In silico prediction of physical protein interactions and characterization of interactome orphans

Nature Methods

Volumn 12, Issue 1, 2014, Pages 79-84

  Kotlyar, Max ^a   Pastrello, Chiara ^a,b   Pivetta, Flavia ^b   Lo Sardo, Alessandra ^b   Cumbaa, Christian ^a   Li, Han ^c   Naranian, Taline ^c   Niu, Yun ^a,d   Ding, Zhiyong ^e   Vafaee, Fatemeh ^a,f   Broackes Carter, Fiona ^a   Petschnigg, Julia ^g   Mills, Gordon B ^e   Jurisicova, Andrea ^c   Stagljar, Igor ^g   Maestro, Roberta ^b   Jurisica, Igor ^a,g,h,i  

^a PRINCESS MARGARET HOSPITAL   (Canada)

^b CENTRO DI RIFERIMENTO ONCOLOGICO   (Italy)

^c MOUNT SINAI HOSPITAL   (Canada)

^d NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

^e UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

^f UNIVERSITY OF SYDNEY   (Australia)

^g UNIVERSITY OF TORONTO   (Canada)

^h UNIVERSITY OF TORONTO   (Canada)

ⁱ UNIVERSITY HEALTH NETWORK   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CARBOHYDRATE METABOLISM; COMPUTER MODEL; COMPUTER PREDICTION; DATA MINING; DETOXIFICATION; EXTRACELLULAR MATRIX; GENETIC ASSOCIATION; GOLD STANDARD; HUMAN; PRIORITY JOURNAL; PROTEIN FUNCTION; PROTEIN PROTEIN INTERACTION; BIOLOGY; COMPUTER PROGRAM; COMPUTER SIMULATION; PHYSIOLOGY; PROCEDURES; PROTEIN ANALYSIS; VALIDATION STUDY;

PROTEIN P53; PROTEOME;

COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATA MINING; HUMANS; PROTEIN INTERACTION MAPPING; PROTEOME; SOFTWARE; TUMOR SUPPRESSOR PROTEIN P53;

EID: 84925028000     PISSN: 15487091     EISSN: 15487105     Source Type: Journal    
DOI: 10.1038/nmeth.3178     Document Type: Article

References (47)

1. Cusick, M.E. Et al. Literature-curated protein interaction datasets. Nat. Methods 6, 39-46 (2009).
2. Pastrello, C. Et al. Integration, visualization and analysis of human interactome. Biochem. Biophys. Res. Commun. 445, 757-773 (2014).
3. Bork, P. Et al. Protein interaction networks from yeast to human. Curr. Opin. Struct. Biol. 14, 292-299 (2004).
4. Stumpf, M.P. Et al. Estimating the size of the human interactome. Proc. Natl. Acad. Sci. USA 105, 6959-6964 (2008).
5. Venkatesan, K. Et al. An empirical framework for binary interactome mapping. Nat. Methods 6, 83-90 (2009).
6. Edwards, A.M. Et al. Too many roads not taken. Nature 470, 163-165 (2011).
7. Braun, P. Et al. An experimentally derived confidence score for binary protein-protein interactions. Nat. Methods 6, 91-97 (2009).
8. Brückner, A., Polge, C., Lentze, N., Auerbach, D. & Schlattner, U. Yeast two-hybrid, a powerful tool for systems biology. Int. J. Mol. Sci. 10, 2763-2788 (2009).
9. Wodak, S.J., Pu, S., Vlasblom, J. & Séraphin, B. Challenges and rewards of interaction proteomics. Mol. Cell. Proteomics 8, 3-18 (2009).
10. Schwartz, A.S., Yu, J., Gardenour, K.R., Finley, R.L. Jr. & Ideker, T. Cost-effective strategies for completing the interactome. Nat. Methods 6, 55-61 (2009).
11. Rhodes, D.R. Et al. Probabilistic model of the human protein-protein interaction network. Nat. Biotechnol. 23, 951-959 (2005).
12. Scott, M.S. & Barton, G.J. Probabilistic prediction and ranking of human protein-protein interactions. BMC Bioinformatics 8, 239 (2007).
13. Kim, J.H. & Pearl,, J. in Proc. IJCAI 190-193 (Morgan Kaufmann, 1983).
14. Petschnigg, J. Et al. The mammalian-membrane two-hybrid assay (MaMTH) for probing membrane-protein interactions in human cells. Nat. Methods 11, 585-592 (2014).
15. Elefsinioti, A. Et al. Large-scale de novo prediction of physical protein-protein association. Mol. Cell. Proteomics 10, M111.010629 (2011).
16. Zhang, Q.C. Et al. Structure-based prediction of protein-protein interactions on a genome-wide scale. Nature 490, 556-560 (2012).
17. D'haeseleer, P. & Church, G.M. in Proc. IEEE Comput. Syst. Bioinform. Conf. 216-223 (IEEE, 2004).
18. Kang, H.S. Et al. NABP1, a novel RORg-regulated gene encoding a single-stranded nucleic-acid-binding protein. Biochem. J. 397, 89-99 (2006).
19. Krokeide, S.Z. Et al. Human NEIL3 is mainly a monofunctional DNA glycosylase removing spiroimindiohydantoin and guanidinohydantoin. DNA Repair (Amst.) 12, 1159-1164 (2013).
20. Menendez, D., Inga, A. & Resnick, M.A. The expanding universe of p53 targets. Nat. Rev. Cancer 9, 724-737 (2009).
21. Wang, W. Et al. Identification of rare DNA variants in mitochondrial disorders with improved array-based sequencing. Nucleic Acids Res. 39, 44-58 (2011).
22. Vaseva, A.V. & Moll, U.M. The mitochondrial p53 pathway. Biochim. Biophys. Acta 1787, 414-420 (2009).
23. Gordon, S., Akopyan, G., Garban, H. & Bonavida, B. Transcription factor YY1: structure, function, and therapeutic implications in cancer biology. Oncogene 25, 1125-1142 (2006).
24. Tanikawa, C. Et al. Regulation of protein citrullination through p53/PADI4 network in DNA damage response. Cancer Res. 69, 8761-8769 (2009).
25. Ashburner, M. Et al. Gene Ontology: tool for the unification of biology. Nat. Genet. 25, 25-29 (2000).
26. Hunter, S. Et al. InterPro: the integrative protein signature database. Nucleic Acids Res. 37, D211-D215 (2009).
27. Imming, P., Sinning, C. & Meyer, A. Drugs, their targets and the nature and number of drug targets. Nat. Rev. Drug Discov. 5, 821-834 (2006).
28. Su, A.I. Et al. A gene atlas of the mouse and human protein-encoding transcriptomes. Proc. Natl. Acad. Sci. USA 101, 6062-6067 (2004).
29. Roth, R.B. Et al. Gene expression analyses reveal molecular relationships among 20 regions of the human CNS. Neurogenetics 7, 67-80 (2006).
30. Wang, E.T. Et al. Alternative isoform regulation in human tissue transcriptomes. Nature 456, 470-476 (2008).
31. Krupp, M. Et al. RNA-Seq Atlas-a reference database for gene expression profiling in normal tissue by next-generation sequencing. Bioinformatics 28, 1184-1185 (2012).
32. Uhlen, M. Et al. Towards a knowledge-based Human Protein Atlas. Nat. Biotechnol. 28, 1248-1250 (2010).
33. The UniProt Consortium. The Universal Protein Resource (UniProt) in 2010. Nucleic Acids Res. 38, D142-D148 (2010).
34. Brown, K.R. & Jurisica, I. Unequal evolutionary conservation of human protein interactions in interologous networks. Genome Biol. 8, R95 (2007).
35. Piccinin, S. Et al. A "twist box" code of p53 inactivation: twist box: p53 interaction promotes p53 degradation. Cancer Cell 22, 404-415 (2012).
36. Hupp, T.R., Hayward, R.L. & Vojtesek, B. Strategies for p53 reactivation in human sarcoma. Cancer Cell 22, 283-285 (2012).
37. Sprinzak, E. & Margalit, H. Correlated sequence-signatures as markers of protein-protein interaction. J. Mol. Biol. 311, 681-692 (2001).
38. Zhang, Y. Et al. Systematic analysis, comparison, and integration of disease based human genetic association data and mouse genetic phenotypic information. BMC Med. Genomics 3, 1 (2010).
39. Osborne, J.D. Et al. Annotating the human genome with Disease Ontology. BMC Genomics 10 (suppl. 1), S6 (2009).
40. Davis, A.P. Et al. The Comparative Toxicogenomics Database: update 2011. Nucleic Acids Res. 39, D1067-D1072 (2011).
41. Kotlyar, M., Fortney, K. & Jurisica, I. Network-based characterization of drug-regulated genes, drug targets, and toxicity. Methods 57, 499-507 (2012).
42. Maglott, D., Ostell, J., Pruitt, K.D. & Tatusova, T. Entrez Gene: gene-centered information at NCBI. Nucleic Acids Res. 35, D26-D31 (2007).
43. Hedges, S.B., Dudley, J. & Kumar, S. TimeTree: a public knowledge-base of divergence times among organisms. Bioinformatics 22, 2971-2972 (2006).
44. Toll-Riera, M. Et al. Origin of primate orphan genes: a comparative genomics approach. Mol. Biol. Evol. 26, 603-612 (2009).
45. Barshir, R. Et al. The TissueNet database of human tissue protein-protein interactions. Nucleic Acids Res. 41, D841-D844 (2013).
46. Birzele, F., Gewehr, J.E. & Zimmer, R. AutoPSI: a database for automatic structural classification of protein sequences and structures. Nucleic Acids Res. 36, D398-D401 (2008).
47. Ward, J.J., Sodhi, J.S., McGuffin, L.J., Buxton, B.F. & Jones, D.T. Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. J. Mol. Biol. 337, 635-645 (2004).