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Physical and in silico approaches identify DNA-PK in a Tax DNA-damage response interactome.

Ramadan E, Ward M, Guo X, Durkin SS, Sawyer A, Vilela M, Osgood C, Pothen A, Semmes OJ - Retrovirology (2008)

Bottom Line: The resulting Tax interactome will have significant utility toward defining new and understanding known activities of this important viral protein.When this rank list was compared to the list of physical Tax-binding proteins, DNA-PK was the highest ranked protein common to both lists.We present this methodology as an approach to discovery and as a means of validating components of a consensus Tax interactome.

View Article: PubMed Central - HTML - PubMed

Affiliation: George L, Wright Center for Biomedical Proteomics, Eastern Virginia Medical School, Norfolk, VA, USA. semmesoj@evms.edu

ABSTRACT

Background: We have initiated an effort to exhaustively map interactions between HTLV-1 Tax and host cellular proteins. The resulting Tax interactome will have significant utility toward defining new and understanding known activities of this important viral protein. In addition, the completion of a full Tax interactome will also help shed light upon the functional consequences of these myriad Tax activities. The physical mapping process involved the affinity isolation of Tax complexes followed by sequence identification using tandem mass spectrometry. To date we have mapped 250 cellular components within this interactome. Here we present our approach to prioritizing these interactions via an in silico culling process.

Results: We first constructed an in silico Tax interactome comprised of 46 literature-confirmed protein-protein interactions. This number was then reduced to four Tax-interactions suspected to play a role in DNA damage response (Rad51, TOP1, Chk2, 53BP1). The first-neighbor and second-neighbor interactions of these four proteins were assembled from available human protein interaction databases. Through an analysis of betweenness and closeness centrality measures, and numbers of interactions, we ranked proteins in the first neighborhood. When this rank list was compared to the list of physical Tax-binding proteins, DNA-PK was the highest ranked protein common to both lists. An overlapping clustering of the Tax-specific second-neighborhood protein network showed DNA-PK to be one of three bridge proteins that link multiple clusters in the DNA damage response network.

Conclusion: The interaction of Tax with DNA-PK represents an important biological paradigm as suggested via consensus findings in vivo and in silico. We present this methodology as an approach to discovery and as a means of validating components of a consensus Tax interactome.

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The G1 first neighborhood network for Rad51, TOP1, Chk2 and 53BP1. The four initial proteins (yellow) were used to generate a network via interrogation of the Human Protein Reference Database. Protein-protein interactions are indicated by lines. Proteins with two or more shared interactions will form a core. PRKDC (DNA-PK) is also highlighted.
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Figure 1: The G1 first neighborhood network for Rad51, TOP1, Chk2 and 53BP1. The four initial proteins (yellow) were used to generate a network via interrogation of the Human Protein Reference Database. Protein-protein interactions are indicated by lines. Proteins with two or more shared interactions will form a core. PRKDC (DNA-PK) is also highlighted.

Mentions: In this section we conducted a query for immediate binding partners of a selected group of known Tax-binding proteins. Our starting group of Tax-binding proteins, Rad51, TOP1, CHEK2 (Chk2), and TP53BP1 (53BP1), known to play a role in the DNA repair response, was referred to as the set C1. The goal was to carefully extend the four protein dataset outward to include the first neighbors of known Tax-binding proteins. We then created a network consisting of the first neighbor interactions of these four proteins with the world of proteins within the HRPD, which we call G1 = 1NN (C1). This sub-network, G1, consists of a set of 50 proteins involved in 112 interactions as shown in figure 1. The G1 sub-network has a diameter of 5, and average path length of 2.7, which are consistent with a small-world network.


Physical and in silico approaches identify DNA-PK in a Tax DNA-damage response interactome.

Ramadan E, Ward M, Guo X, Durkin SS, Sawyer A, Vilela M, Osgood C, Pothen A, Semmes OJ - Retrovirology (2008)

The G1 first neighborhood network for Rad51, TOP1, Chk2 and 53BP1. The four initial proteins (yellow) were used to generate a network via interrogation of the Human Protein Reference Database. Protein-protein interactions are indicated by lines. Proteins with two or more shared interactions will form a core. PRKDC (DNA-PK) is also highlighted.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2576351&req=5

Figure 1: The G1 first neighborhood network for Rad51, TOP1, Chk2 and 53BP1. The four initial proteins (yellow) were used to generate a network via interrogation of the Human Protein Reference Database. Protein-protein interactions are indicated by lines. Proteins with two or more shared interactions will form a core. PRKDC (DNA-PK) is also highlighted.
Mentions: In this section we conducted a query for immediate binding partners of a selected group of known Tax-binding proteins. Our starting group of Tax-binding proteins, Rad51, TOP1, CHEK2 (Chk2), and TP53BP1 (53BP1), known to play a role in the DNA repair response, was referred to as the set C1. The goal was to carefully extend the four protein dataset outward to include the first neighbors of known Tax-binding proteins. We then created a network consisting of the first neighbor interactions of these four proteins with the world of proteins within the HRPD, which we call G1 = 1NN (C1). This sub-network, G1, consists of a set of 50 proteins involved in 112 interactions as shown in figure 1. The G1 sub-network has a diameter of 5, and average path length of 2.7, which are consistent with a small-world network.

Bottom Line: The resulting Tax interactome will have significant utility toward defining new and understanding known activities of this important viral protein.When this rank list was compared to the list of physical Tax-binding proteins, DNA-PK was the highest ranked protein common to both lists.We present this methodology as an approach to discovery and as a means of validating components of a consensus Tax interactome.

View Article: PubMed Central - HTML - PubMed

Affiliation: George L, Wright Center for Biomedical Proteomics, Eastern Virginia Medical School, Norfolk, VA, USA. semmesoj@evms.edu

ABSTRACT

Background: We have initiated an effort to exhaustively map interactions between HTLV-1 Tax and host cellular proteins. The resulting Tax interactome will have significant utility toward defining new and understanding known activities of this important viral protein. In addition, the completion of a full Tax interactome will also help shed light upon the functional consequences of these myriad Tax activities. The physical mapping process involved the affinity isolation of Tax complexes followed by sequence identification using tandem mass spectrometry. To date we have mapped 250 cellular components within this interactome. Here we present our approach to prioritizing these interactions via an in silico culling process.

Results: We first constructed an in silico Tax interactome comprised of 46 literature-confirmed protein-protein interactions. This number was then reduced to four Tax-interactions suspected to play a role in DNA damage response (Rad51, TOP1, Chk2, 53BP1). The first-neighbor and second-neighbor interactions of these four proteins were assembled from available human protein interaction databases. Through an analysis of betweenness and closeness centrality measures, and numbers of interactions, we ranked proteins in the first neighborhood. When this rank list was compared to the list of physical Tax-binding proteins, DNA-PK was the highest ranked protein common to both lists. An overlapping clustering of the Tax-specific second-neighborhood protein network showed DNA-PK to be one of three bridge proteins that link multiple clusters in the DNA damage response network.

Conclusion: The interaction of Tax with DNA-PK represents an important biological paradigm as suggested via consensus findings in vivo and in silico. We present this methodology as an approach to discovery and as a means of validating components of a consensus Tax interactome.

Show MeSH
Related in: MedlinePlus