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dc.contributor.authorVasylenko, Tamaraen_US
dc.contributor.authorLiou, Yi-Fanen_US
dc.contributor.authorChiou, Po-Chinen_US
dc.contributor.authorChu, Hsiao-Weien_US
dc.contributor.authorLai, Yung-Sungen_US
dc.contributor.authorChou, Yu-Lingen_US
dc.contributor.authorHuang, Hui-Lingen_US
dc.contributor.authorHo, Shinn-Yingen_US
dc.date.accessioned2017-04-21T06:49:38Z-
dc.date.available2017-04-21T06:49:38Z-
dc.date.issued2016-12-22en_US
dc.identifier.issn1471-2105en_US
dc.identifier.urihttp://dx.doi.org/10.1186/s12859-016-1371-4en_US
dc.identifier.urihttp://hdl.handle.net/11536/134503-
dc.description.abstractBackground: Bacterial tyrosine-kinases (BY-kinases), which play an important role in numerous cellular processes, are characterized as a separate class of enzymes and share no structural similarity with their eukaryotic counterparts. However, in silico methods for predicting BY-kinases have not been developed yet. Since these enzymes are involved in key regulatory processes, and are promising targets for anti-bacterial drug design, it is desirable to develop a simple and easily interpretable predictor to gain new insights into bacterial tyrosine phosphorylation. This study proposes a novel SCMBYK method for predicting and characterizing BY-kinases. Results: A dataset consisting of 797 BY-kinases and 783 non-BY-kinases was established to design the SCMBYK predictor, which achieved training and test accuracies of 97.55 and 96.73%, respectively. Furthermore, the leaveone-phylum-out method was used to predict specific bacterial phyla hosts of target sequences, gaining 97.39% average test accuracy. After analyzing SCMBYK-derived propensity scores, four characteristics of BY-kinases were determined: 1) BY-kinases tend to be composed of a-helices; 2) the amino-acid content of extracellular regions of BY-kinases is expected to be dominated by residues such as Val, Ile, Phe and Tyr; 3) BY-kinases structurally resemble nuclear proteins; 4) different domains play different roles in triggering BY-kinase activity. Conclusions: The SCMBYK predictor is an effective method for identification of possible BY-kinases. Furthermore, it can be used as a part of a novel drug repurposing method, which recognizes putative BY-kinases and matches them to approved drugs. Among other results, our analysis revealed that azathioprine could suppress the virulence of M. tuberculosis, and thus be considered as a potential antibiotic for tuberculosis treatment.en_US
dc.language.isoen_USen_US
dc.subjectBY-kinaseen_US
dc.subjectScoring card methoden_US
dc.subjectDrug repurposingen_US
dc.subjectPropensity scoresen_US
dc.subjectDipeptideen_US
dc.titleSCMBYK: prediction and characterization of bacterial tyrosine-kinases based on propensity scores of dipeptidesen_US
dc.typeArticle; Proceedings Paperen_US
dc.identifier.doi10.1186/s12859-016-1371-4en_US
dc.identifier.journalBMC BIOINFORMATICSen_US
dc.citation.volume17en_US
dc.contributor.department生物科技學院zh_TW
dc.contributor.department生物資訊及系統生物研究所zh_TW
dc.contributor.departmentCollege of Biological Science and Technologyen_US
dc.contributor.departmentInstitude of Bioinformatics and Systems Biologyen_US
dc.identifier.wosnumberWOS:000392533100011en_US
dc.citation.woscount1en_US
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