A Web Resource for Improved Analysis of AP-MS Protein Interaction Data.

摘要: Affinity purification coupled with mass spectrometry (AP-MS) is now a widely used approach for the identification of protein-protein interactions. However, any given protein interest, determining which identified polypeptides represent bona fide interactors versus those that are background contaminants (e.g. proteins interact solid-phase support, affinity reagent or epitope tag) challenging task. While standard to identify nonspecific interactions using one more negative controls, most small-scale AP-MS studies do not capture complete, accurate set. Fortunately, since controls largely bait-independent, we reasoned generated by proteomics research community could be developed as resource scoring data. Here present Contaminant Repository Purification (The CRAPome), currently containing data from 343 control purifications conducted 11 different groups (www.crapome.org). Users employ an intuitive graphical user interface explore database, either querying at time, downloading contaminant lists selected experimental conditions, uploading their own (alongside when available) and performing analysis. The CRAPome database scores vs. true based on semi-quantitative (normalized spectral counts) embedded in experiments. Significance Analysis INTeractome (SAINT) scheme, addition simpler Fold Change calculation (FC score) score user-supplied return ranked list putative interactors. We also describe structure composition, provide examples use this filter properly chosen demonstrate utility scheme identifying interaction partners. accommodates variety schemes and, while focused human data, will expanded other species.