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Construction of protein phosphorylation networks by data mining, text mining and ontology integration: analysis of the spindle checkpoint.

Ross KE, Arighi CN, Ren J, Huang H, Wu CH - Database (Oxford) (2013)

Bottom Line: The integrated approach involves (i) text mining guided by RLIMS-P, a tool that identifies phosphorylation-related information in scientific literature; (ii) data mining from curated PPI databases; (iii) protein form and complex representation using the Protein Ontology (PRO); (iv) functional annotation using the Gene Ontology (GO); and (v) network visualization and analysis with Cytoscape.The phosphorylation networks we construct, centered on the human checkpoint kinase BUB1B (BubR1) and its yeast counterpart MAD3, offer a unique view of the spindle checkpoint that emphasizes biologically relevant phosphorylated forms, phosphorylation-state-specific PPIs and kinase-substrate relationships.Our approach for constructing protein phosphorylation networks can be applied to any biological process that is affected by phosphorylation.

View Article: PubMed Central - PubMed

Affiliation: Center for Bioinformatics and Computational Biology, 15 Innovation Way, Suite 205, University of Delaware, Newark, DE 19711, USA. ross@dbi.udel.edu

ABSTRACT
Knowledge representation of the role of phosphorylation is essential for the meaningful understanding of many biological processes. However, such a representation is challenging because proteins can exist in numerous phosphorylated forms with each one having its own characteristic protein-protein interactions (PPIs), functions and subcellular localization. In this article, we evaluate the current state of phosphorylation event curation and then present a bioinformatics framework for the annotation and representation of phosphorylated proteins and construction of phosphorylation networks that addresses some of the gaps in current curation efforts. The integrated approach involves (i) text mining guided by RLIMS-P, a tool that identifies phosphorylation-related information in scientific literature; (ii) data mining from curated PPI databases; (iii) protein form and complex representation using the Protein Ontology (PRO); (iv) functional annotation using the Gene Ontology (GO); and (v) network visualization and analysis with Cytoscape. We use this framework to study the spindle checkpoint, the process that monitors the assembly of the mitotic spindle and blocks cell cycle progression at metaphase until all chromosomes have made bipolar spindle attachments. The phosphorylation networks we construct, centered on the human checkpoint kinase BUB1B (BubR1) and its yeast counterpart MAD3, offer a unique view of the spindle checkpoint that emphasizes biologically relevant phosphorylated forms, phosphorylation-state-specific PPIs and kinase-substrate relationships. Our approach for constructing protein phosphorylation networks can be applied to any biological process that is affected by phosphorylation. Database URL: http://www.yeastgenome.org/

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The human BUB1B network. The BUB1B node is shown in red; other core spindle checkpoint proteins are shown in purple; nodes representing phosphorylation-state–specific forms are shown in blue. Triangles indicate protein kinases. Green and yellow edges are PPIs identified by text mining and data mining, respectively; blue edges connect kinases to their phosphorylated products; black edges indicate the has_part relation connecting protein complexes to their components.
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bat038-F2: The human BUB1B network. The BUB1B node is shown in red; other core spindle checkpoint proteins are shown in purple; nodes representing phosphorylation-state–specific forms are shown in blue. Triangles indicate protein kinases. Green and yellow edges are PPIs identified by text mining and data mining, respectively; blue edges connect kinases to their phosphorylated products; black edges indicate the has_part relation connecting protein complexes to their components.

Mentions: The BUB1B protein interaction network based on our text and data mining results is shown in Figure 2. Five of the seven core checkpoint proteins—MAD1L1, MAD2L1, BUB1, BUB3 and MPS1 (Figure 2, purple nodes)—are linked directly or indirectly to BUB1B via interactions we identified by text mining. AURKB, on the other hand, was incorporated into the network through a physical interaction with BUB1B that we identified by data mining. Thus, both text and data mining contributed critical pieces to the spindle checkpoint network.Figure 2.


Construction of protein phosphorylation networks by data mining, text mining and ontology integration: analysis of the spindle checkpoint.

Ross KE, Arighi CN, Ren J, Huang H, Wu CH - Database (Oxford) (2013)

The human BUB1B network. The BUB1B node is shown in red; other core spindle checkpoint proteins are shown in purple; nodes representing phosphorylation-state–specific forms are shown in blue. Triangles indicate protein kinases. Green and yellow edges are PPIs identified by text mining and data mining, respectively; blue edges connect kinases to their phosphorylated products; black edges indicate the has_part relation connecting protein complexes to their components.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3675891&req=5

bat038-F2: The human BUB1B network. The BUB1B node is shown in red; other core spindle checkpoint proteins are shown in purple; nodes representing phosphorylation-state–specific forms are shown in blue. Triangles indicate protein kinases. Green and yellow edges are PPIs identified by text mining and data mining, respectively; blue edges connect kinases to their phosphorylated products; black edges indicate the has_part relation connecting protein complexes to their components.
Mentions: The BUB1B protein interaction network based on our text and data mining results is shown in Figure 2. Five of the seven core checkpoint proteins—MAD1L1, MAD2L1, BUB1, BUB3 and MPS1 (Figure 2, purple nodes)—are linked directly or indirectly to BUB1B via interactions we identified by text mining. AURKB, on the other hand, was incorporated into the network through a physical interaction with BUB1B that we identified by data mining. Thus, both text and data mining contributed critical pieces to the spindle checkpoint network.Figure 2.

Bottom Line: The integrated approach involves (i) text mining guided by RLIMS-P, a tool that identifies phosphorylation-related information in scientific literature; (ii) data mining from curated PPI databases; (iii) protein form and complex representation using the Protein Ontology (PRO); (iv) functional annotation using the Gene Ontology (GO); and (v) network visualization and analysis with Cytoscape.The phosphorylation networks we construct, centered on the human checkpoint kinase BUB1B (BubR1) and its yeast counterpart MAD3, offer a unique view of the spindle checkpoint that emphasizes biologically relevant phosphorylated forms, phosphorylation-state-specific PPIs and kinase-substrate relationships.Our approach for constructing protein phosphorylation networks can be applied to any biological process that is affected by phosphorylation.

View Article: PubMed Central - PubMed

Affiliation: Center for Bioinformatics and Computational Biology, 15 Innovation Way, Suite 205, University of Delaware, Newark, DE 19711, USA. ross@dbi.udel.edu

ABSTRACT
Knowledge representation of the role of phosphorylation is essential for the meaningful understanding of many biological processes. However, such a representation is challenging because proteins can exist in numerous phosphorylated forms with each one having its own characteristic protein-protein interactions (PPIs), functions and subcellular localization. In this article, we evaluate the current state of phosphorylation event curation and then present a bioinformatics framework for the annotation and representation of phosphorylated proteins and construction of phosphorylation networks that addresses some of the gaps in current curation efforts. The integrated approach involves (i) text mining guided by RLIMS-P, a tool that identifies phosphorylation-related information in scientific literature; (ii) data mining from curated PPI databases; (iii) protein form and complex representation using the Protein Ontology (PRO); (iv) functional annotation using the Gene Ontology (GO); and (v) network visualization and analysis with Cytoscape. We use this framework to study the spindle checkpoint, the process that monitors the assembly of the mitotic spindle and blocks cell cycle progression at metaphase until all chromosomes have made bipolar spindle attachments. The phosphorylation networks we construct, centered on the human checkpoint kinase BUB1B (BubR1) and its yeast counterpart MAD3, offer a unique view of the spindle checkpoint that emphasizes biologically relevant phosphorylated forms, phosphorylation-state-specific PPIs and kinase-substrate relationships. Our approach for constructing protein phosphorylation networks can be applied to any biological process that is affected by phosphorylation. Database URL: http://www.yeastgenome.org/

Show MeSH
Related in: MedlinePlus