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跨膜螺旋预测:比较评估与分析

Transmembrane helix prediction: a comparative evaluation and analysis.

作者信息

Cuthbertson Jonathan M, Doyle Declan A, Sansom Mark S P

机构信息

Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, UK.

出版信息

Protein Eng Des Sel. 2005 Jun;18(6):295-308. doi: 10.1093/protein/gzi032. Epub 2005 Jun 2.

Abstract

The prediction of transmembrane (TM) helices plays an important role in the study of membrane proteins, given the relatively small number (approximately 0.5% of the PDB) of high-resolution structures for such proteins. We used two datasets (one redundant and one non-redundant) of high-resolution structures of membrane proteins to evaluate and analyse TM helix prediction. The redundant (non-redundant) dataset contains structure of 434 (268) TM helices, from 112 (73) polypeptide chains. Of the 434 helices in the dataset, 20 may be classified as 'half-TM' as they are too short to span a lipid bilayer. We compared 13 TM helix prediction methods, evaluating each method using per segment, per residue and termini scores. Four methods consistently performed well: SPLIT4, TMHMM2, HMMTOP2 and TMAP. However, even the best methods were in error by, on average, about two turns of helix at the TM helix termini. The best and worst case predictions for individual proteins were analysed. In particular, the performance of the various methods and of a consensus prediction method, were compared for a number of proteins (e.g. SecY, ClC, KvAP) containing half-TM helices. The difficulties of predicting half-TM helices suggests that current prediction methods successfully embody the two-state model of membrane protein folding, but do not accommodate a third stage in which, e.g., short helices and re-entrant loops fold within a bundle of stable TM helices.

摘要

鉴于膜蛋白的高分辨率结构数量相对较少(约占蛋白质数据银行的0.5%),跨膜(TM)螺旋的预测在膜蛋白研究中起着重要作用。我们使用了两个膜蛋白高分辨率结构数据集(一个冗余数据集和一个非冗余数据集)来评估和分析TM螺旋预测。冗余(非冗余)数据集包含来自112(73)条多肽链的434(268)个TM螺旋的结构。数据集中的434个螺旋中,有20个可能被归类为“半TM”,因为它们太短,无法跨越脂质双层。我们比较了13种TM螺旋预测方法,使用每段、每个残基和末端得分来评估每种方法。有四种方法始终表现良好:SPLIT4、TMHMM2、HMMTOP2和TMAP。然而,即使是最好的方法,在TM螺旋末端平均也会有大约两圈螺旋的误差。分析了单个蛋白质的最佳和最差预测情况。特别是,比较了多种方法和一种共识预测方法对一些含有半TM螺旋的蛋白质(如SecY、ClC、KvAP)的性能。预测半TM螺旋的困难表明,当前的预测方法成功地体现了膜蛋白折叠的两态模型,但没有考虑到第三阶段,例如短螺旋和折返环在一束稳定的TM螺旋内折叠的情况。

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