Simple but predictive protein models

被引:63
作者
Ding, F [1 ]
Dokholyan, NV [1 ]
机构
[1] Univ N Carolina, Sch Med, Dept Biochem & Biophys, Chapel Hill, NC 27599 USA
关键词
D O I
10.1016/j.tibtech.2005.07.001
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
The traditional approach to computational biophysics studies of molecular systems is brute force molecular dynamics simulations under the conditions of interest. The disadvantages of this approach are that the time and length scales that are accessible to computer simulations often do not reach biologically relevant scales. An alternative approach, which we call intuitive modeling, is hypothesis-driven and based on tailoring simplified protein models to the systems of interest. Using intuitive modeling, the length and time scales that can be achieved using simplified protein models exceed those of traditional molecular-dynamic simulations. Here, we describe several recent studies that signify the predictive power of simplified protein models within the intuitive-modeling approach.
引用
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页码:450 / 455
页数:6
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