TCBG Seminar

Adaptive Methods for Free Energy Computation and Coarse-graining Strategies

Professor Eric Darve
Mechanical Engineering Department
Stanford University
Palo Alto, CA

Monday, March 24, 2008
3:00 pm (CT)
3269 Beckman Institute

Abstract

Free energy computation is one of the main goals of molecular dynamics simulations. Numerically, these calculations are made difficult by the presence of free energy barriers separating meta-stable basins. Several methods have been developed to address this issue such as the adaptive biasing force (ABF), in which an external force is progressively adapted. Upon convergence, the reaction coordinate along which the free energy is computed exhibits a diffusive behavior in a flat free energy profile, leading to a rapid convergence of the computed averages and a rapid reduction of statistical errors. Such methods can serve as starting point for computing coarse grained models of large proteins in which the number of variables is greatly reduced. These models can potentially allow modeling the dynamics of proteins over very long time scales. A powerful coarse graining approach consists in computing stochastic differential equations which approximate the effect of the unresolved variables on the dynamics of the resolved variables. The Mori-Zwanzig projection is a key tool to rigorously derive such stochastic models. We will show the role free energy plays in calculating these models. In this case as well, ABF can be applied to yield faster convergence.


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