The idea being that the target protein (or “bait”) is pulled-down along with other proteins (or “prey”) with which it interacts. A typical AP-MS workflow consists of the immunoprecipitation (IP) or “pull-down” of a target protein of interest using an antibody followed by injection into a liquid chromatography (LC) tandem mass spectrometry (MS/MS) system. Further, due to the breadth and scope of possible interactions, methods that are capable of simultaneously detecting multiple proteins are often required.Īffinity proteomics (AP-MS) has become a popular experimental method for reliably querying the universe of PPIs, often referred to as the interactome. Since proteins are almost always part of larger protein complexes and complex signaling networks, robust and reproducible methods are necessary for facilitating our understanding of PPIs. Alterations in native PPIs can be cause or consequence of human disease, and as such, they are increasingly being seen as promising drug targets. These interactions are important as they give rise to nearly all biological processes. Protein-protein interactions (PPIs) are a fundamental type of physical interaction between two or more proteins. We provide sample data and a sample workflow with step-by-step instructions to quickly acquaint users with the process. This platform enables researchers with no prior computational experience to begin with data from a mass spectrometer (e.g., peaklists in mzML format) and perform peak processing, database searching, assignment of interaction confidence scores, and data visualization with a few clicks of a mouse. Here, we describe a Galaxy-based platform enabling AP-MS analysis. One solution to address these issues is Galaxy, an open source and web-based platform for developing and deploying user-friendly computational pipelines or workflows.
However, if the scientist (e.g., a bench biologist) lacks a computational background, then managing large AP-MS datasets can be challenging, manually formatting AP-MS data for input into analysis software can be error-prone, and data visualization involving dozens of variables can be laborious. The AP-MS approach necessitates several different software tools, integrated into reproducible and accessible workflows. Affinity proteomics (AP-MS) is growing in importance for characterizing protein-protein interactions (PPIs) in the form of protein complexes and signaling networks.