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FINDSITE:一种基于进化与结构相结合的蛋白质功能预测方法。

FINDSITE: a combined evolution/structure-based approach to protein function prediction.

作者信息

Skolnick Jeffrey, Brylinski Michal

机构信息

Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology 250 14th St NW, Atlanta, GA 30318, USA.

出版信息

Brief Bioinform. 2009 Jul;10(4):378-91. doi: 10.1093/bib/bbp017. Epub 2009 Mar 26.

Abstract

A key challenge of the post-genomic era is the identification of the function(s) of all the molecules in a given organism. Here, we review the status of sequence and structure-based approaches to protein function inference and ligand screening that can provide functional insights for a significant fraction of the approximately 50% of ORFs of unassigned function in an average proteome. We then describe FINDSITE, a recently developed algorithm for ligand binding site prediction, ligand screening and molecular function prediction, which is based on binding site conservation across evolutionary distant proteins identified by threading. Importantly, FINDSITE gives comparable results when high-resolution experimental structures as well as predicted protein models are used.

摘要

后基因组时代的一项关键挑战是确定给定生物体中所有分子的功能。在此,我们综述了基于序列和结构的蛋白质功能推断及配体筛选方法的现状,这些方法可为平均蛋白质组中约50%未分配功能的开放阅读框(ORF)中的很大一部分提供功能见解。然后,我们描述了FINDSITE,这是一种最近开发的用于配体结合位点预测、配体筛选和分子功能预测的算法,它基于通过穿线法鉴定的进化距离较远的蛋白质间的结合位点保守性。重要的是,当使用高分辨率实验结构以及预测的蛋白质模型时,FINDSITE能给出可比的结果。

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