Recent Advances in Solving the Protein Threading Problem

Andonov, Rumen; Collet, Guillaume; Gibrat, Jean‐François; Marin, Antoine; Poirriez, Vincent; Yanev, Nicola

doi:10.1002/9780470191637.ch14

Cited by 2 publications

(3 citation statements)

References 37 publications

(71 reference statements)

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“…This study focusses on the local sequence-structure alignment problem. We propose an approach based on integer programming which expands upon our previous results [7,9]. To the best of our knowledge, no attempt has been done previously for solving this problem.…”

Section: Global Alignmentmentioning

confidence: 92%

“…The algorithm proposed by Lathrop & Smith was the first for finding the global alignment with the optimal score [5]. Since then, other methods have been developed that improved the efficiency of the global sequence-structure alignment algorithms [6,7,8,9].…”

Section: Global Alignmentmentioning

confidence: 99%

“…Thus, a global alignment between template 9gaaA and sequence 1apyB is impossible. However, with a local alignment, a part of 9gaaA can be deleted and the subdomain can be aligned with 1apyB as illustrated in figure (9).…”

Section: Local Similaritiesmentioning

confidence: 99%

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Local protein threading by Mixed Integer Programming

Collet

Andonov

Yanev

et al. 2011

Discrete Applied Mathematics

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International audienceDuring the last decade, significant progress has been made in solving the Protein Threading Problem (PTP). However, all previous approaches to PTP only perform global sequencestructure alignment. This obvious limitation is in clear contrast with the world of sequences, where local sequencesequence alignments are widely used to find functionally important regions in families of proteins. This paper presents a novel approach to PTP which allows to align a part of a protein structure onto a protein sequence in order to detect local similarities. We show experimentally that such local sequence-structure alignments improve the quality of the prediction. Our approach is based on Mixed Integer Programming (MIP) which has been shown to be very successful in this domain. We describe five MIP models for local sequence-structure alignments, compare and analyze their performances by using ILOG CPLEX 10 solver on a benchmark of proteins

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Section: Global Alignmentmentioning

confidence: 92%

Section: Global Alignmentmentioning

confidence: 99%

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Local protein threading by Mixed Integer Programming

Collet

Andonov

Yanev

et al. 2011

Discrete Applied Mathematics

Self Cite

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Statistical Significance of Threading Scores

Movaghar

Launay

Schbath

et al. 2012

Journal of Computational Biology

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We present a general method for assessing threading score significance. The threading score of a protein sequence, thread onto a given structure, should be compared with the threading score distribution of a random amino-acid sequence, of the same length, thread on the same structure; small p-values point significantly high scores. We claim that, due to general protein contact map properties, this reference distribution is a Weibull extreme value distribution whose parameters depend on the threading method, the structure, the length of the query and the random sequence simulation model used. These parameters can be estimated off-line with simulated sequence samples, for different sequence lengths. They can further be interpolated at the exact length of a query, enabling the quick computation of the p-value.

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Recent Advances in Solving the Protein Threading Problem

Cited by 2 publications

References 37 publications

Local protein threading by Mixed Integer Programming

Local protein threading by Mixed Integer Programming

Statistical Significance of Threading Scores

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