Prediction of protein solvent accessibility using fuzzy k-nearest neighbor method
Prediction of protein solvent accessibility using fuzzy k-nearest neighbor method
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DOI：
10.1093/bioinformatics/bti423
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发表时间：
2005-06-15
期刊：
影响因子：
5.8
通讯作者：
Lee, J
中科院分区：
文献类型：
--
作者：
Sim, J;Kim, SY;Lee, J
动机：氨基酸残基的溶剂可及性在三级结构预测中起着重要作用，特别是在一个查询蛋白与已知结构没有显著序列相似性的情况下。尽管近年来的研究有所改进，但溶剂可及性预测的准确性仍低于二级结构预测。k近邻法是一种简单但功能强大的分类算法，虽然它经常用于生物和医学数据的分类，但从未应用于溶剂可及性的预测。结果：将模糊k近邻法应用于溶剂可及性预测，以PSI-BLAST剖面作为特征向量，预测精度较高。通过序列聚类构建的ASTRAL SCOP参考数据集的留一交叉验证，我们的方法对3状态（埋藏/中间/暴露）预测（埋藏/中间阈值为9%，中间/暴露阈值为36%）的准确率达到64.1%，对2状态（埋藏/暴露）预测（埋藏/暴露阈值分别为0、5、16和25%）的准确率分别达到86.7、82.0、79.0和78.5%。在RS126数据集和229种蛋白质的基准数据集上，我们的方法也比其他方法略微提高了2-5%的准确性。
Motivation: The solvent accessibility of amino acid residues plays an important role in tertiary structure prediction, especially in the absence of significant sequence similarity of a query protein to those with known structures. The prediction of solvent accessibility is less accurate than secondary structure prediction in spite of improvements in recent researches. The k-nearest neighbor method, a simple but powerful classification algorithm, has never been applied to the prediction of solvent accessibility, although it has been used frequently for the classification of biological and medical data. Results: We applied the fuzzy k-nearest neighbor method to the solvent accessibility prediction, using PSI-BLAST profiles as feature vectors, and achieved high prediction accuracies. With leave-one-out cross-validation on the ASTRAL SCOP reference dataset constructed by sequence clustering, our method achieved 64.1 % accuracy for a 3-state (buried/intermediate/exposed) prediction (thresholds of 9% for buried/intermediate and 36% for intermediate/exposed) and 86.7, 82.0, 79.0 and 78.5% accuracies for 2-state (buried/exposed) predictions (thresholds of each 0, 5, 16 and 25% for buried/exposed), respectively. Our method also showed slightly better accuracies than other methods by about 2-5% on the RS126 dataset and a bench-marking dataset with 229 proteins.