HSP90-inhibitor complexes. The results indicate that some of the simulation methods can already be usefully applied in drug discovery or lead optimization programs but that further studies on more high-quality experimental benchmark datasets are necessary to improve and validate computational methods.

arXiv commentFigure 3 was improved. A definition of PIB was included. Reference to WE was added (ref. 20), reference to RAMD was corrected (ref. 43)

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Cited by in corpus (7)

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• Multisecond ligand dissociation dynamics from atomistic simulations
• Ligand unbinding mechanisms and kinetics for T4 lysozyme mutants from tauRAMD simulations
• Efficient quantum computation of molecular forces and other energy gradients
• Predicting ion channel conductance via dissipation-corrected targeted molecular dynamics and Langevin equation simulations
• Free energy along drug-protein binding pathways interactively sampled in virtual reality
• Autoencoders for dimensionality reduction in molecular dynamics: collective variable dimension, biasing and transition states