Development and Application of a Multi-Scale Markov Model for Simulating Protein Folding

Stanford University, Stanford CA

Investigators

Abstract

One of the fundamental challenges in molecular simulation is the fact that chemical detail is often necessary for answering questions of interest, yet it is this very detail which greatly limits what is feasible to study. Multi-scale simulation methods give the hope to solve this problem, by combining results from multiple scales, using detail only where it is needed most. Several key issues remain, such as how can one know which details are the most relevant? How can one efficiently, systematically, and rigorously combine results from multiple scales? Here, the PI presents a framework for a novel and highly flexible multi-scale approach, which uses Markov State Models (MSMs) as a framework for multi-scale simulation. Such multi-scale MSMs (or MSMSMs) can combine results from different simulation methodologies, with the expectation of getting the "best of both worlds", i.e. the accuracy of more detailed models and the computational tractability of simpler models. Moreover, MSMSMs present a natural, statistical framework for bringing together multiple simulation methodologies, predicting long timescale behavior from many shorter simulations, and describing and elucidating complex, heterogeneous dynamics. To test these methods, the PI will apply this model to the study of protein folding. There are several broader impacts of this work. First, if successful, The PI's methods could have very broad impact in molecular simulation in fields very far from just protein folding, since the issues of understanding which details are relevant and the use of simple vs complex models are present in essentially all fields of molecular simulation. Second, as the PI uses the Folding@home distributed computing platform for this project, there is a significant education and outreach component; the PI has pioneered several outreach aspects, including the use of YouTube videos, PlayStation 3, and large-scale distributed computing as outreach, and he proposes to continue that work with this project. This work has had the impact in making many people in the general public familiar with biology and chemistry at a sophisticated level, as many individuals participating in Folding@home wish to understand the simulations they are running. Moreover, the PI plans to expand these areas to incorporate means to engage underrepresented groups by direct interaction with teachers from local schools, building curricula and web pages to be put on our Folding@home web site. This project is jointly supported by Molecular Biophysics in the Division of Molecular and Cellular Biosciences and the Theory, Models and Computational Methods Program in the Chemistry Division.