Abstract
At present, about a quarter of all genes in most genomes contain transmembrane (TM) helices, and among the overall cellular interactome, helical membrane protein interaction is a major component. Interactions between membrane proteins play a significant role in a variety of cellular phenomena, including the transduction of signals across membranes, the transfer of membrane proteins between the plasma membrane and internal organelles, and the assembly of oligomeric protein structures. However, current experimental techniques for large-scale detection of protein-protein interactions are biased against membrane proteins. In this paper, we construct membrane protein interaction network based on gene regulatory network model. GRN model is proposed to understand the dynamic and collective control of developmental process and the characters of membrane protein interaction network, including small-world network, scale free distributing and robustness, and its significance for biology. The proposed method is proved to be effective for the study of membrane protein interaction network. The results show that the approach holds a high potential to become a useful tool in prediction of membrane protein interactions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chou, K.C., Shen, H.B.: MemType-2L: A Web server for predicting membrane proteins and their types by incorporating evolution information through Pse-PSSM. Biochemical and Biophysical Research Communications 360(2), 339–345 (2007)
Zhao, P.Y., Ding, Y.S., Chou, K.C.: Prediction of membrane protein interactions based on a fuzzy support vector machine classifier (to appear)
Ren, L.H., Ding, Y.S., Shen, Y.Z., Zhang, X.F.: Multi-agent-based bio-network for systems biology: Protein-protein interaction network as an example. Amino Acid 35(3), 565–572 (2008)
Zheng, L., Baker, M.J., Lockyer, N.P., Vickerman, J.C., Ewing, A.G., Winograd, N.: Investigating lipid-lipid and lipid-protein interactions in model membranes by ToF-SIMS. Applied Surface Science 255(4), 1190–1192 (2008)
Dario, L., Bernard, C., Stefanie, D.K.: Lipid membrane interactions of indacaterol and salmeterol: Do they influence their pharmacological properties? European Journal of Pharmaceutical Sciences 38(5), 533–547 (2009)
Toshinori, S., Haruyuki, I., Ena, O., Naoya, S., Hiroshi, U., Ryoichi, K.: Development of membrane chip system for study on membrane-protein interaction. Journal of Bioscience and Bioengineering 108(suppl. 1), S147–S164 (2009)
Peter, M.: Glycolipid transfer proteins and membrane interaction. Biochimica et Biophysica Acta 1788(1), 267–272 (2009)
Dsssow, G., Meir, E., Munro, E.M., Odell, G.M.: The segment polargity network is a robust development module. Nature 406(13), 188–192 (2000)
Dsssow, G., Meir, E., Munro, E.M., Odell, G.M.: Formulation of a model of the segment polarity network as a system of first-order ordinary differential equations using Ingeneue (2000), http://www.ingenue.org
Wang, Z.D., Lam, J., Wei, G.L., Fraser, K., Liu, X.H.: Filtering for nonlinear genetic regulatory networks with stochastic disturbances. IEEE Trans. Automatic Control 53(10), 2448–2457 (2008)
Wang, Z.D., Gao, H.J., Cao, J.D., Liu, X.H.: On delayed genetic regulatory networks with polytopic uncertainties: robust stability analysis. IEEE Trans. NanoBioscience 7(2), 154–163 (2008)
Ben-Tabou de-Leon, S., Davidson, E.H.: Modeling the dynamics of transcriptional gene regulatory networks for animal development. Developmental Biology 325(2), 317–328 (2009)
Miller, J.P., Lo, R.S., Ben-Hur, A., Desmarais, C., Stagljar, I., Noble, W.S., Fields, S.: Large-scale identification of yeast integral membrane protein interactions. Proc. Natl. Acad. Sci. 102(34), 12123–12128 (2005)
Watts, D.J.: Small Worlds. Princeton University Press, Princeton (1999)
Strogatz, S.H.: Exploring complex networks. Nature 410(6825), 268–276 (2001)
Pereira-Lea, J.B., Levy, E.D., Teichmann, S.A.: The origins and evolution of functional modules: Lessons from protein complexes. Philos. Trans. R Soc. Lond. B Biol. Sci. 361(1467), 507–517 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ding, YS., Shen, YZ., Cheng, LJ., Xu, JJ. (2010). Study on Membrane Protein Interaction Networks by Constructing Gene Regulatory Network Model. In: Li, K., Li, X., Ma, S., Irwin, G.W. (eds) Life System Modeling and Intelligent Computing. ICSEE LSMS 2010 2010. Communications in Computer and Information Science, vol 98. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15859-9_34
Download citation
DOI: https://doi.org/10.1007/978-3-642-15859-9_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15858-2
Online ISBN: 978-3-642-15859-9
eBook Packages: Computer ScienceComputer Science (R0)