利用层次聚类探索蛋白质能量景观。
Exploring protein energy landscapes with hierarchical clustering.
作者信息
Gront Dominik, Hansmann Ulrich H E, Kolinski Andrzej
出版信息
Int J Quantum Chem. 2005;105(6):826-830. doi: 10.1002/qua.20741.
Abstract
In this work we present a new method for investigating local energy minima on a protein energy landscape. The CABS (CAlpha, CBeta and the center of mass of the Side chain) method was employed for generating protein models, but any other method could be used instead. Cα traces from an ensemble of models are hierarchical clustered with the HCPM (Hierarchical Clustering of Protein Models) method. The efficiency of this method for sampling and analyzing energy landscapes is shown.
摘要
在这项工作中，我们提出了一种研究蛋白质能量景观上局部能量最小值的新方法。采用CABS（Cα、Cβ和侧链质心）方法生成蛋白质模型，但也可以使用任何其他方法替代。来自一组模型的Cα轨迹通过HCPM（蛋白质模型层次聚类）方法进行层次聚类。展示了该方法在采样和分析能量景观方面的效率。
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本文引用的文献
1
Generalized protein structure prediction based on combination of fold-recognition with de novo folding and evaluation of models.
Proteins. 2005;61 Suppl 7:84-90. doi: 10.1002/prot.20723.
2
Optimal allocation of replicas in parallel tempering simulations.
J Chem Phys. 2005 Jan 8;122(2):024111. doi: 10.1063/1.1831273.
3
Protein modeling and structure prediction with a reduced representation.
Acta Biochim Pol. 2004;51(2):349-71.
4
An improved protein decoy set for testing energy functions for protein structure prediction.
Proteins. 2003 Oct 1;53(1):76-87. doi: 10.1002/prot.10454.
5
Clustering of low-energy conformations near the native structures of small proteins.
Proc Natl Acad Sci U S A. 1998 Sep 15;95(19):11158-62. doi: 10.1073/pnas.95.19.11158.
6
Energy functions that discriminate X-ray and near native folds from well-constructed decoys.
J Mol Biol. 1996 May 3;258(2):367-92. doi: 10.1006/jmbi.1996.0256.
7
Recognition of errors in three-dimensional structures of proteins.
Proteins. 1993 Dec;17(4):355-62. doi: 10.1002/prot.340170404.
8
Principles of protein folding--a perspective from simple exact models.
Protein Sci. 1995 Apr;4(4):561-602. doi: 10.1002/pro.5560040401.
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