title: Prediction of S-nitrosylation modification sites based on kernel sparse representation classification and mRMR algorithm.
abstract: Protein S-nitrosylation plays a very important role in a wide variety of cellular biological activities. Hitherto, accurate prediction of S-nitrosylation sites is still of great challenge. In this paper, we presented a framework to computationally predict S-nitrosylation sites based on kernel sparse representation classification and minimum Redundancy Maximum Relevance algorithm. As much as 666 features derived from five categories of amino acid properties and one protein structure feature are used for numerical representation of proteins. A total of 529 protein sequences collected from the open-access databases and published literatures are used to train and test our predictor. Computational results show that our predictor achieves Matthews' correlation coefficients of 0.1634 and 0.2919 for the training set and the testing set, respectively, which are better than those of k-nearest neighbor algorithm, random forest algorithm, and sparse representation classification algorithm. The experimental results also indicate that 134 optimal features can better represent the peptides of protein S-nitrosylation than the original 666 redundant features. Furthermore, we constructed an independent testing set of 113 protein sequences to evaluate the robustness of our predictor. Experimental result showed that our predictor also yielded good performance on the independent testing set with Matthews' correlation coefficients of 0.2239.
authors.affiliation: Institute of Systems Biology, Shanghai University, Shanghai 200444, China ; Department of Mathematics, Shaoyang University, Shaoyang, Hunan 422000, China.
authors.forename: Guohua
authors.initials: G
authors.lastname: Huang
authors.affiliation: School of Biomedical Engineering, Shanghai Jiaotong University, Shanghai 200240, China.
authors.forename: Lin
authors.identifier: 0000-0001-7743-7022
authors.initials: L
authors.lastname: Lu
authors.affiliation: Shanghai Center for Bioinformation Technology, Shanghai 200235, China.
authors.forename: Kaiyan
authors.initials: K
authors.lastname: Feng
authors.affiliation: School of Biomedical Engineering, Shanghai Jiaotong University, Shanghai 200240, China.
authors.forename: Jun
authors.identifier: 0000-0002-3539-2249
authors.initials: J
authors.lastname: Zhao
authors.affiliation: Graduate School of the Chinese Academy of Sciences, Beijing 100049, China ; State Key Laboratory of Medical Genomics, Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
authors.forename: Yuchao
authors.identifier: 0000-0002-8289-3003
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: East China Normal University Software Engineering Institute, Shanghai 200062, China.
authors.forename: Yaochen
authors.initials: Y
authors.lastname: Xu
authors.affiliation: Department of Biomedical Engineering, Tianjin University, Tianjin Key Lab of BME Measurement, Tianjin 300072, China.
authors.forename: Ning
authors.initials: N
authors.lastname: Zhang
authors.affiliation: Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
authors.forename: Bi-Qing
authors.identifier: 0000-0002-1656-7744
authors.initials: BQ
authors.lastname: Li
authors.affiliation: Department of Mathematics, Shaoyang University, Shaoyang, Hunan 422000, China.
authors.forename: Weiping
authors.initials: W
authors.lastname: Huang
authors.affiliation: Institute of Systems Biology, Shanghai University, Shanghai 200444, China.
authors.forename: Yu-Dong
authors.initials: YD
authors.lastname: Cai
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry / Q000235:genetics; D019295:Computational Biology; D030562:Databases, Protein; D011499:Protein Processing, Post-Translational; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D012984:Software
chemical_list: D000596:Amino Acids; D011506:Proteins