Simulating long time scale phenomena with Markov State Models

Vijay Pande
Stanford University
Department of Chemistry

One of the major challenges of connecting simulation to many application areas, especially biological applications such as protein folding or lipid vesicle fusion, is the relatively long time scales found experimentally (milliseconds to seconds) compared to what is typically possible computationally (nanoseconds to microseconds). I will describe our efforts to break past these time scale barriers with Markov State Models (MSM's). In our MSM formulation, we have means to automatically identify relevant states, very efficiently sample transitions from these states using adaptive methods, and then to finally statistically test and compare models. I will demonstrate this method using a diverse set of biological examples, including protein folding, misfolding of Alzheimer's peptides, and lipid vesicle fusion.

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