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HypDB: A functionally annotated web-based database of the proline hydroxylation proteome.
Gong, Yao; Behera, Gaurav; Erber, Luke; Luo, Ang; Chen, Yue.
Afiliação
  • Gong Y; Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota at Twin Cities, Minneapolis, Minnesota, United States of America.
  • Behera G; Bioinformatics and Computational Biology Program, University of Minnesota at Twin Cities, Minneapolis, Minnesota, United States of America.
  • Erber L; Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota at Twin Cities, Minneapolis, Minnesota, United States of America.
  • Luo A; Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota at Twin Cities, Minneapolis, Minnesota, United States of America.
  • Chen Y; Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota at Twin Cities, Minneapolis, Minnesota, United States of America.
PLoS Biol ; 20(8): e3001757, 2022 08.
Article em En | MEDLINE | ID: mdl-36026437
Proline hydroxylation (Hyp) regulates protein structure, stability, and protein-protein interaction. It is widely involved in diverse metabolic and physiological pathways in cells and diseases. To reveal functional features of the Hyp proteome, we integrated various data sources for deep proteome profiling of the Hyp proteome in humans and developed HypDB (https://www.HypDB.site), an annotated database and web server for Hyp proteome. HypDB provides site-specific evidence of modification based on extensive LC-MS analysis and literature mining with 14,413 nonredundant Hyp sites on 5,165 human proteins including 3,383 Class I and 4,335 Class II sites. Annotation analysis revealed significant enrichment of Hyp on key functional domains and tissue-specific distribution of Hyp abundance across 26 types of human organs and fluids and 6 cell lines. The network connectivity analysis further revealed a critical role of Hyp in mediating protein-protein interactions. Moreover, the spectral library generated by HypDB enabled data-independent analysis (DIA) of clinical tissues and the identification of novel Hyp biomarkers in lung cancer and kidney cancer. Taken together, our integrated analysis of human proteome with publicly accessible HypDB revealed functional diversity of Hyp substrates and provides a quantitative data source to characterize Hyp in pathways and diseases.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Prolina / Proteoma Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Prolina / Proteoma Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article