Hirakawa H, Muta S, Kuhara S
Graduate School of Genetic Resources Technology, Kyushu University, Hakozaki, Higashi-ku, Fukuoka 812-8581, Japan.
Bioinformatics. 1999 Feb;15(2):141-8. doi: 10.1093/bioinformatics/15.2.141.
In the process of protein construction, buried hydrophobic residues tend to assemble in a core of a protein. Methods used to predict these cores involve use or no use of sequential alignment. In the case of a close homology, prediction was more accurate if sequential alignment was used. If the homology was weak, predictions would be unreliable. A hydrophobicity plot involving the hydropathy index is useful for purposes of prediction, and smoothing is essential. However, the proposed methods are insufficient. We attempted to predict hydrophobic cores with a low frequency extracted from the hydrophobicity plot, using wavelet analysis.
The cores were predicted at a rate of 68.7%, by cross-validation. Using wavelet analysis, the cores of non-homologous proteins can be predicted with close to 70% accuracy, without sequential alignment.
The program used in this study is available from Intergalactic Reality (http://www.intergalact.com).
在蛋白质构建过程中，埋藏的疏水残基倾向于聚集在蛋白质的核心区域。用于预测这些核心区域的方法涉及使用或不使用序列比对。在同源性较高的情况下，如果使用序列比对，预测会更准确。如果同源性较弱，预测将不可靠。涉及亲水性指数的疏水性图谱对于预测目的很有用，并且平滑处理至关重要。然而，现有的方法并不充分。我们尝试使用小波分析从疏水性图谱中提取低频信息来预测疏水核心区域。
通过交叉验证，核心区域的预测准确率为68.7%。使用小波分析，可以在不进行序列比对的情况下，以接近70%的准确率预测非同源蛋白质的核心区域。
本研究中使用的程序可从Intergalactic Reality（http://www.intergalact.com）获得。
