College of Sciences, Inner Mongolia University of Technology, Hohhot 010051, PR China.
J Theor Biol. 2011 Oct 7;286(1):24-30. doi: 10.1016/j.jtbi.2011.07.001. Epub 2011 Jul 19.
Protein secondary structure prediction is an intermediate step in the overall process of tertiary structure prediction. β-turns are important components of the secondary structure of a protein. Development of an accurate method of prediction of β-turn types would be helpful for predicting the overall tertiary structure of proteins. In this work, we constructed a database of 2805 protein chains. Our work improved the previous input parameters and used the support vector machine algorithm to predict the β-turn types; we obtained the overall prediction accuracy of 98.1%, 96.0%, 96.1%, 98.7%, 99.1%, 86.8%, 99.2% and 73.2% with the Matthews Correlation Coefficient values of 0.398, 0.460, 0.043, 0.463, 0.355, 0.172, 0.109 and 0.247, respectively, for types I, II, VIII, I', II', IV, VI and non-β-turn, respectively. In addition, we also used same method to predict the β-turn types in three databases of 426, 547 and 823 protein chains and found that our prediction results were better than other predictions.
蛋白质二级结构预测是三级结构预测整体过程中的一个中间步骤。β-转角是蛋白质二级结构的重要组成部分。开发一种准确的β-转角类型预测方法将有助于预测蛋白质的整体三级结构。在这项工作中，我们构建了一个包含 2805 条蛋白质链的数据库。我们的工作改进了先前的输入参数，并使用支持向量机算法来预测β-转角类型；我们获得了整体预测准确率为 98.1%、96.0%、96.1%、98.7%、99.1%、86.8%、99.2%和 73.2%，马氏相关系数值分别为 0.398、0.460、0.043、0.463、0.355、0.172、0.109 和 0.247，分别对应类型 I、II、VIII、I'、II'、IV、VI 和非-β-转角。此外，我们还使用相同的方法预测了三个包含 426、547 和 823 条蛋白质链的数据库中的β-转角类型，发现我们的预测结果优于其他预测。
