Advertisement

Representation of Protein Secondary Structure Using Bond-Orientational Order Parameters

  • Cem Meydan
  • Osman Ugur Sezerman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7632)

Abstract

Structural studies of proteins for motif mining and other pattern recognition techniques require the abstraction of the structure into simpler elements for robust matching. In this study, we propose the use of bond-orientational order parameters, a well-established metric usually employed to compare atom packing in crystals and liquids. Creating a vector of orientational order parameters of residue centers in a sliding window fashion provides us with a descriptor of local structure and connectivity around each residue that is easy to calculate and compare. To test whether this representation is feasible and applicable to protein structures, we tried to predict the secondary structure of protein segments from those descriptors, resulting in 0.99 AUC (area under the ROC curve). Clustering those descriptors to 6 clusters also yield 0.93 AUC, showing that these descriptors can be used to capture and distinguish local structural information.

Keywords

bond-orientational order secondary structure machine learning structural alphabet 

References

  1. 1.
    Joseph, A.P., Agarwal, G., Mahajan, S., Gelly, J.C., Swapna, L.S., Offmann, B., Cadet, F., Bornot, A., Tyagi, M., Valadie, H., Schneider, B., Etchebest, C., Srinivasan, N., De Brevern, A.G.: A short survey on protein blocks. Biophys. Rev. 2, 137–147 (2010)CrossRefGoogle Scholar
  2. 2.
    de Brevern, A.G., Etchebest, C., Hazout, S.: Bayesian probabilistic approach for pre-dicting backbone structures in terms of protein blocks. Proteins 41, 271–287 (2000)CrossRefGoogle Scholar
  3. 3.
    Grindley, H.M., Artymiuk, P.J., Rice, D.W., Willett, P.: Identification of tertiary structure resemblance in proteins using a maximal common subgraph isomorphism algorithm. J. Mol. Biol. 229, 707–721 (1993)CrossRefGoogle Scholar
  4. 4.
    Atilgan, A.R., Durell, S.R., Jernigan, R.L., Demirel, M.C., Keskin, O., Bahar, I.: Ani-sotropy of fluctuation dynamics of proteins with an elastic network model. Biophys J. 80, 505–515 (2001)CrossRefGoogle Scholar
  5. 5.
    Martin, J., Letellier, G., Marin, A., Taly, J.F., de Brevern, A.G., Gibrat, J.F.: Protein secondary structure assignment revisited: a detailed analysis of different assignment methods. BMC Struct. Biol. 5, 17 (2005)CrossRefGoogle Scholar
  6. 6.
    Steinhardt, P.J., Nelson, D.R., Ronchetti, M.: Bond-Orientational Order in Liquids and Glasses. Phys. Rev. B 28, 784–805 (1983)CrossRefGoogle Scholar
  7. 7.
    Offmann, B., Tyagi, M., de Brevern, A.G.: Local protein structures. Curr. Bioinform. 2, 165–202 (2007)CrossRefGoogle Scholar
  8. 8.
    Atilgan, C., Okan, O.B., Atilgan, A.R.: How orientational order governs collectivity of folded proteins. Proteins 78, 3363–3375 (2010)CrossRefGoogle Scholar
  9. 9.
    Sternberg, W.J., Smith, T.L.: The theory of potential and spherical harmonics. Univ. of Toronto Press, Toronto (1946)Google Scholar
  10. 10.
    Landau, L.D., Lifshitz, E.M.: Quantum mechanics: non-relativistic theory. Pergamon Press; sole distributors in the U.S.A., Addison-Wesley Pub. Co., Reading, Mass., Oxford, New York (1965)Google Scholar
  11. 11.
    Truskett, T.M., Torquato, S., Debenedetti, P.G.: Towards a quantification of disorder in materials: distinguishing equilibrium and glassy sphere packings. Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Topics 62, 993–1001 (2000)CrossRefGoogle Scholar
  12. 12.
    Torquato, S.: Random heterogeneous materials: microstructure and macroscopic properties. Springer, New York (2002)zbMATHGoogle Scholar
  13. 13.
    Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shind-yalov, I.N., Bourne, P.E.: The Protein Data Bank. Nucleic Acids Res. 28, 235–242 (2000)CrossRefGoogle Scholar
  14. 14.
    Murzin, A.G., Brenner, S.E., Hubbard, T., Chothia, C.: SCOP: a structural classification of proteins database for the investigation of sequences and structures. J. Mol. Biol. 247, 536–540 (1995)Google Scholar
  15. 15.
    Zhang, Y., Skolnick, J.: TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res. 33, 2302–2309 (2005)CrossRefGoogle Scholar
  16. 16.
    Frishman, D., Argos, P.: Knowledge-based protein secondary structure assignment. Proteins 23, 566–579 (1995)CrossRefGoogle Scholar
  17. 17.
    Fodje, M.N., Al-Karadaghi, S.: Occurrence, conformational features and amino acid propensities for the pi-helix. Protein Eng. 15, 353–358 (2002)CrossRefGoogle Scholar
  18. 18.
    Chang, C.-C., Lin, C.-J.: LIBSVM: a library for support vector machines (2001)Google Scholar
  19. 19.
    Demšar, J., Zupan, B., Leban, G., Curk, T.: Orange: From Experimental Machine Learning to Interactive Data Mining. In: Boulicaut, J.-F., Esposito, F., Giannotti, F., Pedreschi, D. (eds.) PKDD 2004. LNCS (LNAI), vol. 3202, pp. 537–539. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  20. 20.
    Hanley, J.A., McNeil, B.J.: A method of comparing the areas under receiver operat-ing characteristic curves derived from the same cases. Radiology 148, 839–843 (1983)Google Scholar
  21. 21.
    Koren, Y., Carmel, L.: Visualization of labeled data using linear transformations. In: In-fovis 2002: IEEE Symposium on Information Visualization 2003, Proceedings, pp. 121–128, 248 (2003)Google Scholar
  22. 22.
    Leban, G., Zupan, B., Vidmar, G., Bratko, I.: VizRank: Data visualization guided by machine learning. Data Mining and Knowledge Discovery 13, 119–136 (2006)MathSciNetCrossRefGoogle Scholar
  23. 23.
    Demsar, J., Leban, G., Zupan, B.: FreeViz–an intelligent multivariate visualization approach to explorative analysis of biomedical data. J. Biomed. Inform. 40, 661–671 (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Cem Meydan
    • 1
  • Osman Ugur Sezerman
    • 1
  1. 1.Biological Sciences & Bioengineering Dept.Sabanci UniversityIstanbulTurkey

Personalised recommendations