A high-accuracy protein structural class prediction algorithm using predicted secondary structural information

作者：Liu, Tian; Jia, Cangzhi^*

来源：Journal of Theoretical Biology, 2010, 267(3): 272-275.

DOI：10.1016/j.jtbi.2010.09.007

• Protein structural class prediction
• Secondary structure
• Alternating frequency
• Parallel and anti-parallel beta-sheets
• Support vector machine

One major problem with the existing algorithm for the prediction of protein structural classes is low accuracies for proteins from alpha/beta and alpha+beta classes. In this study, three novel features were rationally designed to model the differences between proteins from these two classes. In combination with other rational designed features, an 11-dimensional vector prediction method was proposed. By means of this method, the overall prediction accuracy based on 25PDB dataset was 1.5% higher than the previous best-performing method, MODAS. Furthermore, the prediction accuracy for proteins from alpha+beta class based on 25PDB dataset was 5% higher than the previous best-performing method, SCPRED. The prediction accuracies obtained with the D675 and FC699 datasets were also improved.

• 出版日期2010-12-7
• 单位大连理工大学; 东北大学