title: iSuc-PseOpt: Identifying lysine succinylation sites in proteins by incorporating sequence-coupling effects into pseudo components and optimizing imbalanced training dataset.
abstract: Succinylation is a posttranslational modification (PTM) where a succinyl group is added to a Lys (K) residue of a protein molecule. Lysine succinylation plays an important role in orchestrating various biological processes, but it is also associated with some diseases. Therefore, we are challenged by the following problem from both basic research and drug development: given an uncharacterized protein sequence containing many Lys residues, which one of them can be succinylated, and which one cannot? With the avalanche of protein sequences generated in the postgenomic age, the answer to the problem has become even more urgent. Fortunately, the statistical significance experimental data for succinylated sites in proteins have become available very recently, an indispensable prerequisite for developing a computational method to address this problem. By incorporating the sequence-coupling effects into the general pseudo amino acid composition and using KNNC (K-nearest neighbors cleaning) treatment and IHTS (inserting hypothetical training samples) treatment to optimize the training dataset, a predictor called iSuc-PseOpt has been developed. Rigorous cross-validations indicated that it remarkably outperformed the existing method. A user-friendly web-server for iSuc-PseOpt has been established at http://www.jci-bioinfo.cn/iSuc-PseOpt, where users can easily get their desired results without needing to go through the complicated mathematical equations involved.
authors.affiliation: Computer Department, Jing-De-Zhen Ceramic Institute, Jing-De-Zhen 333403, China. Electronic address: jjh163yx@163.com.
authors.forename: Jianhua
authors.initials: J
authors.lastname: Jia
authors.affiliation: Computer Department, Jing-De-Zhen Ceramic Institute, Jing-De-Zhen 333403, China.
authors.forename: Zi
authors.initials: Z
authors.lastname: Liu
authors.affiliation: Computer Department, Jing-De-Zhen Ceramic Institute, Jing-De-Zhen 333403, China; Gordon Life Science Institute, Boston, MA 02478, USA. Electronic address: xxiao@gordonlifescience.org.
authors.forename: Xuan
authors.initials: X
authors.lastname: Xiao
authors.affiliation: Computer Department, Jing-De-Zhen Ceramic Institute, Jing-De-Zhen 333403, China.
authors.forename: Bingxiang
authors.initials: B
authors.lastname: Liu
authors.affiliation: Gordon Life Science Institute, Boston, MA 02478, USA; Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia. Electronic address: kcchou@gordonlifescience.org.
authors.forename: Kuo-Chen
authors.initials: KC
authors.lastname: Chou
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D030562:Databases, Protein; D006801:Humans; D020407:Internet; D008239:Lysine / Q000032:analysis*; D011506:Proteins / Q000737:chemistry*; D012984:Software; D013386:Succinates / Q000737:chemistry*
chemical_list: D011506:Proteins; D013386:Succinates; D008239:Lysine
keywords: Lysine succinylation; Optimize training dataset; PseAAC; Sequence-coupling model; Target cross-validation