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Inferring physical protein contacts from large-scale purification data of protein complexes.

Schelhorn SE, Mestre J, Albrecht M, Zotenko E - Mol. Cell Proteomics (2011)

Bottom Line: Our results show that raw purification data can indeed be exploited to determine high-confidence physical protein contacts within protein complexes.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.

View Article: PubMed Central - PubMed

Affiliation: Max Planck Institute for Informatics, Saarbr├╝cken, Germany. sven@mpi-inf.mpg.de

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.

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Assessment of inferred physical protein contacts by five scoring methods against reference sets that provide indirect evidence for physical contacts. Inferred physical contacts are ranked by scores of the corresponding scoring method. A, Physical contacts are evaluated by their enrichment in protein domains that are known to interact in crystal structures of protein complexes. B, Functional similarity of proteins involved in inferred physical contacts is assessed by correlating genetic interaction profiles of these proteins. C, D, Performance is measured by plotting the number of complexes that are sufficiently connected by top-ranking inferred physical contacts for different rank cutoffs. We consider a complex sufficiently connected by a set of inferred physical contacts if the physical contacts reduce the number of connected components within the complex to less than 50% compared with the unconnected complex.
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Figure 3: Assessment of inferred physical protein contacts by five scoring methods against reference sets that provide indirect evidence for physical contacts. Inferred physical contacts are ranked by scores of the corresponding scoring method. A, Physical contacts are evaluated by their enrichment in protein domains that are known to interact in crystal structures of protein complexes. B, Functional similarity of proteins involved in inferred physical contacts is assessed by correlating genetic interaction profiles of these proteins. C, D, Performance is measured by plotting the number of complexes that are sufficiently connected by top-ranking inferred physical contacts for different rank cutoffs. We consider a complex sufficiently connected by a set of inferred physical contacts if the physical contacts reduce the number of connected components within the complex to less than 50% compared with the unconnected complex.

Mentions: Several resources exist that derive pairs of interacting domains from crystal structures of protein complexes in the PDB. In this work, we use the latest release of the 3DID database (30) to obtain interactions between domains that are annotated to at least one yeast gene. These interactions are denoted as 3DID reference set and compared with a set of domains induced by top-ranking inferred physical contacts. More specifically, for each method, all domain pairs were ranked according to the best-ranking inferred physical protein contact that could be formed by the domain pair. The results of this evaluation are presented in Fig. 3A. Again, the SA and ISA methods significantly outperform other approaches over the range of 3,000 to 4,000 inferred physical contacts that are reliably supported by experimental data. At the same time, both SA and ISA perform comparably to the Y2H binary experimental data set with about 240 true domain interactions at a rank cutoff of 4,000 physical contacts.


Inferring physical protein contacts from large-scale purification data of protein complexes.

Schelhorn SE, Mestre J, Albrecht M, Zotenko E - Mol. Cell Proteomics (2011)

Assessment of inferred physical protein contacts by five scoring methods against reference sets that provide indirect evidence for physical contacts. Inferred physical contacts are ranked by scores of the corresponding scoring method. A, Physical contacts are evaluated by their enrichment in protein domains that are known to interact in crystal structures of protein complexes. B, Functional similarity of proteins involved in inferred physical contacts is assessed by correlating genetic interaction profiles of these proteins. C, D, Performance is measured by plotting the number of complexes that are sufficiently connected by top-ranking inferred physical contacts for different rank cutoffs. We consider a complex sufficiently connected by a set of inferred physical contacts if the physical contacts reduce the number of connected components within the complex to less than 50% compared with the unconnected complex.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3108834&req=5

Figure 3: Assessment of inferred physical protein contacts by five scoring methods against reference sets that provide indirect evidence for physical contacts. Inferred physical contacts are ranked by scores of the corresponding scoring method. A, Physical contacts are evaluated by their enrichment in protein domains that are known to interact in crystal structures of protein complexes. B, Functional similarity of proteins involved in inferred physical contacts is assessed by correlating genetic interaction profiles of these proteins. C, D, Performance is measured by plotting the number of complexes that are sufficiently connected by top-ranking inferred physical contacts for different rank cutoffs. We consider a complex sufficiently connected by a set of inferred physical contacts if the physical contacts reduce the number of connected components within the complex to less than 50% compared with the unconnected complex.
Mentions: Several resources exist that derive pairs of interacting domains from crystal structures of protein complexes in the PDB. In this work, we use the latest release of the 3DID database (30) to obtain interactions between domains that are annotated to at least one yeast gene. These interactions are denoted as 3DID reference set and compared with a set of domains induced by top-ranking inferred physical contacts. More specifically, for each method, all domain pairs were ranked according to the best-ranking inferred physical protein contact that could be formed by the domain pair. The results of this evaluation are presented in Fig. 3A. Again, the SA and ISA methods significantly outperform other approaches over the range of 3,000 to 4,000 inferred physical contacts that are reliably supported by experimental data. At the same time, both SA and ISA perform comparably to the Y2H binary experimental data set with about 240 true domain interactions at a rank cutoff of 4,000 physical contacts.

Bottom Line: Our results show that raw purification data can indeed be exploited to determine high-confidence physical protein contacts within protein complexes.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.

View Article: PubMed Central - PubMed

Affiliation: Max Planck Institute for Informatics, Saarbr├╝cken, Germany. sven@mpi-inf.mpg.de

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.

Show MeSH