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Bioinformatics Advance Access published online on June 9, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl282
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received April 14, 2006
Accepted May 29, 2006

Article

Application of the multiensemble sampling to the equilibrium folding of proteins

Hyeon S. Son 1, Seung-Yeon Kim 2, Jooyoung Lee 3, and Kyu-Kwang Han 4 *

1 Laboratory of Computational Biology and Bioinformatics, Institute of Health and Environment, Graduate School of Public Health, Seoul National University, Seoul 110-799, Korea
2 School of Computational Sciences, Korea Institute for Advanced Study, Seoul 130-722, Korea; Present address: Computer-Aided Molecular Design Research Center, Soongsil University, Seoul 156-743, Korea
3 School of Computational Sciences, Korea Institute for Advanced Study, Seoul 130-722, Korea
4 Department of Applied Physics, Pai Chai University, Daejeon 302-735, Korea

* To whom correspondence should be addressed.
Kyu-Kwang Han, E-mail: khan{at}mail.pcu.ac.kr


  Abstract

Motivation: Conventional Monte Carlo and molecular dynamics simulations of proteins in the canonical ensemble are of little use, because they tend to get trapped in states of energy local minima at low temperatures. One way to surmount this difficulty is to use a non-Boltzmann sampling method in which conformations are sampled upon a general weighting function instead of the conventional Boltzmann weighting function. The multiensemble sampling (MES) method is a non-Boltzmann sampling method that was originally developed to estimate free energy differences between systems with different potential energies and/or at different thermodynamic states. The method has not been yet applied to studies of complex molecular systems such as proteins.

Results: MES Monte Carlo simulations of small proteins have been carried out using a united-residue force field. The proteins at several temperatures from the unfolded to the folded states were simulated in a single MC run at a time and their equilibrium thermodynamic properties were calculated correctly. The distributions of sampled conformations clearly indicate that, when going through states of energy local minima, the MES simulation did not get trapped in them but escaped from them so quickly that all the relevant parts of conformation space could be sampled properly. A two-step folding process consisting of a collapse transition followed by a folding transition is observed. This study demonstrates that the use of MES alleviates the multiple-minima problem greatly.

Availability: Available on request from the authors.

Supplementary information: A FORTRAN90 code of MES algorithm for MC simulation and its sample input have been deposited as Supplimentary data available at Bioinformatics online.

Associate Editor: Martin Bishop
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