Surprisal Adaptive Sampling

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.

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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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