title: Prediction of ubiquitination sites by using the composition of k-spaced amino acid pairs.
abstract: As one of the most important reversible protein post-translation modifications, ubiquitination has been reported to be involved in lots of biological processes and closely implicated with various diseases. To fully decipher the molecular mechanisms of ubiquitination-related biological processes, an initial but crucial step is the recognition of ubiquitylated substrates and the corresponding ubiquitination sites. Here, a new bioinformatics tool named CKSAAP_UbSite was developed to predict ubiquitination sites from protein sequences. With the assistance of Support Vector Machine (SVM), the highlight of CKSAAP_UbSite is to employ the composition of k-spaced amino acid pairs surrounding a query site (i.e. any lysine in a query sequence) as input. When trained and tested in the dataset of yeast ubiquitination sites (Radivojac et al, Proteins, 2010, 78: 365-380), a 100-fold cross-validation on a 1∶1 ratio of positive and negative samples revealed that the accuracy and MCC of CKSAAP_UbSite reached 73.40% and 0.4694, respectively. The proposed CKSAAP_UbSite has also been intensively benchmarked to exhibit better performance than some existing predictors, suggesting that it can be served as a useful tool to the community. Currently, CKSAAP_UbSite is freely accessible at http://protein.cau.edu.cn/cksaap_ubsite/. Moreover, we also found that the sequence patterns around ubiquitination sites are not conserved across different species. To ensure a reasonable prediction performance, the application of the current CKSAAP_UbSite should be limited to the proteome of yeast.
authors.affiliation: State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Chen
authors.forename: Yong-Zi
authors.initials: YZ
authors.lastname: Chen
authors.forename: Xiao-Feng
authors.initials: XF
authors.lastname: Wang
authors.forename: Chuan
authors.initials: C
authors.lastname: Wang
authors.forename: Ren-Xiang
authors.initials: RX
authors.lastname: Yan
authors.forename: Ziding
authors.initials: Z
authors.lastname: Zhang
mesh_terms: D000596:Amino Acids / Q000378:metabolism*; D019295:Computational Biology; D006801:Humans; D056510:Position-Specific Scoring Matrices; D011499:Protein Processing, Post-Translational; D011506:Proteins / Q000737:chemistry*; D020539:Sequence Analysis, Protein / Q000379:methods*; D060388:Support Vector Machine; D054875:Ubiquitination
chemical_list: D000596:Amino Acids; D011506:Proteins