CONS-COCOMAPS: A novel tool to measure and visualize the conservation of inter-residue contacts in multiple docking solutions

Anna Vangone, Romina Oliva*, Luigi Cavallo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


Background: The development of accurate protein-protein docking programs is making this kind of simulations an effective tool to predict the 3D structure and the surface of interaction between the molecular partners in macromolecular complexes. However, correctly scoring multiple docking solutions is still an open problem. As a consequence, the accurate and tedious screening of many docking models is usually required in the analysis step.Methods: All the programs under CONS-COCOMAPS have been written in python, taking advantage of python libraries such as SciPy and Matplotlib. CONS-COCOMAPS is freely available as a web tool at the URL:. Here we presented CONS-COCOMAPS, a novel tool to easily measure and visualize the consensus in multiple docking solutions. CONS-COCOMAPS uses the conservation of inter-residue contacts as an estimate of the similarity between different docking solutions. To visualize the conservation, CONS-COCOMAPS uses intermolecular contact maps.Conclusions: The application of CONS-COCOMAPS to test-cases taken from recent CAPRI rounds has shown that it is very efficient in highlighting even a very weak consensus that often is biologically meaningful.

Original languageEnglish (US)
Article numberS19
JournalBMC Bioinformatics
Issue numberSUPPL.4
StatePublished - Mar 28 2012

Bibliographical note

Funding Information:
Funding RO has been supported by the Italian MIUR (Ministero dell’Istruzione, dell’Università e della Ricerca; Grant PRIN2008). This article has been published as part of BMC Bioinformatics Volume 13 Supplement 4, 2012: Italian Society of Bioinformatics (BITS): Annual Meeting 2011. The full contents of the supplement are available online at http://

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics


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