期刊论文详细信息
BMC Bioinformatics
Visualisation and graph-theoretic analysis of a large-scale protein structural interactome
Dan Bolser2  Panos Dafas1  Richard Harrington2  Jong Park3  Michael Schroeder1 
[1] Department of Computing, City University, London EC1V 0HB, UK
[2] Dunn Human Nutrition Unit, Medical Research Council, Cambridge CB2 2XY, UK
[3] Department of BioSystems, Korea Advanced Institute of Science and Technology, Korea
关键词: PSIMAP.;    PSIEYE;    Taxonomic Diversity;    Interaction Rank;    Graph-theory;    Interactomics;    Protein Interaction;    Structural Interactome;   
Others  :  1171857
DOI  :  10.1186/1471-2105-4-45
 received in 2003-07-31, accepted in 2003-10-08,  发布年份 2003
PDF
【 摘 要 】

Background

Large-scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in the PDB. PSIMAP incorporates both functional and evolutionary information into a single network.

Results

We present a global analysis of PSIMAP using several distinct network measures relating to centrality, interactivity, fault-tolerance, and taxonomic diversity. We found the following results: Centrality: we show that the center and barycenter of PSIMAP do not coincide, and that the superfamilies forming the barycenter relate to very general functions, while those constituting the center relate to enzymatic activity. Interactivity: we identify the P-loop and immunoglobulin superfamilies as the most highly interactive. We successfully use connectivity and cluster index, which characterise the connectivity of a superfamily's neighbourhood, to discover superfamilies of complex I and II. This is particularly significant as the structure of complex I is not yet solved. Taxonomic diversity: we found that highly interactive superfamilies are in general taxonomically very diverse and are thus amongst the oldest. Fault-tolerance: we found that the network is very robust as for the majority of superfamilies removal from the network will not break up the network.

Conclusions

Overall, we can single out the P-loop containing nucleotide triphosphate hydrolases superfamily as it is the most highly connected and has the highest taxonomic diversity. In addition, this superfamily has the highest interaction rank, is the barycenter of the network (it has the shortest average path to every other superfamily in the network), and is an articulation vertex, whose removal will disconnect the network. More generally, we conclude that the graph-theoretic and taxonomic analysis of PSIMAP is an important step towards the understanding of protein function and could be an important tool for tracing the evolution of life at the molecular level.

【 授权许可】

   
2003 Bolser et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.

【 预 览 】
附件列表
Files Size Format View
20150420021506414.pdf 3089KB PDF download
Figure 17. 40KB Image download
Figure 16. 26KB Image download
Figure 15. 19KB Image download
Figure 14. 48KB Image download
Figure 13. 64KB Image download
Figure 12. 32KB Image download
Figure 11. 41KB Image download
Figure 10. 30KB Image download
Figure 9. 19KB Image download
Figure 8. 28KB Image download
Figure 7. 38KB Image download
Figure 6. 44KB Image download
Figure 5. 39KB Image download
Figure 4. 12KB Image download
Figure 3. 48KB Image download
Figure 2. 42KB Image download
Figure 1. 37KB Image download
【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Figure 9.

Figure 10.

Figure 11.

Figure 12.

Figure 13.

Figure 14.

Figure 15.

Figure 16.

Figure 17.

【 参考文献 】
  • [1]Ito T, et al.: A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc Natl Acad Sci USA 2001, 98(8):4569-4574.
  • [2]McCraith S, et al.: Genome-wide analysis of vaccinia virus protein-protein interactions. Proc Natl Acad Sci USA 2000, 97(9):4879-4884.
  • [3]Uetz P, et al.: A comprehensive analysis of protein-protein interactions in: Saccharomyces cerevisiae. Nature 2000, 403(6770):623-7.
  • [4]Walhout AJ, et al.: Protein Interaction Mapping in C. elegans Using Proteins Involved in Vulval Development. Science 1999, 5450:116-121.
  • [5]Fromont-Racine M, et al.: Genome-wide protein interaction screens reveal functional networks involving Sm-like proteins. Yeast 2000, 17(2):95-110.
  • [6]Fromont-Racine M, Rain JC, Legrain P: Toward a functional analysis of the yeast genome through exhaustive two-hybrid screens. Nat Genet 1997, 16(3):277-82.
  • [7]Ito T, et al.: Toward a protein-protein interaction map of the budding yeast: A comprehensive system to examine two-hybrid interactions in all possible combinations between the yeast proteins. Proc Natl Acad Sci U S A 2000, 97(3):1143-7.
  • [8]Flajolet M, et al.: A genomic approach of the hepatitis C virus generates a protein interaction map. Gene 2000, 242(1–2):369-79.
  • [9]Rain JC, et al.: The protein-protein interaction map of Helicobacter pylori. Nature 2001, 409(6817):211-5.
  • [10]Hartwell LH, et al.: From molecular to modular cell biology. Nature 1999, 6761(Supp 1):C47-C54.
  • [11]Vidal M: A Biological Atlas of Functional Maps. Cell 2001, 104(3):333-340.
  • [12]Fellenberg M, et al.: Integrative Analysis of Protein Interaction Data. In in Intelligent systems for molecular biology. La Jolla, CA: AAAI Press; 2000.
  • [13]Lappe M, et al.: Generating protein interaction maps from incomplete data: application to fold assignment. Bioinformatics 2001, 17(Suppl 1):S149-56.
  • [14]Marcotte EM, et al.: Detecting protein function and protein-protein interactions from genome sequences. Science 1999, 285(5428):751-3.
  • [15]Dandekar T, et al.: Conservation of gene order: a fingerprint of proteins that physically interact. Trends Biochem Sci 1998, 23(9):324-8.
  • [16]Enright AJ, et al.: Protein interaction maps for complete genomes based on gene fusion events. Nature 1999, 402(6757):86-90.
  • [17]Huynen M, et al.: Predicting protein function by genomic context: quantitative evaluation and qualitative inferences. Genome Res 2000, 10(8):1204-10.
  • [18]Pellegrini M, et al.: Assigning protein functions by comparative genome analysis: protein phylogenetic profiles. Proc Natl Acad Sci U S A 1999, 96(8):4285-8.
  • [19]Berman HM, et al.: The Protein Data Bank. Nucleic Acids Res 2000, 28(1):235-42.
  • [20]Park J, Lappe M, Teichmann SA: Mapping protein family interactions: intramolecular and intermolecular protein family interaction repertoires in the PDB and yeast. J Mol Biol 2001, 307(3):929-38.
  • [21]Matthews LR, et al.: Identification of potential interaction networks using sequence-based searches for conserved protein-protein interactions or "interologs". Genome Res 2001, 11(12):2120-6.
  • [22]Wojcik J, Schachter V: Protein-protein interaction map inference using interacting domain profile pairs. Bioinformatics 2001, 17(Suppl 1):S296-305.
  • [23]Deng M, et al.: Inferring domain-domain interactions from protein-protein interactions. Genome Res 2002, 12(10):1540-8.
  • [24]Murzin AG, et al.: SCOP: A Structural Classification of Proteins Database for the Investigation of Sequences and Structures. Journal of Molecular Biology 1995, 247(4):536.
  • [25]Orengo CA, et al.: CATH – a hierarchic classification of protein domain structures. Structure 1997, 5:1093-108.
  • [26]Holm L, Sander C: Mapping the protein universe. Science 1996, 273:595-603.
  • [27]Sonnhammer EL, Eddy SR, Durbin R: Pfam: a comprehensive database of protein domain families based on seed alignments. in Proteins 1997, 28:405-420.
  • [28]Aloy P, Russell RB: Interrogating protein interaction networks through structural biology. Proc Natl Acad Sci USA 2002, 99(9):5896-5901.
  • [29]Chothia C: Proteins. One thousand families for the molecular biologist. Nature 1992, 357(6379):543-4.
  • [30]Orengo CA, Jones DT, Thornton JM: Protein superfamilies and domain superfolds. Nature 1994, 372(6507):631-4.
  • [31]Alexandrov NN, Go N: Biological meaning, statistical significance, and classification of local spatial similarities in nonhomologous proteins. Protein Sci 1994, 3(6):866-75.
  • [32]Wang ZX: How many fold types of protein are there in nature? Proteins 1996, 26(2):186-91.
  • [33]Zhang CT.: Relations of the numbers of protein sequences, families and folds. Protein Engineering 1997, 10(7):757-761.
  • [34]Gough J, et al.: Assignment of homology to genome sequences using a library of hidden Markov models that represent all proteins of known structure. J Mol Biol 2001, 313(4):903-19.
  • [35]Tsai CJ, et al.: Protein-protein interfaces: architectures and interactions in protein-protein interfaces and in protein cores. Their similarities and differences. Crit Rev Biochem Mol Biol 1996, 31(2):127-52.
  • [36]Bennett MJ, Choe S, Eisenberg D: Domain swapping: entangling alliances between proteins. Proc Natl Acad Sci U S A 1994, 91(8):3127-31.
  • [37]Miller S: The structure of interfaces between subunits of dimeric and tetrameric proteins. Protein Eng 1989, 3(2):77-83.
  • [38]Jones S, Marin A, Thornton JM: Protein domain interfaces: characterization and comparison with oligomeric protein interfaces. Protein Eng 2000, 13(2):77-82.
  • [39]Bader GD, Hogue CW: BIND – a data specification for storing and describing biomolecular interactions, molecular complexes and pathways. Bioinformatics 2000, 16(5):465-77.
  • [40]Xenarios I, et al.: DIP: the Database of Interacting Proteins. Nucleic Acids Research 2000, 28(1):289-291.
  • [41]Ju BH, et al.: Visualization and analysis of protein interactions. Bioinformatics 2003, 19:317-318.
  • [42]Enright AJ, Ouzounis CA: BioLayout-an automatic graph layout algorithm for similarity visualization. Bioinformatics 2001, 17(9):853-854.
  • [43]Mrowka R: A Java applet for visualizing protein-protein interaction. Bioinformatics 2001, 17(7):669-670.
  • [44]Jeong H, et al.: Lethality and centrality in protein networks. Nature 2001, 6833:41.
  • [45]Wuchty S, Stadler PF: Centers of complex networks. J Theor Biol 2003, 223(1):45-53.
  • [46]Schwikowski B, Uetz P, Fields S: A network of protein-protein interactions in yeast. Nature Biotechnology 2000, 18(12):1257-1261.
  • [47]Schroder M, et al.: PSIEYE: A tool for the graph-theoretic analysis of protein interaction networks. Bioinformatics[submitted]
  • [48]Park J, Bolser D: Conservation of Protein Interaction Network in Evolution. Genome Informatics Series 2001, 135-140.
  • [49]Hemmingsen SM, et al.: Homologous plant and bacterial proteins chaperone oligomeric protein assembly. Nature 1988, 333(6171):330-4.
  • [50]Anantharaman V, Koonin EV, Aravind L: Regulatory Potential, Phyletic Distribution and Evolution of Ancient, Intracellular Small-molecule-binding Domains. Journal of Molecular Biology 2001, 307(5):1271-1292.
  • [51]Hanks SK, Hunter T: Protein kinases 6: The eukaryotic protein kinase superfamily: kinase (catalytic) domain structure and classification. Faseb Journal 1995, 9(8):576.
  • [52]Djordjevic S, Driscoll PC: Structural insight into substrate specificity and regulatory mechanisms of phosphoinositide 3-kinases. Trends in Biochemical Sciences 2002, 27(8):426-432.
  • [53]Watts DJ, Strogatz SH: Collective dynamics of 'small-world' networks. Nature 1998, 393(6684):440-2.
  • [54]Altschul SF, et al.: Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997, 25(17):3389-402.
  • [55]Dongen Sv: Graph Clustering by Flow Simulation. PhD thesis. University of Utrecht, Centre for Mathematics and Computer Science 2000.
  • [56]Wheeler DL, et al.: Database resources of the National Center for Biotechnology: Information. Nucleic Acids Res 2000, 28(1):10-4.
  • [57]Wagner A, Fell DA: The small world inside large metabolic networks. Proc R Soc Lond Biol Sci 2001, 1478:1803-1810.
  • [58]Christensen B, et al.: Homocysteine remethylation during nitrous oxide exposure of: cells cultured in media containing various concentrations of folates. J Pharmacol Exp Ther 1992, 261(3):1096-105.
  • [59]Allen RH, et al.: Metabolic abnormalities in cobalamin (vitamin B12) and folate: deficiency. Faseb J 1993, 7(14):1344-53.
  • [60]Doolittle RF: Convergent evolution: the need to be explicit. Trends Biochem Sci 1994, 19(1):15-8.
  • [61]Bader GD, Hogue CW: An automated method for finding molecular complexes in: large protein interaction networks. BMC Bioinformatics 2003, 4(1):2. BioMed Central Full Text
  文献评价指标  
  下载次数:0次 浏览次数:1次