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J Chem Phys. 2009 Sep 28;131(12):124101. doi: 10.1063/1.3216567.

Progress and challenges in the automated construction of Markov state models for full protein systems.

Author information

1
Biophysics Program, Stanford University, Stanford, California 94305, USA.

Abstract

Markov state models (MSMs) are a powerful tool for modeling both the thermodynamics and kinetics of molecular systems. In addition, they provide a rigorous means to combine information from multiple sources into a single model and to direct future simulations/experiments to minimize uncertainties in the model. However, constructing MSMs is challenging because doing so requires decomposing the extremely high dimensional and rugged free energy landscape of a molecular system into long-lived states, also called metastable states. Thus, their application has generally required significant chemical intuition and hand-tuning. To address this limitation we have developed a toolkit for automating the construction of MSMs called MSMBUILDER (available at https://simtk.org/home/msmbuilder). In this work we demonstrate the application of MSMBUILDER to the villin headpiece (HP-35 NleNle), one of the smallest and fastest folding proteins. We show that the resulting MSM captures both the thermodynamics and kinetics of the original molecular dynamics of the system. As a first step toward experimental validation of our methodology we show that our model provides accurate structure prediction and that the longest timescale events correspond to folding.

PMID:
19791846
PMCID:
PMC2766407
DOI:
10.1063/1.3216567
[Indexed for MEDLINE]
Free PMC Article

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