An integrated bioinformatics platform for investigating the human E3 ubiquitin ligase-substrate interaction network

Yang Li,Ping Xie,Dong Li,Liang Lu,Lihong Diao,Han Liang,Yangzhige He,Qin Huang,Zhongyang Liu,Feifei Guo,Yuan Liu,Fuchu He,Jian Wang

doi:10.1038/s41467-017-00299-9

Abstract

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).

Highlights

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
We developed a naïve Bayesian classifier-based computational algorithm to combine multiple types of heterogeneous biological evidence including homology E3substrate interaction, enriched domain and Gene Ontology (GO) term pair, protein interaction network loop, and inferred E3 recognition consensus motif, to predict human E3-substrate interactions
We compiled a golden standard data set with 913 E3-substrate pairs (GESID, golden standard E3-substrate interaction data set) by manual literature mining (Papers before 1 January 2010)

Summary

Results

We evaluated five types of heterogeneous evidence for the model, including homology E3-substrate interaction, enriched domain and GO term pair, protein–protein interaction network loop, and inferred E3 recognition consensus motif. Some E3-substrate interactions are mediated by the interacting protein domains[16], we thought that novel E3-substrate interactions might be predicted by identifying domain pairs enriched among known E3-substrate interactions. We identified 3856 domain pairs that were enriched in known E3-substrate interactions, and some of them have been reported in literature. E3 ligases and their substrates involved in ESIs are supposed to be of the same biological functions. To test this hypothesis, we adopted the similar strategy as DER to calculate the GO term. D1: 1.30 < DER ≤ 3.00 D2: 3.00 < DER ≤ 5.00 D3: 5.00 < DER ≤ 10.00 D4: 10.00 < DER ≤ 24.00 D5: DER > 24.00

C1 C2 C3 C4 C5 F1 F2 F3 F4 F5 P1 P2 P3 P4 GO term enrichment ratio

T1 T2 T3 T4

SMURF1

90 IB: Myc-HRP