4.8 Article

qPhos: a database of protein phosphorylation dynamics in humans

期刊

NUCLEIC ACIDS RESEARCH
卷 47, 期 D1, 页码 D451-D458

出版社

OXFORD UNIV PRESS
DOI: 10.1093/nar/gky1052

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资金

  1. National Natural Science Foundation of China [31501069, 81802438]
  2. National Key R&D Program of China [2018YFC1313300]
  3. Program for Guangdong Introducing Innovative and Entrepreneurial Teams [2017ZT07S096]
  4. Natural Science Foundation of Guangdong Province [2014A030312015]
  5. Science and Technology Program of Guangdong [2015B020232008]
  6. Science and Technology Program of Guangzhou [15570006, 201508020250, 201604020003]
  7. Fundamental Research Funds for the Central Universities [SYSU: 16ykzd06]
  8. Pearl River S&T Nova Program of Guangzhou
  9. Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase)

向作者/读者索取更多资源

Temporal and spatial protein phosphorylation dynamically orchestrates a broad spectrum of biological processes and plays various physiological and pathological roles in diseases and cancers. Recent advancements in high-throughput proteomics techniques greatly promoted the profiling and quantification of phosphoproteome. However, although several comprehensive databases have reserved the phosphorylated proteins and sites, a resource for phosphorylation quantification still remains to be constructed. In this study, we developed the qPhos (http://qphos.cancerbio.info) database to integrate and host the data on phosphorylation dynamics. A total of 3 537 533 quantification events for 199 071 non-redundant phosphorylation sites on 18 402 proteins under 484 conditions were collected through exhaustive curation of published literature. The experimental details, including sample materials, conditions and methods, were recorded. Various annotations, such as protein sequence and structure properties, potential upstream kinases and their inhibitors, were systematically integrated and carefully organized to present details about the quantified phosphorylation sites. Various browse and search functions were implemented for the user-defined filtering of samples, conditions and proteins. Furthermore, the qKinAct service was developed to dissect the kinase activity profile from user-submitted quantitative phosphoproteome data through annotating the kinase activity-related phosphorylation sites. Taken together, the qPhos database provides a comprehensive resource for protein phosphorylation dynamics to facilitate related investigations.

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