Abstract
Protein binding sites are regions where interactions between a protein and ligand take place. Identification of binding sites is a functional issue especially in structure-based drug design. This paper aims to present a novel feature of protein binding pockets based on the complexity of corresponding weighted Delaunay triangulation. The results demonstrate that candidate binding pockets obtain less relative Von Neumann entropy which means more random scattering of voids inside them.
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
Seco, J., Luque, J., Barril, X.: Binding Site Detection and Druggability Index from First Principles. Journal of Medicinal Chemistry 52, 2363–2371 (2009)
Pérot, S., Sperandio, O., Miteva, M.A., Camproux, A., Villoutreix, B.O.: Druggable pockets and binding site centric chemical space: a paradigm shift in drug discovery. Drug Discovery Today 15, 656–667 (2010)
Hendlich, M., Rippmann, F., Barnickel, G.: LIGSITE: Automatic and efficient detection of potential small molecule-binding sites in proteins. J. Mol. Graph. Model. 15, 359–363 (1997)
Huang, B., Schroeder, M.: LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation. BMC Structural Biology 6, 19–29 (2006)
Weisel, M., Proschak, E., Schneider, G.: PocketPicker: analysis of ligand binding-sites with shape descriptors. Chemistry Central Journal 1 (2007)
Laskowsk, R.A.: SURFNET: a program for visualizing molecular surfaces, cavities, and intermolecular interactions. J. Mol. Graph. 13, 323–330, 307–308 (1995)
Brady, G.P., Stouten, P.F.: Fast prediction and visualization of protein binding pockets with PASS. J. Comput. Aided Mol. Des. 14, 383–401 (2000)
Edelsbrunner, H., Facello, M., Liang, J.: On the definition and the construction of pockets in macromolecules. Descrete Applied Mathematics 88, 83–102 (1998)
Le Guilloux, V., Schmidtke, P., Tuffery, P.: Fpocket: an open source platform for ligand pocket detection. BMC Bioinformatics 10 (2009)
Haung, B.: MetaPocket: a meta approach to improve protein ligand binding site prediction. OMICS 13, 325–330 (2009)
Zhang, Z., Li, Y., Lin, B., Schroeder, M., Huang, B.: Identification of cavities on protein surface using multiple computational approaches for drug binding site prediction. Bioinformatics 27, 2083–2088 (2011)
Laskowski, R.A., Luscombe, N.M., Swindless, M.B., Thornton, J.M.: Protein clefts in molecular recognition and function. Protein Science 5, 2438–2452 (1996)
Gao, J., Liu, Q., Kang, H., Cao, Z., Zhu, R.: Comparison of Different Ranking Methods in Protein-Ligand Binding Site Prediction. International Journal of Molecular Science 13, 8752–8761 (2012)
Dundas, J., Ouyang, Z., Tseng, J., Binkowski, A., Turpaz, Y., Liang, J.: CASTp: computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues. Nucleic Acids Res. 34, W116–W118 (2006)
Dehmer, M., Barbarini, N., Varmuza, K., Graber, A.: A large scale analysis of information-theoretic network complexity measures using chemical structures. PLoS One 4, e8057 (2009)
Dehmer, M., Mowshowitz, A.: A history of graph entropy measures. Information Science 181, 57–78 (2011)
Passerini, F., Severini, S.: Quantifying complexity in networks: The Von Neumann entropy. IJATS 4, 58–67 (2009)
Du, W., Li, X., Li, Y., Severini, S.: A note on the von Neumann entropy of random graphs. Linear Algebra and its Application (2010)
Dai, T., Liu, Q., Gao, J., Cao, Z., Zhu, R.: A new protein-ligand binding sites prediction method based on the integration of protein sequence conservation information. BMC Bioinformatics 12(suppl. 14), S9 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Forouzesh, N., Kazemi, M.R., Mohades, A. (2014). Structure-Based Analysis of Protein Binding Pockets Using Von Neumann Entropy. In: Basu, M., Pan, Y., Wang, J. (eds) Bioinformatics Research and Applications. ISBRA 2014. Lecture Notes in Computer Science(), vol 8492. Springer, Cham. https://doi.org/10.1007/978-3-319-08171-7_27
Download citation
DOI: https://doi.org/10.1007/978-3-319-08171-7_27
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08170-0
Online ISBN: 978-3-319-08171-7
eBook Packages: Computer ScienceComputer Science (R0)