On the determination of rate constants from equilibrium molecular dynamics simulations

1990 ◽  
Vol 93 (6) ◽  
pp. 4117-4122 ◽  
Author(s):  
David Brown ◽  
Julian H. R. Clarke
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Rate Constants ◽  
Dynamics Simulations

scholarly journals A method of incorporating rate constants as kinetic constraints in molecular dynamics simulations

2020 ◽  
Vol 118 (2) ◽  
pp. e2012423118
Author(s):  
Z. Faidon Brotzakis ◽  
Michele Vendruscolo ◽  
Peter G. Bolhuis
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Rate Constants ◽  
Molecular System ◽  
Accurate Determination ◽  
Molecular Simulations ◽  
Model Systems ◽  
Wide Range ◽  
Dynamics Simulations

From the point of view of statistical mechanics, a full characterization of a molecular system requires an accurate determination of its possible states, their populations, and the respective interconversion rates. Toward this goal, well-established methods increase the accuracy of molecular dynamics simulations by incorporating experimental information about states using structural restraints and about populations using thermodynamics restraints. However, it is still unclear how to include experimental knowledge about interconversion rates. Here, we introduce a method of imposing known rate constants as constraints in molecular dynamics simulations, which is based on a combination of the maximum-entropy and maximum-caliber principles. Starting from an existing ensemble of trajectories, obtained from either molecular dynamics or enhanced trajectory sampling, this method provides a minimally perturbed path distribution consistent with the kinetic constraints, as well as modified free energy and committor landscapes. We illustrate the application of the method to a series of model systems, including all-atom molecular simulations of protein folding. Our results show that by combining experimental rate constants and molecular dynamics simulations, this approach enables the determination of transition states, reaction mechanisms, and free energies. We anticipate that this method will extend the applicability of molecular simulations to kinetic studies in structural biology and that it will assist the development of force fields to reproduce kinetic and thermodynamic observables. Furthermore, this approach is generally applicable to a wide range of systems in biology, physics, chemistry, and material science.

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