Building Markov state models along pathways to determine free energies and rates of transitions.
An efficient method is proposed for building Markov models with discrete states able to accurately describe the slow relaxation of a complex system with two stable conformations. First, the reaction pathway described by a set of collective variables between the two stable states is determined using the string method with swarms of trajectories. Then, short trajectories are initiated at different points along this pathway to build the state-to-state transition probability matrix. It is shown, using a model system, how this strategy makes it possible to use trajectories that are significantly shorter than the slowest relaxation time to efficiently build a reliable and accurate Markov model. Extensions of the method to multiple pathways, as well as some common pitfalls arising from poorly relaxed paths or an inappropriate choice of collective variables, are illustrated and discussed.
Pan
Albert C
AC
Department Biochemistry and Molecular Biology, Gordon Center of Integrative Science, University of Chicago, Chicago, Illinois 60637, USA.
Roux
Benoît
B
D003198:Computer Simulation; D007700:Kinetics; D008390:Markov Chains; D008958:Models, Molecular; D013816:Thermodynamics; D013997:Time Factors