Application of the multiensemble sampling to the equilibrium folding of proteins.
BACKGROUND
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 yet been 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.


BACKGROUND
Available on request from the authors.
Son
Hyeon S
HS
Laboratory of Computational Biology and Bioinformatics, Institute of Health and Environment, Graduate School of Public Health, Seoul National University Seoul 110-799, Korea.
Kim
Seung-Yeon
SY
Lee
Jooyoung
J
Han
Kyu-Kwang
KK
D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D008956:Models, Chemical; D008958:Models, Molecular; D015233:Models, Statistical; D008969:Molecular Sequence Data; D009010:Monte Carlo Method; D009038:Motion; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D018401:Sample Size; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D013314:Stress, Mechanical
D011506:Proteins