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Relevance Rank Platform (RRP) for Functional Filtering of High Content Protein-Protein Interaction Data
- Source :
- Molecularcellular proteomics : MCP. 14(12)
- Publication Year :
- 2015
-
Abstract
- High content protein interaction screens have revolutionized our understanding of protein complex assembly. However, one of the major challenges in translation of high content protein interaction data is identification of those interactions that are functionally relevant for a particular biological question. To address this challenge, we developed a relevance ranking platform (RRP), which consist of modular functional and bioinformatic filters to provide relevance rank among the interactome proteins. We demonstrate the versatility of RRP to enable a systematic prioritization of the most relevant interaction partners from high content data, highlighted by the analysis of cancer relevant protein interactions for oncoproteins Pin1 and PME-1. We validated the importance of selected interactions by demonstration of PTOV1 and CSKN2B as novel regulators of Pin1 target c-Jun phosphorylation and reveal previously unknown interacting proteins that may mediate PME-1 effects via PP2A-inhibition. The RRP framework is modular and can be modified to answer versatile research problems depending on the nature of the biological question under study. Based on comparison of RRP to other existing filtering tools, the presented data indicate that RRP offers added value especially for the analysis of interacting proteins for which there is no sufficient prior knowledge available. Finally, we encourage the use of RRP in combination with either SAINT or CRAPome computational tools for selecting the candidate interactors that fulfill the both important requirements, functional relevance, and high confidence interaction detection.
- Subjects :
- Computer science
Computational biology
Protein complex assembly
computer.software_genre
Biochemistry
Interactome
Analytical Chemistry
Protein–protein interaction
Ranking (information retrieval)
03 medical and health sciences
0302 clinical medicine
Cell Line, Tumor
Protein Interaction Mapping
Biomarkers, Tumor
Humans
Relevance (information retrieval)
Protein Phosphatase 2
Phosphorylation
Molecular Biology
030304 developmental biology
0303 health sciences
business.industry
Research
Rank (computer programming)
ta1182
Computational Biology
Proteins
Modular design
Peptidylprolyl Isomerase
Neoplasm Proteins
NIMA-Interacting Peptidylprolyl Isomerase
Identification (information)
030220 oncology & carcinogenesis
Data mining
business
computer
Carboxylic Ester Hydrolases
Algorithms
Subjects
Details
- ISSN :
- 15359484
- Volume :
- 14
- Issue :
- 12
- Database :
- OpenAIRE
- Journal :
- Molecularcellular proteomics : MCP
- Accession number :
- edsair.doi.dedup.....e93be4a2b8274ecff5a735991589b231