Computer Science

Predicting the folding pathway of engrailed homeodomain with a probabilistic roadmap enhanced reaction-path algorithm

Document Type

Article

Abstract

To predict a protein-folding pathway, we present an alternative to the time-consuming dynamic simulation of atomistic models. We replace the actual dynamic simulation with variational optimization of a reaction path connecting known initial and final protein conformations in such a way as to maximize an estimate of the reactive flux or minimize the mean first passage time at a given temperature, referred to as MaxFlux. We solve the MaxFlux global optimization problem with an efficient graph-theoretic approach, the probabilistic roadmap method (PRM). We employed CHARMM19 and the EEF1 implicit solvation model to describe the protein solution. The effectiveness of our MaxFlux-PRM is demonstrated in our promising simulation results on the folding pathway of the engrailed homeodomain. Our MaxFlux-PRM approach provides the direct evidence to support that the previously reported intermediate state is a genuine on-pathway intermediate, and the demand of CPU power is moderate. © 2008 by the Biophysical Society.

Publication Title

Biophysical Journal

Publication Date

2008

Volume

94

Issue

5

First Page

1622

Last Page

1629

ISSN

0006-3495

DOI

10.1529/biophysj.107.119214

Keywords

algorithms, computational biology, computer simulation, protein folding, proteins chemistry, forecasting, models, statistical, probability, protein binding, protein conformation, solutions chemistry, temperature

APA Citation

Li, D. W., Yang, H., Han, L., & Huo, S. (2008). Predicting the folding pathway of engrailed homeodomain with a probabilistic roadmap enhanced reaction-path algorithm. Biophysical journal, 94(5), 1622-1629.

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