Abstract

Recent large-scale data sets of protein complex purifications have provided unprecedented insights into the organization of cellular protein complexes. Several computational methods have been developed to detect co-complexed proteins in these data sets. Their common aim is the identification of biologically relevant protein complexes. However, much less is known about the network of direct physical protein contacts within the detected protein complexes. Therefore, our work investigates whether direct physical contacts can be computationally derived by combining raw data of large-scale protein complex purifications. We assess four established scoring schemes and introduce a new scoring approach that is specifically devised to infer direct physical protein contacts from protein complex purifications. The physical contacts identified by the five methods are comprehensively benchmarked against different reference sets that provide evidence for true physical contacts.Our results show that raw purification data can indeed be exploited to determine high-confidence physical protein contacts within protein complexes. In particular, our new method outperforms competing approaches at discovering physical contacts involving proteins that have been screened multiple times in purification experiments. It also excels in the analysis of recent protein purification screens of molecular chaperones and protein kinases. In contrast to previous findings, we observe that physical contacts inferred from purification experiments of protein complexes can be qualitatively comparable to binary protein interactions measured by experimental high-throughput assays such as yeast two-hybrid. This suggests that computationally derived physical contacts might complement binary protein interaction assays and guide large-scale interactome mapping projects by prioritizing putative physical contacts for further experimental screens.

Highlights

  • IntroductionEstablished purification scoring schemes have been shown to perform well in determining the composition of protein complexes by identifying such protein interactions in the purification data

  • From the ‡Max Planck Institute for Informatics, Campus E1.4, 66123 Saarbrucken, Germany ¶School of Information Technologies, University of Sydney, NSW 2006, Australia

  • Less is known about which proteins in large-scale protein purifications form direct physical contacts this information is crucial for a deeper understanding of protein complex formation and organization

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Summary

Introduction

Established purification scoring schemes have been shown to perform well in determining the composition of protein complexes by identifying such protein interactions in the purification data. These scoring schemes do not discriminate between direct physical contacts and indirect protein interactions. Less is known about which proteins in large-scale protein purifications form direct physical contacts this information is crucial for a deeper understanding of protein complex formation and organization. The difficulty of identifying physical protein contacts within protein complex purifications has hampered the comparison with results of binary protein interaction experiments such as yeast two-hybrid assays.

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