Hydrophobic cluster analysis at protein and proteome scales.

Isabelle Callebaut, Jean-Paul Mornon
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引用次数: 0

Abstract

Hydrophobic Cluster Analysis (HCA) adds secondary structure information to the analysis of protein amino acid sequence. Focusing on the elementary building blocks of protein folds, this approach has proved to be a powerful tool for detecting distant (hidden) relationships between proteins. At a time when huge masses of data are now available, both in terms of protein sequences and models of three-dimensional structures, it still constitutes a relevant tool for analyzing structural features at the scale of whole proteomes, enabling, among other things, to characterize the continuum between disorder and order and to explore the characteristics of protein dark matter. The aim of this mini-review is to provide a brief overview of this approach, describing its principles and achievements, recent developments and future prospects.

蛋白质和蛋白质组尺度上的疏水聚类分析。
疏水聚类分析(HCA)为蛋白质氨基酸序列分析增加了二级结构信息。专注于蛋白质折叠的基本构建块,这种方法已被证明是检测蛋白质之间遥远(隐藏)关系的强大工具。在蛋白质序列和三维结构模型方面的大量数据可供使用的时候,它仍然是分析整个蛋白质组的结构特征的相关工具,在其他方面,能够表征无序和有序之间的连续体,并探索蛋白质暗物质的特征。这篇小型综述的目的是简要概述这一方法,描述其原则和成就、最近的发展和未来前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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