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Biophys. J. BioFAST: First Published February 29, 2008. doi:10.1529/biophysj.107.121665
© 2008 by the Biophysical Society.


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BIOPHYSICAL THEORY AND MODELING

Protein Unfolding Behavior Studied by Elastic Network Model

Ji Guo Su 1, Chun Hua Li 1, Rui Hao 2, Wei Zu Chen 1 and Cun Xin Wang 1*

1 Beijing University of Technology
2 Yanshan University

* To whom correspondence should be addressed. E-mail: cxwang{at}bjut.edu.cn.

Submitted on September 10, 2007
Revised on October 10, 2007
Accepted on 3 January 2008


   Abstract
Experimental and theoretical studies have showed that the native-state topology conceals a wealth of information about protein folding/unfolding. In the present study, a method based on the Gaussian network model (GNM) is developed to study some properties of protein unfolding and explore the role of topology in protein unfolding process. The Gaussian network model has been successful in predicting atomic fluctuations around an energy minimum. However, in the Gaussian network model, the normal mode description is linear and cannot be accurate in studying protein folding/unfolding, which has many local minima in the energy landscape. In order to describe the nonlinearity of the conformational changes during protein unfolding, a method based on the iterative use of normal mode calculation is proposed. The protein unfolding process is mimicked through breaking the native contacts between the residues one by one according to the fluctuations of the distance between them. With this approach, the unfolding processes of two proteins, CI2 and barnase, are simulated. It is found that the sequence of protein unfolding events revealed by this method is consistent with that obtained from thermal unfolding by molecular dynamics (MD) and Monte Carlo (MC) simulations. The results indicate that this method is effective in studying protein unfolding. In this method, only native contacts are considered, which implies that the native topology may play an important role in the protein unfolding process. The simulation results also show that the unfolding pathway is robust against the introduction of some noise, or stochastic characters. Furthermore, several conformations selected from the unfolding process are studied to show that the denatured state does not behave as a random coil, but seems to have highly cooperative motions, which may help and promote the polypeptide chain to fold into the native state correctly and speedily.

Key Words: CI2, Gaussian network model, barnase, nonlinearity of motions, protein unfolding, topology







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Copyright © 2008 by the Biophysical Society.