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Oxford University Press, Bioinformatics, 24(32), p. 3760-3767, 2016

DOI: 10.1093/bioinformatics/btw533

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PPI4DOCK: Large scale assessment of the use of homology models in free docking over more than 1000 realistic targets.

Journal article published in 2016 by Jinchao Yu ORCID, Raphaël Guerois
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Motivation: Protein–protein docking methods are of great importance for understanding interactomes at the structural level. It has become increasingly appealing to use not only experimental structures but also homology models of unbound subunits as input for docking simulations. So far we are missing a large scale assessment of the success of rigid-body free docking methods on homology models. Results: We explored how we could benefit from comparative modelling of unbound subunits to expand docking benchmark datasets. Starting from a collection of 3157 non-redundant, high X-ray resolution heterodimers, we developed the PPI4DOCK benchmark containing 1417 docking targets based on unbound homology models. Rigid-body docking by Zdock showed that for 1208 cases (85.2%), at least one correct decoy was generated, emphasizing the efficiency of rigid-body docking in generating correct assemblies. Overall, the PPI4DOCK benchmark contains a large set of realistic cases and provides new ground for assessing docking and scoring methodologies. Availability and Implementation: Benchmark sets can be downloaded from http://biodev.cea.fr/interevol/ppi4dock/ Contact: guerois@cea.fr Supplementary information: Supplementary data are available at Bioinformatics online.