Systematic analysis of human lysine acetylation proteins and accurate prediction of human lysine acetylation through bi-relative adapted binomial score Bayes feature representation
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AbstractLysine acetylation is a reversible post-translational modification (PTM) which has been linked to many biological and pathological implications. Hence, localization of lysine acetylation is essential for deciphering the mechanism of such implications. Whereas many acetylated lysines in human proteins have been localized through experimental approaches in wet lab, it still fails to reach completion. In the present study, we proposed a novel feature extraction approach, bi-relative adapted binomial score Bayes (BRABSB), combined with support vector machines (SVMs) to construct a human-specific lysine acetylation predictor, which yields, on average, a sensitivity of 83.91%, a specificity of 87.25% and an accuracy of 85.58%, in the case of 5-fold cross validation experiments. Results obtained through the validation on independent data sets show that the proposed approach here outperforms other existing lysine acetylation predictors. Furthermore, due to the fact that global analysis of human lysine acetylproteins, which would ultimately facilitate the systematic investigation of the biological and pathological consequences associated with lysine acetylation events, remains to be resolved, we made an attempt to systematically analyze human lysine acetylproteins, demonstrating their diversity with respect to subcellular localization as well as biological process and predominance by "binding" in terms of molecular function. Our analysis also revealed that human lysine acetylproteins are significantly enriched in neurodegenerative disorders and cancer pathways. Remarkably, lysine acetylproteins in mitochondria are significantly related to neurodegenerative disorders and those in the nucleus are instead significantly involved in pathways in cancers, all of which might ultimately provide novel global insights into such pathological processes for the therapeutic purpose. The web server is deployed at http://www.bioinfo.bio.cuhk.edu.hk/bpbphka.
All Author(s) ListShao JL, Xu D, Hu LD, Kwan YW, Wang YF, Kong XY, Ngai SM
Journal nameMolecular BioSystems
Detailed descriptionTo ORKTS: doi: 10.1039/C2MB25251A
Year2012
Month1
Day1
Volume Number8
Issue Number11
PublisherRoyal Society of Chemistry
Pages2964 - 2973
ISSN1742-206X
eISSN1742-2051
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesBiochemistry & Molecular Biology; BIOCHEMISTRY & MOLECULAR BIOLOGY

Last updated on 2020-26-09 at 23:09