Novel Feature for Catalytic Protein Residues Reflecting Interactions with Other Residues

Yizhou Li; Gongbing Li; Zhining Wen; Hui Yin; Mei Hu; Jiamin Xiao; Menglong Li
March 2011
PLoS ONE;2011, Vol. 6 Issue 3, p1
Academic Journal
Owing to their potential for systematic analysis, complex networks have been widely used in proteomics. Representing a protein structure as a topology network provides novel insight into understanding protein folding mechanisms, stability and function. Here, we develop a new feature to reveal correlations between residues using a protein structure network. In an original attempt to quantify the effects of several key residues on catalytic residues, a power function was used to model interactions between residues. The results indicate that focusing on a few residues is a feasible approach to identifying catalytic residues. The spatial environment surrounding a catalytic residue was analyzed in a layered manner. We present evidence that correlation between residues is related to their distance apart: most environmental parameters of the outer layer make a smaller contribution to prediction; and (ii) catalytic residues tend to be located near key positions in enzyme folds. Feature analysis revealed satisfactory performance for our features, which were combined with several conventional features in a prediction model for catalytic residues using a comprehensive data set from the Catalytic Site Atlas. Values of 88.6% for sensitivity and 88.4% for specificity were obtained by 10-fold cross-validation. These results suggest that these features reveal the mutual dependence of residues and are promising for further study of structure-function relationship.


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