期刊
JOURNAL OF COMPUTATIONAL CHEMISTRY
卷 24, 期 12, 页码 1432-1436出版社
WILEY
DOI: 10.1002/jcc.10297
关键词
protein folding; Langevin dynamics; distributed computing; solvent viscosity; folding rate
资金
- NIGMS NIH HHS [IP20 GM64782-01, R01GM62868-01A2] Funding Source: Medline
By using distributed computing techniques and a supercluster of more than 20,000 processors we simulated folding of a 20-residue Trp Cage miniprotein in atomistic detail with implicit GB/SA solvent at a variety of solvent viscosities (gamma). This allowed us to analyze the dependence of folding rates on viscosity. In particular, we focused on the low-viscosity regime (values below the viscosity of water). In accordance with Kramers' theory, we observe approximately linear dependence of the folding rate on 1/gamma for values from 1-10(-1)x that of water viscosity. However, for the regime between 10(-4)-10(-1)x that of water viscosity we observe power-law dependence of the form k similar to y(-1/5). These results suggest that estimating folding rates from molecular simulations run at low viscosity under the assumption of linear dependence of rate on inverse viscosity may lead to erroneous results. (C) 2003 Wiley Periodicals, Inc.
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