Abstract

To understand the functional roles of biomolecules, it is necessary to study both stable and metastable states in conformational space and how they are connected. Because of the advance of hardware and software, molecular dynamics (MD) simulation methods have become a feasible tool for this purpose, resulting in rather quantitative conclusions, which can be compared with experiment. MD simulation methods, however, still have a bottleneck due to “rare events” connecting stable states, and such a rare event can occur with millisecond timescales in a large biomolecule, which hampers a direct application of MD simulations to the rare event of biomolecules. This is why we need some novel ideas and algorithms to overcome this problem of rare events, and many researchers have been developing promising methods, mainly focusing on conformational sampling methods. These include very powerful replica exchange and multicanonical methods, but time information is lost in these methods and dynamic characterization of a rare event is difficult. In this presentation, we apply the milestoning method devised by Elber, Vanden-Eijnden and others to conformational change of a small peptide, chignolin, at the folding temperature (∼420K). The milestoning method is regarded as an alternative of Markov state modeling, and by defining “milestones (collections of small dividing surfaces)” in some order parameter space and counting the crossing of milestones by a trajectory, mean first passage times (MFPTs) between two milestones can be obtained and a kinetic characterization of conformational change can be achieved. Here we will examine how the choice of order parameter space affects the results of MFPTs, and also analyze the effects of non-Markovianity for this process using Zuckerman's method.

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