A Graph-Based Approach for Querying Protein-Ligand Structural Patterns

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10813)


In the context of protein engineering and biotechnology, the discovery and characterization of structural patterns is very relevant as it can give fundamental insights about protein structures. In this paper we present GSP4PDB, a bioinformatics web tool that lets the users design, search and analyze protein-ligand structural patterns inside the Protein Data Bank (PDB). The novel feature of GSP4PDB is that a protein-ligand structural pattern is graphically designed as a graph such that the nodes represent protein’s components and the edges represent structural relationships. The resulting graph pattern is transformed into a SQL query, and executed in a PostgreSQL database system where the PDB data is stored. The results of the search are presented using a textual representation, and the corresponding binding-sites can be visualized using a JSmol interface.



Renzo Angles has funding from Millennium Nucleus Center for Semantic Web Research under Grant NC120004. The first version of GSP4PDB was created by Diego Cisterna, as part of his final engineering project at Universidad de Talca (Chile).


  1. 1.
    Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., Walter, P.: Molecular Biology of the Cell, 4th edn. Garland Science, New York (2002)Google Scholar
  2. 2.
    Arenas-Salinas, M., Ortega-Salazar, S., Gonzales-Nilo, F., Pohl, E., Holmes, D.S., Quatrini, R.: AFAL: a web service for profiling amino acids surrounding ligands in proteins. J. Comput. Aided Mol. Des. 28(11), 1069–1076 (2014)CrossRefGoogle Scholar
  3. 3.
    Berg, J.M., Tymoczko, J.L., Stryer, L.: Protein structure and function. In: Biochemistry, 5th edn. W. H. Freeman (2002)Google Scholar
  4. 4.
    Du, X., Li, Y., Xia, Y.L., Ai, S.M., Liang, J., Sang, P., Ji, X.L., Liu, S.Q.: Insights into protein-ligand interactions: mechanisms, models, and methods. Int. J. Mol. Sci. 17(2), 144 (2016)CrossRefGoogle Scholar
  5. 5.
    Fahrrolfes, R., Bietz, S., Flachsenberg, F., Meyder, A., Nittinger, E., Otto, T., Volkamer, A., Rarey, M.: ProteinsPlus: a web portal for structure analysis of macromolecules. Nucleic Acids Res. 45(1), 337–343 (2017)CrossRefGoogle Scholar
  6. 6.
    Iuchi, S.: Three classes of C2H2 zinc finger proteins. Cell. Mol. Life Sci. 58(4), 625–635 (2001)CrossRefGoogle Scholar
  7. 7.
    Lee, D., Redfern, O., Orengo, C.: Predicting protein function from sequence and structure. Nat. Rev. Mol. Cell Biol. 8, 995–1005 (2007)CrossRefGoogle Scholar
  8. 8.
    Meysman, P., Zhou, C., Cule, B., Goethals, B., Laukens, K.: Mining the entire Protein DataBank for frequent spatially cohesive amino acid patterns. BioData Min. 8, 4 (2015)CrossRefGoogle Scholar
  9. 9.
    Minai, R., Matsuo, Y., Onuki, H., Hirot, H.: Method for comparing the structures of protein ligand-binding sites and application for predicting protein drug interactions. Proteins 72(1), 267–381 (2008)CrossRefGoogle Scholar
  10. 10.
    Williams, M.A.: Protein-ligand interactions: fundamentals. In: Williams, M., Daviter, T. (eds.) Protein-Ligand Interactions. Methods in Molecular Biology (Methods and Protocols), vol. 1008, pp. 3–34. Humana Press, Totowa (2013). Scholar
  11. 11.
    Mavromoustakos, T., Durdagi, S., Koukoulitsa, C., Simcic, M., Papadopoulos, M.G., Hodoscek, M., Golic Grdadolnik, S.: Strategies in the rational drug design. Curr. Med. Chem. 18(17), 2517–2530 (2011)CrossRefGoogle Scholar
  12. 12.
    Wang, T., Wu, M.B., Zhang, R.H., Chen, Z.J., Hua, C., Lin, J.P., Yang, L.R.: Advances in computational structure-based drug design and application in drug discovery. Curr. Top. Med. Chem. 16(9), 901–916 (2016)CrossRefGoogle Scholar
  13. 13.
    Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., Bourne, P.E.: The protein data bank. Nucleic Acids Res. 28(1), 235–242 (2000)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversidad de TalcaTalcaChile
  2. 2.Department of BioinformaticsUniversidad de TalcaTalcaChile
  3. 3.Center for Semantic Web ResearchSantiagoChile

Personalised recommendations