Abstract

It remains a significant challenge to define individual protein associations within networks where an individual protein can directly interact with other proteins and/or be part of large complexes, which contain functional modules. Here we demonstrate the topological scoring (TopS) algorithm for the analysis of quantitative proteomic analyses of affinity purifications. Data is analyzed in a parallel fashion where a bait protein is scored in an individual affinity purification by aggregating information from the entire dataset. A broad range of scores is obtained which indicate the enrichment of an individual protein in every bait protein analyzed. TopS was applied to interaction networks derived from human DNA repair proteins and yeast chromatin remodeling complexes. TopS captured direct protein interactions and modules within complexes. TopS is a rapid method for the efficient and informative computational analysis of datasets, is complementary to existing analysis pipelines, and provides new insights into protein interaction networks.