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Analysis of the Effects of Multiple Sequence Alignments in Protein Secondary Structure Prediction

  • Conference paper
Advances in Bioinformatics and Computational Biology (BSB 2005)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 3594))

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Abstract

Secondary structure prediction methods are widely used bioinformatics algorithms providing initial insights about protein structure from sequence information. Significant efforts to improve the prediction accuracy over the past years were made, specially the incorporation of information from multiple sequence alignments. This motivated the search for the factors contributing for this improvement. We show that in two of the highly ranked secondary structure prediction methods, DSC and PREDATOR, the use of multiple alignments consistently improves the prediction accuracy as compared to the use of single sequences. This is validated by using different measures of accuracy, which also permit to identify that helical regions benefit the most from alignments, whereas β-strands seem to have reached a plateau in terms of predictability. Also, the origins of this improvement is explored in terms of sequence specificity, secondary structure composition and the extent of sequence similarity which provides the optimal performance. It is found that divergent sequences, in the identity range of 25–55% provide the largest accuracy gain and that above 65% identity there is almost no advantage in using multiple alignments.

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Author information

Authors and Affiliations

  1. Biotechnology and Genomic Sciences program, Universidade Católica de Brasília,  

    Georgios Joannis Pappas Jr.

  2. Departments of Bioengineering, Chemistry, and Biochemistry, University of California at San Diego, La Jolla, California

    Shankar Subramaniam

Authors
  1. Georgios Joannis Pappas Jr.
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  2. Shankar Subramaniam
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Virginia Bioinformatics Institute and Virginia Polytechnic Institute and State University, Bioinformatics 1, Box 0477, 24060-0477, Blacksburg, VA, USA

    João Carlos Setubal

  2. Instituto de Quimica, Departamento de Bioquimica, Universidade de Sao Paulo, Av. Prof. Lineu Prestes 748, 05508-000, Sao Paulo, SP, Brazil

    Sergio Verjovski-Almeida

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© 2005 Springer-Verlag Berlin Heidelberg

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Pappas, G.J., Subramaniam, S. (2005). Analysis of the Effects of Multiple Sequence Alignments in Protein Secondary Structure Prediction. In: Setubal, J.C., Verjovski-Almeida, S. (eds) Advances in Bioinformatics and Computational Biology. BSB 2005. Lecture Notes in Computer Science(), vol 3594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11532323_14

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  • DOI: https://doi.org/10.1007/11532323_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28008-8

  • Online ISBN: 978-3-540-31861-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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