The computation of dissociation rates from modeling of macromolecule-ligand unbinding processes is a topic of recent and increasing interest for drug design applications. However, the complexity of the high-dimensional space explored during dissociation on timescales that often exceed those accessible to conventional molecular dynamics (MD) simulations make this task highly challenging. Introduction of a scaling potential or additional force can accelerate the dissociation process, but may affect the reliability of simulated egress paths and thus observed mechanisms and computed residence times. We address this problem by exploring the dissociation of benzene and indole from T4 lysozyme mutants. We employ the tau-Random Acceleration Molecular Dynamics (tauRAMD) method, in which a small randomly oriented force is applied to the ligand to facilitate its unbinding during MD simulations. We find that tauRAMD yields the ranking of dissociation rates for the simulated ligands, protein mutants and temperature conditions in good accordance with experiments. Comparison of the unbinding paths and metastable states of benzene from the L99A mutant reveals a good agreement of tauRAMD with much more computationally demanding conventional MD simulations. Moreover, mapping of the egress routes for all the systems studied shows that visiting more metastable states slows dissociation and indicates that accurate dissociation rates can be computed without exhaustive sampling, as long as the main egress route is sampled. Overall, this study demonstrates that tauRAMD combines both computational efficiency and the ability to capture the main features determining the relative dissociation rates, thus providing insights that could be exploited in drug design .
The computation of dissociation rates from modeling of macromolecule-ligand unbinding processes is a topic of recent and increasing interest for drug design applications. However, the complexity of the high-dimensional space explored during dissociation on timescales that often exceed those accessible to conventional molecular dynamics (MD) simulations make this task highly challenging. Introduction of a scaling potential or additional force can accelerate the dissociation process, but may affect the reliability of simulated egress paths and thus observed mechanisms and computed residence times. We address this problem by exploring the dissociation of benzene and indole from T4 lysozyme mutants. We employ the tau-Random Acceleration Molecular Dynamics (tauRAMD) method, in which a small randomly oriented force is applied to the ligand to facilitate its unbinding during MD simulations. We find that tauRAMD yields the ranking of dissociation rates for the simulated ligands, protein mutants and temperature conditions in good accordance with experiments. Comparison of the unbinding paths and metastable states of benzene from the L99A mutant reveals a good agreement of tauRAMD with much more computationally demanding conventional MD simulations. Moreover, mapping of the egress routes for all the systems studied shows that visiting more metastable states slows dissociation and indicates that accurate dissociation rates can be computed without exhaustive sampling, as long as the main egress route is sampled. Overall, this study provides physical insights that could be exploited in the rational optimization of the kinetic properties of drug candidates .
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demonstrates that tauRAMD combines both computational efficiency and the ability to capture the main features determining the relative dissociation rates, thus providing
provides physical
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drug design
the rational optimization of the kinetic properties of drug candidates