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.
The protein-ligand residence time, tau, influences molecular function in biological networks and has been recognized as an important determinant of drug efficacy. To predict tau, computational methods must overcome the problem that tau often exceeds the timescales accessible to conventional molecular dynamics (MD) simulation. Here, we apply the tau-Random Acceleration Molecular Dynamics (tauRAMD) method to a set of kinetically characterized complexes of T4 lysozyme mutants with engineered binding cavities. tauRAMD yields relative ligand dissociation rates in good accordance with experiments and thereby allows a comprehensive characterization of the ligand egress routes and determinants of tau. Although ligand dissociation by multiple egress routes is observed, we find that egress via the predominant route determines the value of tau. We also find that the presence of metastable states along egress pathways slows down protein-ligand dissociation. These physical insights could be exploited in the rational optimization of the kinetic properties of drug candidates.
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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
protein-ligand residence time, tau, influences molecular function in biological networks and has been recognized as an important determinant of drug efficacy. To predict tau, computational methods must overcome the problem that tau often exceeds the timescales
R
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
simulation. Here, we apply the
R
, 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
to a set of kinetically characterized complexes of T4 lysozyme mutants with engineered binding cavities. tauRAMD yields relative ligand dissociation rates
R
. 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
and thereby allows a comprehensive characterization of the ligand egress routes and determinants of tau. Although ligand dissociation by multiple egress routes is observed, we find that egress via the predominant route determines the value of tau. We also find that the presence of metastable states along egress pathways slows down protein-ligand dissociation. These physical insights