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蛋白质折叠识别的成功度量。

A measure of success in fold recognition.

作者信息

Marchler-Bauer A, Bryant S H

机构信息

Computational Biology Branch, National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894, USA.

出版信息

Trends Biochem Sci. 1997 Jul;22(7):236-40. doi: 10.1016/s0968-0004(97)01078-5.

Abstract

Prediction of protein structure by fold recognition, or threading, was recently put to the test in a 'blind' structure prediction experiment, CASP2. Thirty-two teams from around the world participated, preparing predictions for 22 different 'target' proteins whose structures were soon to be determined. As experimental structures became available, we, as organizers of the threading competition, computed objective measures of fold-recognition specificity and model accuracy, to identify and characterize successful predictions. Here, we present a brief summary of these prediction evaluations, a tally of 'correct' predictions and a discussion of factors associated with correct predictions. We find that threading produced specific recognition and accurate models whenever the structural database contained a template spanning a large fraction of target sequence. Presence of conserved sequence motifs was helpful, but not required, and it would appear that threading can succeed whenever similarity to a known structure is sufficiently extensive.

摘要

通过折叠识别或穿线法预测蛋白质结构,最近在一次“盲测”结构预测实验——CASP2中接受了检验。来自世界各地的32个团队参与其中,针对22种不同的“目标”蛋白质进行预测,而这些蛋白质的结构即将被确定。随着实验结构的可得,作为穿线法竞赛的组织者,我们计算了折叠识别特异性和模型准确性的客观指标,以识别并描述成功的预测。在此,我们简要总结这些预测评估、“正确”预测的统计以及与正确预测相关因素的讨论。我们发现,只要结构数据库中包含跨越目标序列很大一部分的模板,穿线法就能产生特异性识别和准确的模型。保守序列基序的存在是有帮助的,但并非必需,而且似乎只要与已知结构的相似性足够广泛,穿线法就能成功。

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