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.

Incorporating key position and amino acid residue features to identify general and species-specific Ubiquitin conjugation sites

“…In this work, it would be difficult to prove definitively that a particular lysine residue is not ubiquitylated under any conditions. However, almost all researchers (Cai et al, 2012;Chen et al, 2011;Lee et al, 2011;Radivojac et al, 2010) of ubiquitylation prediction use a strategy in which any lysine residue that is not marked by any ubiquitylation information on the same protein is a non-ubiquitylation site. In addition, Radivojac et al (2010) concluded that this strategy did not significantly influence the prediction performance for a model of yeast.…”

“…CKSAAP_UbSite was constructed by Chen et al (2011) for identifying ubiquitylation sites by using the composition of k-space amino acid pairs surrounding a query site with the assistance of a SVM. Recently, Cai et al (2012) presented a method based on multi-sequence features and the nearest neighbor algorithm.…”

Modelling the structure of full-length Epstein–Barr virus nuclear antigen 1

“…Ubiquitination sites were predicted using CKSAAP UbSite web server (59). Pictorial 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 representations of structural motifs against the linear sequence were generated in the EMBL server PDBsum.…”

Biochemistry: A radical treatment

“…In 2011, University of Pittsburgh, Pennsylvania, pulmonologist Jay Kolls reported that mice genetically lacking the IL-17 receptor did not develop emphysema despite six months of exposure to cigarette smoke 9 . More recently, Kheradmand and collaborators at the MD Anderson Cancer Center in Houston, Texas, genetically engineered mice to overexpress one form of IL-17 -IL-17A -and then exposed these mice to cigarette smoke for four months 8 . The mice developed an especially severe form of emphysema along with producing more destructive proteases.…”