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iScience. 2019 May 27;16:177-191. doi: 10.1016/j.isci.2019.05.033. [Epub ahead of print]

A Multidimensional Characterization of E3 Ubiquitin Ligase and Substrate Interaction Network.

Author information

1
CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
2
CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; Department of Hepatobiliary Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian Medical University, Dalian 116000, China.
3
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian Medical University, Dalian 116000, China.
4
CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China. Electronic address: hpiao@dicp.ac.cn.

Abstract

E3 ubiquitin ligases (E3s) play a critical role in molecular and cellular mechanisms. However, a large number of E3-substrate interactions (ESIs) remain unrevealed. Here, we integrated the increasing omics data with biological knowledge to characterize and identify ESIs. Multidimensional features were computed to obtain the association patterns of ESIs, and an ensemble prediction model was constructed to identify ESIs. Comparison with non-ESI cases revealed the specific association patterns of ESIs, which provided meaningful insights into ESI interpretation. Reliability of the prediction model was confirmed from various perspectives. Notably, our evaluations on leucine-rich repeat family of F box (FBXL) family were consistent with a proteomic study, and several substrates for SKP2 and an orphan E3 FBXL6 were experimentally verified. Moreover, a cancer hallmark ESI landscape was studied. Taken together, our study catches a glimpse at the omics-driven ESI association patterns and provides a valuable resource (http://www.esinet.dicp.ac.cn/home.php) to assist ubiquitination research.

KEYWORDS:

Bioinformatics; Molecular Network; Proteomics; Systems Biology

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