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折叠识别方法。

Fold recognition methods.

作者信息

Godzik Adam

机构信息

Program in Bioinformatics and Biological Diversity, Burnham Institute, La Jolla, CA, USA.

出版信息

Methods Biochem Anal. 2003;44:525-46. doi: 10.1002/0471721204.ch26.

Abstract

We are still missing a basic understanding of sequence/structure/function relationships in proteins. Analogy-based prediction algorithms remain the only reliable fold prediction tools. New methods, such as threading and hybrid threading/sequence fold recognition, can often recognize even the most distant homologues and, in some cases, even unrelated proteins with similar overall structures. This knowledge pushed the envelope of analogy-based function analysis to the point that the majority of newly sequenced genomes can be tentatively assigned to already characterized protein superfamilies. However, at this evolutionary distance, fold prediction is no longer equivalent to function prediction. Instead of having the same exact function, distantly related proteins might share some functional analogy that is not obvious to the casual observer. The main challenge facing the fold recognition field is to develop tools to follow the structure prediction with function prediction and analysis.

摘要

我们仍然缺乏对蛋白质序列/结构/功能关系的基本理解。基于类比的预测算法仍然是唯一可靠的折叠预测工具。新的方法,如穿线法和混合穿线法/序列折叠识别法,常常能够识别出即使是最遥远的同源物,在某些情况下,甚至能识别出整体结构相似的非相关蛋白质。这些知识将基于类比的功能分析拓展到了这样一个程度,即大多数新测序的基因组可以初步归类到已表征的蛋白质超家族中。然而,在这种进化距离下,折叠预测不再等同于功能预测。远缘相关蛋白质可能并不具有完全相同的功能,而是可能共享一些功能上的相似性,这对于非专业观察者来说并不明显。折叠识别领域面临的主要挑战是开发工具以便在结构预测之后进行功能预测和分析。

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