Computing the transition state populations in simple protein models

Sefika Ozkan, Ken A. Dill, Ivet Bahar

Research output: Contribution to journalArticle

42 Citations (Scopus)

Abstract

We describe the master equation method for computing the kinetics of protein folding. We illustrate the method using a simple Go model. Presently most models of two-state fast-folding protein folding kinetics invoke the classical idea of a transition state to explain why there is a single exponential decay in time. However, if proteins fold via funnel-shaped energy landscapes, as predicted by many theoretical studies, then it raises the question of what is the transition state. Is it a specific structure, or a small ensemble of structures, as is expected from classical transition state theory? Or is it more like the denatured states of proteins, a very broad ensemble? The answer that is usually obtained depends on the assumptions made about the transition state. The present method is a rigorous way to find transition states, without assumptions or approximations, even for very nonclassical shapes of energy landscapes. We illustrate the method here, showing how the transition states in two-state protein folding can be very broad ensembles.

Original languageEnglish (US)
Pages (from-to)35-46
Number of pages12
JournalBiopolymers
Volume68
Issue number1
DOIs
StatePublished - Jan 2003
Externally publishedYes

Fingerprint

Protein folding
Protein Folding
Proteins
Population
Kinetics
Theoretical Models

Keywords

  • Go model
  • Kinetics of protein folding
  • Master equation method
  • Transition state
  • Two-state fast-folding

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Biochemistry
  • Biophysics

Cite this

Computing the transition state populations in simple protein models. / Ozkan, Sefika; Dill, Ken A.; Bahar, Ivet.

In: Biopolymers, Vol. 68, No. 1, 01.2003, p. 35-46.

Research output: Contribution to journalArticle

Ozkan, Sefika ; Dill, Ken A. ; Bahar, Ivet. / Computing the transition state populations in simple protein models. In: Biopolymers. 2003 ; Vol. 68, No. 1. pp. 35-46.
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