Conference Paper

Protein Threading.

In proceeding of: Proceedings of the 8th Cologne-Twente Workshop on Graphs and Combinatorial Optimization, CTW 2009, Paris, France, June 2-4 2009
Source: OAI

ABSTRACT This paper describes a new algorithm that expands upon algorithms proposed in previous works to allow implementation of local sequence – structure alignments for the protein threading problem. This allows threading methods to cover the whole spectrum of alignment types needed to analyze homologous proteins.

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    ABSTRACT: We present a new local alignment method for the protein threading problem. Local sequence-sequence alignments are widely used to find functionally important regions in families of proteins. However, to the best of our knowledge, no local sequence-structure alignment algorithm has been described in the literature. Here we model local alignments as Mixed Integer Programming (MIP) models. These models permit to align a part of a protein structure onto a protein sequence in order to detect local similarities. The paper describes two MIP models, compares and analyzes their performance by using ILOG CPLEX 10 solver.
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    ABSTRACT: This paper presents a novel linear programming approach to do protein 3-dimensional (3D) structure prediction via threading. Based on the contact map graph of the protein 3D structure template, the protein threading problem is formulated as a large scale integer programming (IP) problem. The IP formulation is then relaxed to a linear programming (LP) problem, and then solved by the canonical branch-and-bound method. The final solution is globally optimal with respect to energy functions. In particular, our energy function includes pairwise interaction preferences and allowing variable gaps which are two key factors in making the protein threading problem NP-hard. A surprising result is that, most of the time, the relaxed linear programs generate integral solutions directly. Our algorithm has been implemented as a software package RAPTOR-RApid Protein Threading by Operation Research technique. Large scale benchmark test for fold recognition shows that RAPTOR significantly outperforms other programs at the fold similarity level. The CAFASP3 evaluation, a blind and public test by the protein structure prediction community, ranks RAPTOR as top 1, among individual prediction servers, in terms of the recognition capability and alignment accuracy for Fold Recognition (FR) family targets. RAPTOR also performs very well in recognizing the hard Homology Modeling (HM) targets. RAPTOR was implemented at the University of Waterloo and it can be accessed at
    Journal of Bioinformatics and Computational Biology 05/2003; 1(1):95-117.
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    ABSTRACT: The fold recognition methods,are promissing tools for capturing the structure of a protein by its amino acid residues sequence but their use is still res tricted by the needs of huge computational resources and suitable efficient algorithms as well. In the r ecent version of FROST (Fold Recogni- tion Oriented Search Tool) package the most efficient algorithm for solving the Protei n Threading Problem (PTP) is implemented,due to the strong collaboration between,the SYMBIOSE group in IRISA and MIG in Jouy-en-Josas. In this paper, we present the diverse components of FROST, em- phasizing on the recent advances in formulating and solving new versions of the PTP and on the way of solving on a computer cluster a million of instances in a reasonable time. Key-words: Protein Threading Problem, Protein Structure, Parallel Processing IRISA, Campus de Beaulieu, 35042 Rennes, France
    Grid Computing for Bioinformatics and Computational Biology, 04/2007: pages 325 - 356; , ISBN: 9780470191637

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