Suppr超能文献

从序列预测蛋白质功能的相关问题。

Issues in predicting protein function from sequence.

作者信息

Ponting C P

机构信息

Department of Human Anatomy and Genetics, University of Oxford, UK.

出版信息

Brief Bioinform. 2001 Mar;2(1):19-29. doi: 10.1093/bib/2.1.19.

Abstract

Identifying homologues, defined as genes that arose from a common evolutionary ancestor, is often a relatively straightforward task, thanks to recent advances made in estimating the statistical significance of sequence similarities found from database searches. The extent by which homologues possess similarities in function, however, is less amenable to statistical analysis. Consequently, predicting function by homology is a qualitative, rather than quantitative, process and requires particular care to be taken. This review focuses on the various approaches that have been developed to predict function from the scale of the atom to that of the organism. Similarities in homologues' functions differ considerably at each of these different scales and also vary for different domain families. It is argued that due attention should be paid to all available clues to function, including orthologue identification, conservation of particular residue types, and the co-occurrence of domains in proteins. Pitfalls in database searching methods arising from amino acid compositional bias and database size effects are also discussed.

摘要

识别同源物(即起源于共同进化祖先的基因)通常是一项相对简单的任务,这得益于近期在评估数据库搜索中发现的序列相似性的统计显著性方面所取得的进展。然而,同源物在功能上具有相似性的程度不太适合进行统计分析。因此,通过同源性预测功能是一个定性而非定量的过程,需要格外小心。本综述重点关注已开发出的从原子尺度到生物体尺度预测功能的各种方法。在这些不同尺度上,同源物功能的相似性差异很大,并且不同结构域家族也有所不同。有人认为,应充分关注所有可用的功能线索,包括直系同源物的鉴定、特定残基类型的保守性以及蛋白质中结构域的共现情况。还讨论了由氨基酸组成偏差和数据库大小效应导致的数据库搜索方法中的陷阱。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验