Probing protein fold space with a simplified model

被引:32
作者
Minary, Peter [1 ]
Levitt, Michae [1 ]
机构
[1] Stanford Univ, Dept Biol Struct, Sch Med, Stanford, CA 94305 USA
基金
美国国家卫生研究院;
关键词
coarse-grained statistical potentials; protein fold space; near-native energy landscape; multicanonical sampling; multidimensional scaling;
D O I
10.1016/j.jmb.2007.10.087
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
We probe the stability and near-native energy landscape of protein fold space using powerful conformational sampling methods together with simple reduced models and statistical potentials. Fold space is represented by a set of 280 protein domains spanning all topological classes and having a wide range of lengths (33-300 residues) amino acid composition and number of secondary structural elements. The degrees of freedom are taken as the loop torsion angles. This choice preserves the native secondary structure but allows the tertiary structure to change. The proteins are represented by three-point per residue, three-dimensional models with statistical potentials derived from a knowledge-based study of known protein structures. When this space is sampled by a combination of parallel tempering and equi-energy Monte Carlo, we find that the three-point model captures the known stability of protein native structures with stable energy basins that are near-native (all alpha: 4.77 angstrom, all beta: 2.93 angstrom, alpha/beta: 3.09 angstrom, alpha+beta: 4.89 angstrom on average and within 6 angstrom for 71.41%, 92.85%, 94.29% and 64.28% for all-alpha, all-beta, alpha/beta and alpha+beta, classes, respectively). Denatured structures also occur and these have interesting structural properties that shed light on the different landscape characteristics of alpha and beta folds. We find that alpha/beta proteins with alternating alpha and beta segments (such as the beta-barrel) are more stable than proteins in other fold classes. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:920 / 933
页数:14
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