An Efficient Lagrangian Relaxation for the Contact Map Overlap Problem

  • Rumen Andonov
  • Nicola Yanev
  • Noël Malod-Dognin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5251)


Among the measures for quantifying the similarity between protein 3-D structures, contact map overlap (CMO) maximization deserved sustained attention during past decade. Despite this large involvement, the known algorithms possess a modest performance and are not applicable for large scale comparison.

This paper offers a clear advance in this respect. We present a new integer programming model for CMO and propose an exact B&B 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 assess furthermore our approach, we constructed a large scale set of 300 protein domains. Computing the similarity measure for any of the 44850 couples, we obtained a classification in excellent agreement with SCOP.


Protein structure alignment contact map overlap combinatorial optimization integer programming branch and bound Lagrangian relaxation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Rumen Andonov
    • 1
  • Nicola Yanev
    • 2
  • Noël Malod-Dognin
    • 1
  1. 1.INRIA Rennes - Bretagne Atlantique and University of Rennes 1 
  2. 2.University of SofiaBulgaria

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