Maximum Contact Map Overlap Revisited

Rumen Andonov 1, * Noël Malod-Dognin 2 Nicola Yanev 3
* Corresponding author
1 SYMBIOSE - Biological systems and models, bioinformatics and sequences
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
2 ABS - Algorithms, Biology, Structure
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Among the measures for quantifying the similarity between three-dimensional (3D) protein structures, maximum contact map overlap (CMO) received sustained attention during the past decade. Despite this, the known algorithms exhibit modest performance and are not applicable for large-scale comparison. This article offers a clear advance in this respect. We present a new integer programming model for CMO and propose an exact branch-andbound algorithm with bounds obtained by a novel Lagrangian relaxation. The efficiency of the approach is demonstrated on a popular small benchmark (Skolnick set, 40 domains). On this set, our algorithm significantly outperforms the best existing exact algorithms. Many hard CMO instances have been solved for the first time. To further assess our approach, we constructed a large-scale set of 300 protein domains. Computing the similarity measure for any of the 44850 pairs, we obtained a classification in excellent agreement with SCOP. Supplementary Material is available at www.liebertonline.com/cmb.
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https://hal.inria.fr/inria-00536624
Contributor : Rumen Andonov <>
Submitted on : Tuesday, November 16, 2010 - 3:44:16 PM
Last modification on : Friday, March 15, 2019 - 5:06:23 PM

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Rumen Andonov, Noël Malod-Dognin, Nicola Yanev. Maximum Contact Map Overlap Revisited. Journal of Computational Biology, Mary Ann Liebert, 2011, 18 (1), pp.1-15. ⟨10.1089/cmb.2009.0196⟩. ⟨inria-00536624⟩

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