Predicting experimental quantities in protein folding kinetics using stochastic roadmap simulation

Authors:
Tsung-Han Chiang;Mehmet Serkan Apaydin;Douglas L. Brutlag;David Hsu;Jean-Claude Latombe
Affiliations:
National University of Singapore, Singapore, Singapore;Dartmouth College, Hanover, NH;Stanford University, Stanford, CA;National University of Singapore, Singapore, Singapore;Stanford University, Stanford, CA
Venue:
RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
Year:
2006

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Abstract

This paper presents a new method for studying protein folding kinetics. It uses the recently introduced Stochastic Roadmap Simulation (SRS) method to estimate the transition state ensemble (TSE) and predict the rates and Φ-values for protein folding. The new method was tested on 16 proteins. Comparison with experimental data shows that it estimates the TSE much more accurately than an existing method based on dynamic programming. This leads to better folding-rate predictions. The results on Φ-value predictions are mixed, possibly due to the simple energy model used in the tests. This is the first time that results obtained from SRS have been compared against a substantial amount of experimental data. The success further validates the SRS method and indicates its potential as a general tool for studying protein folding kinetics.