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Log-Linear Modelling of Protein Dipeptide Structure Reveals Interesting Patterns of Side-Chain-Backbone Interactions

Author

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  • Hommola Kerstin

    (University of Leeds)

  • Gilks Walter R.

    (University of Leeds and Rothamsted Research)

  • Mardia Kanti V.

    (University of Leeds)

Abstract

It has long been known that the amino-acid sequence of a protein determines its 3-dimensional structure, but accurate ab initio prediction of structure from sequence remains elusive. We gain insight into local protein structure conformation by studying the relationship of dihedral angles in pairs of residues in protein sequences (dipeptides). We adopt a contingency table approach, exploring a targeted set of hypotheses through log-linear modelling to detect patterns of association of these dihedral angles in all dipeptides considered. Our models indicate a substantial association of the side-chain conformation of the first residue with the backbone conformation of the second residue (side-to-back interaction) as well as a weaker but still significant association of the backbone conformation of the first residue with the side-chain conformation of the second residue (back-to-side interaction). To compare these interactions across different dipeptides, we cluster the parameter estimates for the corresponding association terms. This reveals a striking pattern. For the side-to-back term, all dipeptides which have the same first residue jointly appear in distinct clusters whereas for the back-to-side term, we observe a much weaker pattern. This suggests that the conformation of the first residue affects the conformation of the second.

Suggested Citation

  • Hommola Kerstin & Gilks Walter R. & Mardia Kanti V., 2011. "Log-Linear Modelling of Protein Dipeptide Structure Reveals Interesting Patterns of Side-Chain-Backbone Interactions," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-27, January.
    • Handle: RePEc:bpj:sagmbi:v:10:y:2011:i:1:n:8
    DOI: 10.2202/1544-6115.1579
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    References listed on IDEAS

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    1. Kanti V. Mardia & Charles C. Taylor & Ganesh K. Subramaniam, 2007. "Protein Bioinformatics and Mixtures of Bivariate von Mises Distributions for Angular Data," Biometrics, The International Biometric Society, vol. 63(2), pages 505-512, June.
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    Cited by:

    1. Fernández-Durán Juan José & Gregorio-Domínguez MarÍa Mercedes, 2014. "Modeling angles in proteins and circular genomes using multivariate angular distributions based on multiple nonnegative trigonometric sums," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(1), pages 1-18, February.

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