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A Hybrid Method for the Protein Structure Prediction Problem

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Advances in Bioinformatics and Computational Biology (BSB 2008)

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Abstract

This article provides the initial results of our effort to develop a hybrid prediction method, combining the principles of de novo and homology modeling, to help solve the protein three-dimensional (3-D) structure prediction problem. A target protein amino acid sequence is fragmented into many short contiguous fragments. Clustered short templates fragments, obtained from experimental protein structures in the Protein Data Bank (PDB), using the NCBI BLASTp program, were used for building an initial conformation, which was further refined by molecular dynamics simulations. We tested our method with the artificially designed alpha helical hairpin (PDB ID: 1ZDD) starting with its amino acids sequence only. The structure obtained with the proposed method is topologically a helical hairpin, with a C( RMSD of ~ 5.0 Å with respect to the experimental PDB structure for all 34 amino acids residues, and only ~ 2.0 Å when considering amino acids 1 to 22. We discuss further improvements to the method.

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Ana L. C. Bazzan Mark Craven Natália F. Martins

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Dorn, M., Breda, A., Norberto de Souza, O. (2008). A Hybrid Method for the Protein Structure Prediction Problem. In: Bazzan, A.L.C., Craven, M., Martins, N.F. (eds) Advances in Bioinformatics and Computational Biology. BSB 2008. Lecture Notes in Computer Science(), vol 5167. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85557-6_5

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  • DOI: https://doi.org/10.1007/978-3-540-85557-6_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85556-9

  • Online ISBN: 978-3-540-85557-6

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