**************** The 10th., Lab Seminar ****************************

Title: Multidimensional Langevin modeling of biomolecular dynamics

Speaker: Takuya Okamoto

Date: Thu. Oct. 14th, 2:30 pm

Abstract:
A systematic computational approach to describe the conformational
dynamics of biomolecules in reduced dimensionality is presented. The
method is based on (i) the decomposition of a high-dimensional molecular
dynamics trajectory into a few "system" and (many) "bath" degrees of
freedom and (ii) a Langevin simulation of the resulting model. Employing
principal component analysis, the dimension of the system is chosen such
that it contains all slow large-amplitude motions of the molecule, while the
bath coordinates only account for its high-frequency fluctuations. It is
shown that a sufficiently large dimension of the model is essential to
ensure a clear time scale separation of system and bath variables, which
warrants the validity of the memory-free Langevin equation. Applying
methods from nonlinear time series analysis, a practical Langevin algorithm
is presented which performs a local estimation of the multidimensional
Langevin vector fields describing deterministic drift and stochastic
driving.
Adopting a 800 ns molecular dynamics simulation of the folding of
heptaalanine in explicit water, it is shown that a five-dimensional Langevin
model correctly reproduces the structure and conformational dynamics of
the system. The virtues and limits of the approach are discussed in some
detail.

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