Literature DB >> 21870242

Protein-fragment complementation assays for large-scale analysis, functional dissection and dynamic studies of protein-protein interactions in living cells.

Stephen W Michnick1, Po Hien Ear, Christian Landry, Mohan K Malleshaiah, Vincent Messier.   

Abstract

Protein-fragment Complementation Assays (PCAs) are a family of assays for detecting protein-protein interactions (PPIs) that have been developed to provide simple and direct ways to study PPIs in any living cell, multicellular organism, or in vitro. PCAs can be used to detect PPI between proteins of any molecular weight and expressed at their endogenous levels. Proteins are expressed in their appropriate cellular compartments and can undergo any posttranslational modification or degradation that, barring effects of the PCA fragment fusion, they would normally undergo. Assays can be performed in any cell type or model organism that can be transformed or transfected with gene expression DNA constructs. Here we focus on recent applications of PCA in the budding yeast, Saccharomyces cerevisiae, that cover the gamut of applications one could envision for studying any aspect of PPIs. We present detailed protocols for large-scale analysis of PPIs with the survival-selection dihydrofolate reductase (DHFR), reporter PCA, and a new PCA based on a yeast cytosine deaminase reporter that allows for both survival and death selection. This PCA should prove a powerful way to dissect PPIs. We then present methods to study spatial localization and dynamics of PPIs based on fluorescent protein reporter PCAs.

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Year:  2011        PMID: 21870242     DOI: 10.1007/978-1-61779-160-4_25

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  11 in total

Review 1.  Diversity in genetic in vivo methods for protein-protein interaction studies: from the yeast two-hybrid system to the mammalian split-luciferase system.

Authors:  Bram Stynen; Hélène Tournu; Jan Tavernier; Patrick Van Dijck
Journal:  Microbiol Mol Biol Rev       Date:  2012-06       Impact factor: 11.056

Review 2.  Beyond hairballs: The use of quantitative mass spectrometry data to understand protein-protein interactions.

Authors:  Anne-Claude Gingras; Brian Raught
Journal:  FEBS Lett       Date:  2012-04-10       Impact factor: 4.124

3.  Protein-Protein Interaction Prediction for Targeted Protein Degradation.

Authors:  Oliver Orasch; Noah Weber; Michael Müller; Amir Amanzadi; Chiara Gasbarri; Christopher Trummer
Journal:  Int J Mol Sci       Date:  2022-06-24       Impact factor: 6.208

4.  Protein-Protein Interactions as New Targets for Ion Channel Drug Discovery.

Authors:  Svetla Stoilova-McPhie; Syed Ali; Fernanda Laezza
Journal:  Austin J Pharmacol Ther       Date:  2013-12-31

5.  Identifying a kinase network regulating FGF14:Nav1.6 complex assembly using split-luciferase complementation.

Authors:  Wei-Chun Hsu; Miroslav N Nenov; Alexander Shavkunov; Neli Panova; Ming Zhan; Fernanda Laezza
Journal:  PLoS One       Date:  2015-02-06       Impact factor: 3.240

Review 6.  Crosstalk of small GTPases at the Golgi apparatus.

Authors:  Francesco Baschieri; Hesso Farhan
Journal:  Small GTPases       Date:  2012 Apr-Jun

7.  Coevolutionary analyses require phylogenetically deep alignments and better null models to accurately detect inter-protein contacts within and between species.

Authors:  Aram Avila-Herrera; Katherine S Pollard
Journal:  BMC Bioinformatics       Date:  2015-08-25       Impact factor: 3.169

8.  Reverse PCA, a systematic approach for identifying genes important for the physical interaction between protein pairs.

Authors:  Ifat Lev; Marina Volpe; Liron Goor; Nelly Levinton; Liach Emuna; Shay Ben-Aroya
Journal:  PLoS Genet       Date:  2013-10-10       Impact factor: 5.917

Review 9.  Protein-protein interaction detection: methods and analysis.

Authors:  V Srinivasa Rao; K Srinivas; G N Sujini; G N Sunand Kumar
Journal:  Int J Proteomics       Date:  2014-02-17

10.  Directed evolution provides insight into conformational substrate sampling by SrtA.

Authors:  Muna Suliman; Vishaka Santosh; Tom C M Seegar; Annamarie C Dalton; Kathryn M Schultz; Candice S Klug; William A Barton
Journal:  PLoS One       Date:  2017-08-31       Impact factor: 3.240

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