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基于氨基酸序列的蛋白质二级结构预测方法评估

An assessment of protein secondary structure prediction methods based on amino acid sequence.

作者信息

Argos P, Schwarz J, Schwarz J

出版信息

Biochim Biophys Acta. 1976 Aug 9;439(2):261-73. doi: 10.1016/0005-2795(76)90062-3.

DOI:10.1016/0005-2795(76)90062-3
PMID:952963
Abstract

Five of the several secondary structure prediction methods based on protein amino acid sequence has been computerized, allowing the calculation of joint prediction histograms which have been shown to be superior to any individual prediction. The known structures of about 40 proteins experimentally determined by X-ray crystallography are compared with the predictions resulting from calculated histograms. The accuracy of the predictions for helices is generally much better than for both beta-sheet regions and for turns. The overall agreement between prediction and observation within the amino terminal half of the protein molecules is clearly superior to that for the carboxyl half, suggesting an amino nucleating core. Predictions for smaller proteins and thermally stable proteins are generally good, indicating the sensitivity of the methods to short-range but not long-range interactions. In less than half the cases tested were the predictions useful; there was no way of knowing ahead of time if a favorable prediction would result. Given the lack of dramatic improvement with an increase in data base for the schemes and the generally poor agreement factors, it appears that a perfect predictive algorithm must include a consideration of energy minimization, thermalization, and long-range interactions. Extreme caution is suggested in applying present prediction routines to unknown protein structures.

摘要

基于蛋白质氨基酸序列的几种二级结构预测方法中的五种已实现计算机化,可计算联合预测直方图,结果表明该直方图优于任何单一预测。将通过X射线晶体学实验测定的约40种蛋白质的已知结构与计算直方图得出的预测结果进行比较。对螺旋结构的预测准确性通常比对β折叠区域和转角的预测要好得多。蛋白质分子氨基末端一半内预测与观察结果的总体一致性明显优于羧基末端一半,表明存在氨基成核核心。对较小蛋白质和热稳定蛋白质的预测通常较好,这表明该方法对短程而非长程相互作用敏感。在不到一半的测试案例中,预测是有用的;无法提前知道是否会得到有利的预测结果。鉴于随着方案数据库的增加没有显著改进且总体一致性因素普遍较差,似乎完美的预测算法必须考虑能量最小化、热化和长程相互作用。在将当前的预测程序应用于未知蛋白质结构时建议极度谨慎。

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