Analysis of dynamic biological networks from a three dimensional protein structure prospective
Most of current studies on biological networks are mainly based on the analysis of static properties without accounting for dynamic properties of biological networks. It has been found that the actual set of biological entities and their interactions may vary substantially depending on tissue samples and physiological conditions. Bossi and Lehner argued that within any particular cell or tissue of the human body not all protein interactions can occur [1]. Han et al. [2] highlighted that the biological role of topological hub proteins, i.e. those with many interactions, might vary depending on the time and location of the interactions they mediate.
By the incorporation of messenger RNA expression profiling data, Han et al. [2] concluded that hubs fall into one of two categories: 'party hubs', which interact with most of their partners simultaneously, and 'date hubs', which bind different partners at different locations and times. However, the validity of date/party hub distinction remains under debate. The properties related to the hub-centric view of modularity in PPI networks found by Han et al. [2] have been questioned by two recent papers published by Batada et al. [3], [4]. More recently, Agarwal et al. [5] found that claims of bimodality in partner co-expression do not appear to be robust. The observation of intermodular and intramodular hubs in the human interactome made by Taylor et al. [6] is not statistically significant and is susceptible to methodology changes, for example, changes in the techniques used to normalise expression data.
Based on our preliminary results [7] , this proposal will take the new step to rigorously scrutinise global dynamic properties of biological networks. It is anticipated that the project will initially focus on the analysis of protein interaction networks. It is aimed to revisit the date and party hub distinction from a three-dimensional structural prospective. A structural version of the protein interaction network will be constructed. The correlation of genomics features with the distinction of date and party hubs will be studied. Efficient visualization techniques used to visualize dynamics organization of protein interaction networks will be also developed.
References
[1] A. Bossi, B. Lehner B, “Tissue specificity and the human protein interaction network,” Mol Syst Biol. 2009, 5: 260.
[2] J. D. Han, N. Bertin, T. Hao, D.S. Goldberg, G.F. Berriz, L.V. Zhang, et al., “ Evidence for dynamically organised modularity in the yeast protein-protein interaction network,” Nature, 2001, 430(6995), pp. 88-93.
[3] N. N. Batada, T. Reguly, A. Breitkreutz, L. Boucher, B.J. Breitkreutz, L.D. Hurst, et al., “Stratus not altocumulus: a new view of the yeast protein interaction network,” PLoS Biol. 2006, 4, p. e317.
[4] N. N. Batada, T. Reguly, A. Breitkreutz, L. Boucher, B.J. Breitkreutz, L.D. Hurst, et al., “Still stratus not altocumulus: further evidence against the date/party hub distinction,” PLoS Biol., 2007, 5, p. e154.
[5] S. Agarwal, C.M. Deane, M.A. Porter, N.S. Jones, “Revisiting date and party hubs: novel approaches to role assignment in protein interaction networks,” PLoS Comput. Biol., 6 (2010)
[6] I. W. Taylor, R. Linding, D. Warde-Farley, Y. Liu, C. Pesquita, D. Faria, et al., “Dynamic modularity in protein interaction networks predicts breast cancer outcome,” Nat Biotechnol, 2009, 27(2), pp.199-204.
[7] H. Wang and H.Zheng, “Correlation of genomics features with the date and party hub distinction: A view from three dimensional protein structures,”, in the Proc. of 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW), pp. 268 - 273
Personnel Involved
First Supervisor: Zheng, H Dr
Second Supervisor: Wang, HY Dr
Collaboration: This project does not involve collaboration with another establishment