Using generalized ensemble simulations and Markov state models to identify conformational states

By Gregory R. Bowman, Xuhui Huang, Vijay S. Pande. Methods, 2009

294 citations recorded by the source corpus.

Part of understanding a molecule’s conformational dynamics is mapping out the dominant metastable, or long lived, states that it occupies. Once identified, the rates for transitioning between these states may then be determined in order to create a complete model of the system’s conformational dynamics. Here we describe the use of the MSMBuilder package (now available at https://simtk.org/home/msmbuilder/) to build Markov State Models (MSMs) to identify the metastable states from Generalized Ensemble (GE) simulations, as well as other simulation datasets. Besides building MSMs, the code also includes tools for model evaluation and visualization.

Subfields: Materials Chemistry, Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/f8e1669e0f8a2bf7c2de57a550781cbc476ee032

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In Materials Chemistry

In Molecular Biology

In Spectroscopy

Citations in the corpus

Cloud-based simulations on Google Exacycle reveal ligand-modulation of GPCR activation pathways (2013, methodology): “Markov state models (MSMs) were then used to stitch together these massively parallel simulations into a single statistical model, capturing rare events on timescales far longer than those reached by any individual simulation (12–14).”