西西弗斯与蛋白质结构预测。

B Rost, S O'Donoghue
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引用次数: 53

摘要

尽管经过了三十多年的深入研究,从序列预测蛋白质结构的问题仍然没有得到根本性的解决。然而,三维(3D)、二维和一维预测的新方法重新打开了这一领域。来自蛋白质数据库的平均力电位可以区分正确和不正确的模型(3D)。残基间接触(2D)可以通过分析相关突变来检测,尽管精度较低。利用多重序列比对,二级结构、溶剂可及性和跨膜螺旋(1D)可以显著提高预测精度。其中一些新的预测方法已被证明足够准确和可靠,可用于基因组分析和实验结构确定。此外,新一代理论方法对分子生物学实验的影响越来越大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sisyphus and prediction of protein structure.

The problem of predicting protein structure from the sequence remains fundamentally unsolved despite more than three decades of intensive research effort. However, new and promising methods in three-dimensional (3D), 2D and 1D prediction have reopened the field. Mean-force-potentials derived from the protein databases can distinguish between correct and incorrect models (3D). Inter-residue contacts (2D) can be detected by analysis of correlated mutations, albeit with low accuracy. Secondary structure, solvent accessibility and transmembrane helices (1D) can be predicted with significantly improved accuracy using multiple sequence alignments. Some of these new prediction methods have proven accurate and reliable enough to be useful in genome analysis, and in experimental structure determination. Moreover, the new generation of theoretical methods is increasingly influencing experiments in molecular biology.

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