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蛋白质柔性预测的准确性。

Accuracy of protein flexibility predictions.

作者信息

Vihinen M, Torkkila E, Riikonen P

机构信息

Department of Biochemistry, University of Turku, Finland.

出版信息

Proteins. 1994 Jun;19(2):141-9. doi: 10.1002/prot.340190207.

DOI:10.1002/prot.340190207
PMID:8090708
Abstract

Protein structural flexibility is important for catalysis, binding, and allostery. Flexibility has been predicted from amino acid sequence with a sliding window averaging technique and applied primarily to epitope search. New prediction parameters were derived from 92 refined protein structures in an unbiased selection of the Protein Data Bank by developing further the method of Karplus and Schulz (Naturwissenschaften 72:212-213, 1985). The accuracy of four flexibility prediction techniques was studied by comparing atomic temperature factors of known three-dimensional protein structures to predictions by using correlation coefficients. The size of the prediction window was optimized for each method. Predictions made with our new parameters, using an optimized window size of 9 residues in the prediction window, were giving the best results. The difference from another previously used technique was small, whereas two other methods were much poorer. Applicability of the predictions was also tested by searching for known epitopes from amino acid sequences. The best techniques predicted correctly 20 of 31 continuous epitopes in seven proteins. Flexibility parameters have previously been used for calculating protein average flexibility indices which are inversely correlated to protein stability. Indices with the new parameters showed better correlation to protein stability than those used previously; furthermore they had relationship even when the old parameters failed.

摘要

蛋白质结构灵活性对于催化、结合和变构作用至关重要。通过滑动窗口平均技术从氨基酸序列预测灵活性,并主要应用于表位搜索。通过进一步发展卡尔普斯和舒尔茨的方法(《自然科学》72:212 - 213, 1985),从蛋白质数据库的无偏选择中的92个精制蛋白质结构中得出了新的预测参数。通过使用相关系数将已知三维蛋白质结构的原子温度因子与预测结果进行比较,研究了四种灵活性预测技术的准确性。针对每种方法优化了预测窗口的大小。使用我们的新参数进行预测,预测窗口中优化的窗口大小为9个残基,得到了最佳结果。与另一种先前使用的技术的差异很小,而另外两种方法则差得多。还通过从氨基酸序列中搜索已知表位来测试预测的适用性。最佳技术正确预测了七种蛋白质中31个连续表位中的20个。灵活性参数先前已用于计算与蛋白质稳定性呈负相关的蛋白质平均灵活性指数。使用新参数的指数与蛋白质稳定性的相关性比先前使用的指数更好;此外,即使旧参数不适用时它们也有关系。

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