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. 2019 Jan 8;47(D1):D451-D458.
doi: 10.1093/nar/gky1052.

qPhos: a database of protein phosphorylation dynamics in humans

Kai Yu  1 , Qingfeng Zhang  1 , Zekun Liu  1   2 , Qi Zhao  1 , Xiaolong Zhang  1 , Yan Wang  1 , Zi-Xian Wang  1 , Ying Jin  1 , Xiaoxing Li  1 , Ze-Xian Liu  1 , Rui-Hua Xu  1
Affiliations

qPhos: a database of protein phosphorylation dynamics in humans

Kai Yu et al. Nucleic Acids Res. .

Abstract

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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Figures

Figure 1.
Figure 1.
The schema for the construction of the qPhos database.
Figure 2
Figure 2
Summary of the sequence and structure preferences and kinase families of the quantified phosphorylation sites, including the summary of the position along the protein sequence (A), secondary structure (B), surface accessibility (C), disorder region (D), serine/threonine/tyrosine (E) and regulator kinase family (F) for the quantified phosphorylation sites.
Figure 3.
Figure 3.
The detailed information in qPhos. (A) Browse function. (B) Simple search function. (C) Advanced search function. (D) The returned search results. (E) The information about the protein. (F) The information about the quantification of the phosphorylation site. (G) The information on potential kinases and their inhibitors for the quantified phosphorylation site. (H) The sequence and structure properties of the phosphorylation site. (I) The enlarged view of the sequence and structure properties.
Figure 4
Figure 4
The qKinAct service for the analysis of kinase activities. (A) The distribution of different types of activity-related phosphorylation sites in kinases. ‘+’, ‘−’ and ‘auto’ represent positively related, negatively related and autophosphorylation sites. (B) The distribution of kinases with activity-related phosphorylation sites in kinases. (C) The distribution of kinase families with activity-related phosphorylation sites in kinases. (D) The example for submission of quantitative phosphoproteome data. (E) The returned results for the query of kinase activity-related phosphorylation sites. The kinase activity profile for phosphorylation dynamics in nicotine-treated pancreatic stellate cells (F) and TNFα-stimulated phosphorylation dynamics (G).
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