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Relevance Rank Platform (RRP) for Functional Filtering of High Content Protein-Protein Interaction Data

Pokharel Yuba R., Jani Saarela, Agnieszka Szwajda, Christian Rupp, Anne Rokka, Shibendra K. L. Karna, Kaisa Teittinen, Garry Corthals, Olli Kallioniemi, Krister Wennerberg, Tero Aittokallio, Jukka Westermarck, Relevance Rank Platform (RRP) for Functional Filtering of High Content Protein-Protein Interaction Data. Molecular and Cellular Proteomics mcp-M115, , 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 combination of RRP and SAINT or CRAPome for selecting the candidate interactors that fulfill the both important requirements, functional relevance and high confidence interaction detection.

BibTeX entry:

@ARTICLE{jPoSaSzRuRoKaTeCoKaWeAiWeSaSzRuRoKaTeCoKaWeAiWe15a,
  title = {Relevance Rank Platform (RRP) for Functional Filtering of High Content Protein-Protein Interaction Data},
  author = {Pokharel Yuba R. and Saarela, Jani and Szwajda, Agnieszka and Rupp, Christian and Rokka, Anne and Karna, Shibendra K. L. and Teittinen, Kaisa and Corthals, Garry and Kallioniemi, Olli and Wennerberg, Krister and Aittokallio, Tero and Westermarck, Jukka},
  journal = {Molecular and Cellular Proteomics},
  volume = {mcp-M115},
  pages = {    },
  year = {2015},
  keywords = {Affinity proteomics; Cancer; FDPS; Functional Inference; HRNR; Lamin A/C; PP2A; Protein Phosphatases; Protein-Protein Interactions; Signal Transduction},
}

Belongs to TUCS Research Unit(s): Biomathematics Research Unit (BIOMATH)

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