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Analysis of Interhelical Angle and Sequential Distance in Proteins

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Computational Science and Its Applications – ICCSA 2008 (ICCSA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5073))

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Abstract

This paper presents the results and discussion of statistical analysis of helix-helix interactions in proteins in terms of interhelical angle and sequential distance. The protein data includes 1290 high-resolution globular protein structures with less than 20 percent homology. We first define possible cases of interactions between helices and identify protein pairs that satisfy the conditions for each case. Two cases of helix-helix interactions are investigated using six parameters that can be obtained by considering the interactions as rigid-body motions. The computational results show that orientational preferences in helix packing are dominated by interactions between helices that are proximal in sequence. This bias is described with a univariate probability density function that depends only on the sequential distance between interacting helices. We also compute bivariate probability densities that depend on both interhelical orientation and sequential distance. The dominance of certain preferred orientations and sequential distance values in this bivariate distribution are also observed. Angle preferences persist even when the bivariate distribution is normalized by the univariate distribution. This statistical analysis provides quantitative probability distributions from which statistical potentials for secondary structure assembly can be derived.

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Osvaldo Gervasi Beniamino Murgante Antonio Laganà David Taniar Youngsong Mun Marina L. Gavrilova

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Lee, S. (2008). Analysis of Interhelical Angle and Sequential Distance in Proteins. In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2008. ICCSA 2008. Lecture Notes in Computer Science, vol 5073. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69848-7_86

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  • DOI: https://doi.org/10.1007/978-3-540-69848-7_86

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69840-1

  • Online ISBN: 978-3-540-69848-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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