title: Computational Identification of Protein Pupylation Sites by Using Profile-Based Composition of k-Spaced Amino Acid Pairs.
abstract: Prokaryotic proteins are regulated by pupylation, a type of post-translational modification that contributes to cellular function in bacterial organisms. In pupylation process, the prokaryotic ubiquitin-like protein (Pup) tagging is functionally analogous to ubiquitination in order to tag target proteins for proteasomal degradation. To date, several experimental methods have been developed to identify pupylated proteins and their pupylation sites, but these experimental methods are generally laborious and costly. Therefore, computational methods that can accurately predict potential pupylation sites based on protein sequence information are highly desirable. In this paper, a novel predictor termed as pbPUP has been developed for accurate prediction of pupylation sites. In particular, a sophisticated sequence encoding scheme [i.e. the profile-based composition of k-spaced amino acid pairs (pbCKSAAP)] is used to represent the sequence patterns and evolutionary information of the sequence fragments surrounding pupylation sites. Then, a Support Vector Machine (SVM) classifier is trained using the pbCKSAAP encoding scheme. The final pbPUP predictor achieves an AUC value of 0.849 in 10-fold cross-validation tests and outperforms other existing predictors on a comprehensive independent test dataset. The proposed method is anticipated to be a helpful computational resource for the prediction of pupylation sites. The web server and curated datasets in this study are freely available at http://protein.cau.edu.cn/pbPUP/.
authors.affiliation: State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, 100193, China.
authors.forename: Md Mehedi
authors.initials: MM
authors.lastname: Hasan
authors.affiliation: State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, 100193, China.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Zhou
authors.affiliation: State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, 100193, China.
authors.forename: Xiaotian
authors.initials: X
authors.lastname: Lu
authors.affiliation: Advanced Analytics Institute and Centre for Health Technologies, University of Technology, Sydney, 81 Broadway, NSW 2007, Australia.
authors.forename: Jinyan
authors.initials: J
authors.lastname: Li
authors.affiliation: National Engineering Laboratory for Industrial Enzymes and Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China; Monash Bioinformatics Platform and Department of Biochemistry and Molecular Biology, Faculty of Medicine, Monash University, Melbourne, VIC 3800, Australia.
authors.forename: Jiangning
authors.initials: J
authors.lastname: Song
authors.affiliation: State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, 100193, China.
authors.forename: Ziding
authors.initials: Z
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000596:Amino Acids / Q000378:metabolism*; D001426:Bacterial Proteins / Q000378:metabolism*; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D020407:Internet; D008969:Molecular Sequence Data; D046988:Proteasome Endopeptidase Complex / Q000378:metabolism; D011499:Protein Processing, Post-Translational; D059748:Proteolysis; D015203:Reproducibility of Results; D060388:Support Vector Machine; D014452:Ubiquitins / Q000378:metabolism*
chemical_list: D000596:Amino Acids; D001426:Bacterial Proteins; D014452:Ubiquitins; D046988:Proteasome Endopeptidase Complex