Analysis of the distributed computing approach applied to the folding of a small β peptide

TitleAnalysis of the distributed computing approach applied to the folding of a small β peptide
Publication TypeJournal Article
Year of Publication2003
AuthorsPaci E., Cavalli A., Vendruscolo M., Caflisch A.
JournalProceedings of the National Academy of Sciences of the United States of America
Volume100
Issue14
Pagination8217-8222
Date Published2003 Jul 8
Type of ArticleResearch Article
ISSN0027-8424
KeywordsComputer Simulation, Models, Molecular, Peptides, Protein Denaturation, Protein Folding, Protein Structure, Secondary, Solvents, Stochastic Processes, Time Factors
Abstract

In the recently proposed distributed computing approach to protein folding a very large number of short independent simulations is performed. Using this method, folding events on a time scale orders of magnitude shorter than the experimental one have been reported. However, it has also been observed that the folding process is not an elementary kinetic step and that the presence of initial lag phases can bias short simulations toward atypical pathways. We study here a 20-residue three-stranded antiparallel β-sheet peptide whose equilibrium properties can be characterized by atomistic molecular dynamics simulations. We found that the folding rate of this peptide is estimated correctly by the distributed computing approach when trajectories > approximately 1/100 of the equilibrium folding time are considered. We also found that the fastest folding events occur through high-energy pathways, which are unlikely under equilibrium conditions. These very fast folding pathways do not relax within the equilibrium denatured state that is stabilized by the transient presence of both native and non-native interactions, and they are characterized by the nearly simultaneous formation of the two β-hairpins and a very small number of non-native contacts.

DOI10.1073/pnas.1331838100
pubindex

0048

Alternate JournalProc. Natl. Acad. Sci. U.S.A.
PubMed ID12815104
PubMed Central IDPMC166209
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