Markov state models (MSMs), which model conforma tional dynamics as a network of transitions between metastable states, have been increasingly used to model the thermodynamics and kinetics of biomolecules. In considering perturbations to molecular dynamics induced by sequence mutations, chemical modifications, or changes in external conditions, it is important to assess how transition rates change, independent of changes in metastable state definitions.
- Journal article: Surprisal Metrics for Quantifying Perturbed Conformational Dynamics in Markov State Models, Vincent A. Voelz, Brandon Elman, Asghar M. Razavi, and Guangfeng Zhou, Journal of Chemical Theory and Computation 10: 5716–5728, 2014
- Poster: Voelz, V., Elman, B., Razavi, A., & Zhou, G. Surprisal metrics for quantifying perturbed conformational dynamics in Markov state models. [PDF]
Asghar Razavi 
About the author asgharrazavi
Asghar Razavi is a postdoctoral associate at the Department of Physiology and Biophysics at Weill Cornell Medical College of Cornell University. He received his Ph.D. in Computational Chemistry and Biophysics from Temple University, Philadelphia, USA. His current research at the Weinstein lab focuses on developing molecular level quantitative kinetic models to understand thermodynamics, kinetics, and conformational pathways during function of neurotransmitter transporters and G protein-coupled receptors.
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June 23, 2017
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June 23, 2017
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January 7, 2017
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Dopamine Transporter