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Identification of the protein folding transition state from molecular dynamics trajectories


Muff, S; Caflisch, A (2009). Identification of the protein folding transition state from molecular dynamics trajectories. Journal of Chemical Physics, 130(12):125104.

Abstract

The rate of protein folding is governed by the transition state so that a detailed characterization of its structure is essential for understanding the folding process. In vitro experiments have provided a coarse-grained description of the folding transition state ensemble (TSE) of small proteins. Atomistic details could be obtained by molecular dynamics (MD) simulations but it is not straightforward to extract the TSE directly from the MD trajectories, even for small peptides. Here, the structures in the TSE are isolated by the cut-based free-energy profile (cFEP) using the network whose nodes and links are configurations sampled by MD and direct transitions among them, respectively. The cFEP is a barrier-preserving projection that does not require arbitrarily chosen progress variables. First, a simple two-dimensional free-energy surface is used to illustrate the successful determination of the TSE by the cFEP approach and to explain the difficulty in defining boundary conditions of the Markov state model for an entropically stabilized free-energy minimum. The cFEP is then used to extract the TSE of a beta-sheet peptide with a complex free-energy surface containing multiple basins and an entropic region. In contrast, Markov state models with boundary conditions defined by projected variables and conventional histogram-based free-energy profiles are not able to identify the TSE of the beta-sheet peptide.

Abstract

The rate of protein folding is governed by the transition state so that a detailed characterization of its structure is essential for understanding the folding process. In vitro experiments have provided a coarse-grained description of the folding transition state ensemble (TSE) of small proteins. Atomistic details could be obtained by molecular dynamics (MD) simulations but it is not straightforward to extract the TSE directly from the MD trajectories, even for small peptides. Here, the structures in the TSE are isolated by the cut-based free-energy profile (cFEP) using the network whose nodes and links are configurations sampled by MD and direct transitions among them, respectively. The cFEP is a barrier-preserving projection that does not require arbitrarily chosen progress variables. First, a simple two-dimensional free-energy surface is used to illustrate the successful determination of the TSE by the cFEP approach and to explain the difficulty in defining boundary conditions of the Markov state model for an entropically stabilized free-energy minimum. The cFEP is then used to extract the TSE of a beta-sheet peptide with a complex free-energy surface containing multiple basins and an entropic region. In contrast, Markov state models with boundary conditions defined by projected variables and conventional histogram-based free-energy profiles are not able to identify the TSE of the beta-sheet peptide.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Department of Biochemistry
07 Faculty of Science > Department of Biochemistry
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:27 March 2009
Deposited On:07 Apr 2009 09:50
Last Modified:20 May 2016 09:35
Publisher:American Institute of Physics
ISSN:0021-9606
Additional Information:Copyright 2009 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in Identification of the protein folding transition state from molecular dynamics trajectories and may be found at http://scitation.aip.org/getpdf/servlet/GetPDFServlet?filetype=pdf&id=JCPSA6000130000012125104000001&idtype=cvips&prog=normal
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1063/1.3099705
Related URLs:http://scitation.aip.org/getpdf/servlet/GetPDFServlet?filetype=pdf&id=JCPSA6000130000012125104000001&idtype=cvips&prog=normal (Publisher)
PubMed ID:19334897

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