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Journal of Computational Biology 18, 1 (2011) 1-15
Maximum Contact Map Overlap Revisited
Rumen Andonov ( ) 1, Noël Malod-Dognin, Nicola Yanev 2
(2011-01)

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.
1:  SYMBIOSE (INRIA - IRISA)
CNRS : UMR6074 – INRIA – Institut National des Sciences Appliquées (INSA) - Rennes – Université de Rennes 1
2:  University of Sofia
Bulgarian Academy of Sciences
Computer Science/Bioinformatics

Life Sciences/Quantitative Methods

Computer Science/Operations Research
branch-and-bound – combinatorial optimization – contact map overlap – integer programming – Lagrangian relaxation – protein structure alignment