State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
Department of Hepatobiliary Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, China.
Nucleic Acids Res. 2019 Jan 8;47(D1):D451-D458. doi: 10.1093/nar/gky1052.
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.
蛋白质的磷酸化在时间和空间上动态地调控着广泛的生物过程，并在疾病和癌症中发挥着各种生理和病理作用。高通量蛋白质组学技术的最新进展极大地促进了磷酸化蛋白质组的分析和定量。然而，尽管有几个综合数据库保留了磷酸化蛋白质和磷酸化位点，但仍需要构建一个用于磷酸化定量的资源。在这项研究中，我们开发了 qPhos（http://qphos.cancerbio.info）数据库，以整合和托管关于磷酸化动态的数据。通过对已发表文献的详尽整理，共收集了 3537533 个定量事件，涉及 18402 种蛋白质上的 199071 个非冗余磷酸化位点，这些蛋白质在 484 种条件下发生磷酸化。记录了实验细节，包括样品材料、条件和方法。系统地整合了各种注释，如蛋白质序列和结构特性、潜在的上游激酶及其抑制剂，并精心组织，以呈现有关定量磷酸化位点的详细信息。实现了各种浏览和搜索功能，用于用户定义的样品、条件和蛋白质的筛选。此外，还开发了 qKinAct 服务，通过注释与激酶活性相关的磷酸化位点，从用户提交的定量磷酸化蛋白质组数据中剖析激酶活性谱。总之，qPhos 数据库为蛋白质磷酸化动力学提供了一个全面的资源，以促进相关研究。
