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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 and experimentally obtained physical contacts involving protein kinases and phosphatases against the BGS and Kinase reference set of experimentally confirmed binary kinase and phosphatase interactions. Note that the SAINT scoring scheme assigns identical score values for its top 1262 inferred interactions. Therefore, SAINT performance curve seems to start at a later point than the curves of other methods.
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Figure 6: Assessment of inferred and experimentally obtained physical contacts involving protein kinases and phosphatases against the BGS and Kinase reference set of experimentally confirmed binary kinase and phosphatase interactions. Note that the SAINT scoring scheme assigns identical score values for its top 1262 inferred interactions. Therefore, SAINT performance curve seems to start at a later point than the curves of other methods.

Mentions: We assessed the performance of the scoring methods SAINT, Hart, ISA, and SA in inferring experimentally known kinase interactions from the BGS and Kinase reference sets (see Experimental procedures section for a description of the reference data). Note that, because of the involved computations or unavailable implementations of the PE and IDBOS methods, these scores could not be evaluated here. However, it has been reported elsewhere that PE was not able to distinguish between true and false interactions in this setting (18). As displayed in Fig. 6, the ISA score outperforms other general-purpose purification scoring schemes on both reference sets by a large margin. Only the highly specialized SAINT scoring scheme can identify slightly more physical contacts in the data. Importantly, however, the peptide counts employed as an integral part of SAINT require additional processing during the experimental setup. Such counts are neither available for the Large-Scale purifications nor for most other publicly available purification data. In contrast, the ISA scoring scheme is generally applicable to all raw purification data without the need for additional peptide count data.


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 and experimentally obtained physical contacts involving protein kinases and phosphatases against the BGS and Kinase reference set of experimentally confirmed binary kinase and phosphatase interactions. Note that the SAINT scoring scheme assigns identical score values for its top 1262 inferred interactions. Therefore, SAINT performance curve seems to start at a later point than the curves of other methods.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 6: Assessment of inferred and experimentally obtained physical contacts involving protein kinases and phosphatases against the BGS and Kinase reference set of experimentally confirmed binary kinase and phosphatase interactions. Note that the SAINT scoring scheme assigns identical score values for its top 1262 inferred interactions. Therefore, SAINT performance curve seems to start at a later point than the curves of other methods.
Mentions: We assessed the performance of the scoring methods SAINT, Hart, ISA, and SA in inferring experimentally known kinase interactions from the BGS and Kinase reference sets (see Experimental procedures section for a description of the reference data). Note that, because of the involved computations or unavailable implementations of the PE and IDBOS methods, these scores could not be evaluated here. However, it has been reported elsewhere that PE was not able to distinguish between true and false interactions in this setting (18). As displayed in Fig. 6, the ISA score outperforms other general-purpose purification scoring schemes on both reference sets by a large margin. Only the highly specialized SAINT scoring scheme can identify slightly more physical contacts in the data. Importantly, however, the peptide counts employed as an integral part of SAINT require additional processing during the experimental setup. Such counts are neither available for the Large-Scale purifications nor for most other publicly available purification data. In contrast, the ISA scoring scheme is generally applicable to all raw purification data without the need for additional peptide count data.

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