关键词: 蛋白质棕榈酰化位点, [k]-spaced氨基酸对组分, 位置特异性得分矩阵, 支持向量机, 递归特征消除

Abstract: Protein palmitoylation is reversible post-translational modification and plays important roles in protein stability, subcellular localization and many other functions. In this study, a new model to identify palmitoylation sites is constructed, designated as PSSM-CKSAAP-RFE. The evolutionary information of amino acid residues involved in tested proteins is represented by a Composition of k-Spaced Amino Acid Pairs（CKSAAP） method. Optional features are selected using a Recursive Feature Elimination（RFE） method. The Support Vector Machine（SVM） classifier is trained using the chosen features, and the performance of the model is examined using a Jackknife Cross Validation Test（JCVT）. The resulting data shows that the values of accuracy, Matthews correlation coefficient, specificity, sensitivity and area under receiver operating characteristic curves（AUC） for the identification of palmitoylation sites are 98. 44%, 0.94, 98.95%, 95.65% and 0.990, as well as 98.41%, 0.93, 99.39%, 92.31% and 0.994 for the train dataset and test dataset, respectively, which are superior to previous methods in the literature. This study provides a new model for the identification of palmitoylation sites of proteins.

Key words: protein palmitoylation sites, composition of k-spaced amino acid pairs, position specific scoring matrix, support vector machine, recursive feature elimination