Xiaofeng Song, Lizhen Hu, P. Han, Xuejiang Guo, J. Sha
{"title":"In silico identification and functional annotation of yeast E3 ubiquitin ligase Rsp5 substrates","authors":"Xiaofeng Song, Lizhen Hu, P. Han, Xuejiang Guo, J. Sha","doi":"10.1504/IJDMB.2015.072754","DOIUrl":null,"url":null,"abstract":"Rsp5, E3 ligases conserved from yeast to mammals, plays a key role in diverse processes in yeast. However, many of Rsp5 substrates are still unclear. Therefore we proposed an in silico method to recognise new substrates of Rsp5. To investigate the molecular determinants that affect the interaction between Rsp5 and its substrate, we have systematically analysed many features that perhaps correlated with the Rsp5 substrate recognition. It is found that PPxY motif, transmembrane region, disorder region and N-linked glycosylation modification are the most important features for substrate recognition. We have constructed an SVM-based classifier to recognise Rsp5 substrates, obtaining 81.5% sensitivity and 74.1% specificity averagely on ten independent testing dataset. We also applied the model on the whole yeast proteome, and identified -66 new Rsp5 substrates. Functional annotation reveals that half of these novel substrates function in the Rsp5 involved cell processes as Rsp5-interacting proteins.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJDMB.2015.072754","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1504/IJDMB.2015.072754","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Rsp5, E3 ligases conserved from yeast to mammals, plays a key role in diverse processes in yeast. However, many of Rsp5 substrates are still unclear. Therefore we proposed an in silico method to recognise new substrates of Rsp5. To investigate the molecular determinants that affect the interaction between Rsp5 and its substrate, we have systematically analysed many features that perhaps correlated with the Rsp5 substrate recognition. It is found that PPxY motif, transmembrane region, disorder region and N-linked glycosylation modification are the most important features for substrate recognition. We have constructed an SVM-based classifier to recognise Rsp5 substrates, obtaining 81.5% sensitivity and 74.1% specificity averagely on ten independent testing dataset. We also applied the model on the whole yeast proteome, and identified -66 new Rsp5 substrates. Functional annotation reveals that half of these novel substrates function in the Rsp5 involved cell processes as Rsp5-interacting proteins.