Complex tree: the basic framework of protein-protein interaction networks

DaiChuan Ma, YuanBo Diao, YiZhou Li, YanZi Guo, Jiang Wu, MengLong Li

.

DOI: 10.4236/ns.2010.29122                

Abstract

In living cells, proteins are dynamically connec ted through biochemical reactions, so its functi onal features are properly encoded into protein protein interaction networks (PINs). Up to pres ent, many efforts have been devoted to exploring the basic feature of PINs. However, it is still a challenging problem to explore a universal pr operty of PINs. Here we employed the complex networks theory to analyze the proteinprotein interactions from Database of Interacting Prot ein. Complex tree: the unique framework of PINs was revealed by three topological properties of the giant component of PINs (GCOP), including rightskewed degree distributions, relatively sm all clustering coefficients and short characteristic path lengths. Furthermore, we proposed a no nlinearly growth model: complex tree model to reflect the tree framework, the simulation resu lts of this model showed that GCOPs were well represented by our model, which could be help ful for understanding the treestructure: basic framework of PINs. Source code and binaries freely available for download at http://cic.scu. edu.cn/bioinformatics/STM/STM_code.rar.

Keywords

Complex Networks; Complex Tree; Pins; Model Simulation

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Ito, T., Chiba, T., Ozawa, R., Yoshida, M., Hattori, M. and Sakaki, Y. (2001) A comprehensive twohybrid analysis to explore the yeast protein interactome. Proceedings of the National Academy of Sciences of the United States of America, 98(8), 45694574.
[2]	Gavin, A.C., Bosche, M., Krause, R., Grandi, P., Marzioch, M. and Bauer, A. (2002) Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature, 415(6868), 141147.
[3]	Ho, Y., Gruhler, A., Heilbut, A., Bader, G. D., Moore, L. and Adams, S.L. (2002) Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature, 415(6868), 180183.
[4]	Zhu, H., Bilgin, M., Bangham, R., Hall, D., Casamayor, A. and Bertone, P. (2001) Global analysis of protein activities using proteome chips. Science, 293(5537), 2101 2105.
[5]	Jeong, H., Tombor, B., Albert, R., Oltvai, Z.N. and Barabasi, A.L. (2000) The largescale organization of metabolic networks. Nature, 407(6804), 651654.
[6]	Barabasi, A.L., Oltvai, Z.N., Wuchty, S. (2004) Characteristics of biological networks. In: BenNaim, E., Frau en felder, H. and Toroczkai, Z., Eds., Complex Networks, SpringerVerlag, 443457.
[7]	Albert, R. (2005) Scalefree networks in cell biology. Journal of Cell Science, 118(21), 49474957.
[8]	Bork, P., Jensen, L.J., von Mering, C., Ramani, A.K., Lee, I. and Marcotte, E.M. (2004) Protein interaction networks from yeast to human. Current Opinion in Structural Biology, 14(3), 292299.
[9]	Eungdamrong, N.J. and Iyengar, R. (2004) Modeling cell signaling networks. Biology of the Cell, 96(5), 355362.
[10]	Giot, L., Bader, J.S., Brouwer, C., Chaudhuri, A., Kuang, B. and Li, Y. (2003) A protein interaction map of Drosophila melanogaster. Science, 302(5651), 17271736.
[11]	Gursoy, A., Keskin, O. and Nussinov, R. (2008) Topological properties of protein interaction networks from a structural perspective. Biochemical Society Transactions, 36, 13981403.
[12]	Yook, S.H., Oltvai, Z.N. and Barabasi, A.L. (2004) Functional and topological characterization of protein interaction networks. Proteomics, 4(4), 928942.
[13]	Jeong, H., Mason, S.P., Barabasi, A.L. and Oltvai, Z.N. (2001) Lethality and centrality in protein networks. Nature, 411(6833), 4142.
[14]	Ng, K.L., Lee, P.H., Huang, C.H., Fang, J.F., Hsiao, H.W., Tsai, J.J.P. (2006) Hierarchical structure of the protein protein interaction networks. Chinese Journal of Physics, 44(1), 6777.
[15]	Deeds, E.J., Ashenberg, O. and Shakhnovich, E.I. (2006) A simple physical model for scaling in proteinprotein interaction networks. Proceedings of the National Academy of Sciences of the United States of America, 103(2), 311316.
[16]	Rhodes, D.R., Tomlins, S.A., Varambally, S., Mahavisno, V., Barrette, T. and KalyanaSundaram, S. (2005) Probabilistic model of the human proteinprotein interaction network. Nature Biotechnology, 23(8), 951959.
[17]	Newman, M.E.J. (2007) Component sizes in networks with arbitrary degree distributions. Physical Review E, 76(4), 4.
[18]	Clauset, A., Shalizi, C.R. and Newman, M.E.J. (2009) PowerLaw Distributions in Empirical Data. SIAM Review, 51(4), 661703.
[19]	Newman, M.E.J. (2003) The structure and function of complex networks. SIAM Review, 45(2), 167256.
[20]	Watts, D.J. and Strogatz, S.H. (1998) Collective dynamics of “smallworld” networks. Nature, 393(6684), 440 442.
[21]	Barabasi, A.L., Dezso, Z., Ravasz, E., SoonHyung, Y. and Oltvai, Z. (2003) Scalefree and hierarchical structures in complex networks. AIP Conference Proceedings, 661, 116.
[22]	Barabasi, A.L., Ravasz, E. and Vicsek, T. (2001) Deterministic scalefree networks. Physica aStatistical Mechanics and its Applications, 299(34), 559564.
[23]	Chen, M., Yu, B.M., Xu, P. and Chen, J. (2007) A new deterministic complex network model with hierarchical structure. Physica aStatistical Mechanics and its Applications, 385(2), 707717.
[24]	Kim, D.H., Rodgers, G.J., Kahng, B. and Kim, D. (2005) Modelling hierarchical and modular complex networks: division and independence. Physica aStatistical Mechanics and Its Applications, 351(24), 671679.
[25]	Barabasi, A.L., Albert, R. and Jeong, H. (1999) Meanfield theory for scalefree random networks. Physica A: Statistical Mechanics and its Applications, 272(12), 173187.
[26]	Ravasz, E., Somera, A.L., Mongru, D.A., Oltvai, Z.N., Barabasi, A.L. (2002) Hierarchical organization of modularity in metabolic networks. Science, 297(5586), 15511555.
[27]	Ravasz, E. and Barabasi, A.L. (2003) Hierarchical organization in complex networks. Physical Review E, 67(2), 026112.
[28]	Kim, D.H., Noh, J.D. and Jeong, H. (2004) Scalefree trees: The skeletons of complex networks. Physical Review E, 70(4), 046126
[29]	Newman, M.E.J. and Watts, D.J. (1999) Renormalization group analysis of the smallworld network model. Physics Letters A, 263(46), 341346.
[30]	Csardi G. and Nepusz T. (2006) The igraph software package for complex network research. Inter Journal, Complex Systems, 16951704.