Database Commons

a catalog of worldwide biological databases

As an important post-translational modification, ubiquitination mediates ∼80% of protein degradation in eukaryotes. The degree of protein ubiquitination is tightly determined by the delicate balance between specific ubiquitin ligase (E3)-mediated ubiquitination and deubiquitinase-mediated deubiquitination. In 2017, we developed UbiBrowser 1.0, which is an integrated database for predicted human proteome-wide E3-substrate interactions. Here, to meet the urgent requirement of proteome-wide E3/deubiquitinase-substrate interactions (ESIs/DSIs) in multiple organisms, we updated UbiBrowser to version 2.0 (http://ubibrowser.ncpsb.org.cn). Using an improved protocol, we collected 4068/967 known ESIs/DSIs by manual curation, and we predicted about 2.2 million highly confident ESIs/DSIs in 39 organisms, with >210-fold increase in total data volume. In addition, we made several new features in the updated version: (i) it allows exploring proteins' upstream E3 ligases and deubiquitinases simultaneously; (ii) it has significantly increased species coverage; (iii) it presents a uniform confidence scoring system to rank predicted ESIs/DSIs. To facilitate the usage of UbiBrowser 2.0, we also redesigned the web interface for exploring these known and predicted ESIs/DSIs, and added functions of 'Browse', 'Download' and 'Application Programming Interface'. We believe that UbiBrowser 2.0, as a discovery tool, will contribute to the study of protein ubiquitination and the development of drug targets for complex diseases.

The ubiquitination mediated by ubiquitin activating enzyme (E1), ubiquitin conjugating enzyme (E2), and ubiquitin ligase (E3) cascade is crucial to protein degradation, transcription regulation, and cell signaling in eukaryotic cells. The high specificity of ubiquitination is regulated by the interaction between E3 ubiquitin ligases and their target substrates. Unfortunately, the landscape of human E3-substrate network has not been systematically uncovered. Therefore, there is an urgent need to develop a high-throughput and efficient strategy to identify the E3-substrate interaction. To address this challenge, we develop a computational model based on multiple types of heterogeneous biological evidence to investigate the human E3-substrate interactions. Furthermore, we provide UbiBrowser as an integrated bioinformatics platform to predict and present the proteome-wide human E3-substrate interaction network ( http://ubibrowser.ncpsb.org ).Protein stability modulation by E3 ubiquitin ligases is an important layer of functional regulation, but screening for E3 ligase-substrate interactions is time-consuming and costly. Here, the authors take an in silico naïve Bayesian classifier approach to integrate multiple lines of evidence for E3-substrate prediction, enabling prediction of the proteome-wide human E3 ligase interaction network.