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Journal of Computer-Aided Molecular Design

, Volume 32, Issue 1, pp 75–87 | Cite as

Ranking docking poses by graph matching of protein–ligand interactions: lessons learned from the D3R Grand Challenge 2

  • Priscila da Silva Figueiredo Celestino Gomes
  • Franck Da Silva
  • Guillaume Bret
  • Didier RognanEmail author
Article

Abstract

A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, prior to the public release of their bound X-ray structures and potencies. In a first phase, 36 agonists were docked to 26 Protein Data Bank (PDB) structures of the FXR receptor, and next rescored using the in-house developed GRIM method. GRIM aligns protein–ligand interaction patterns of docked poses to those of available PDB templates for the target protein, and rescore poses by a graph matching method. In agreement with results obtained during the previous 2015 docking challenge, we clearly show that GRIM rescoring improves the overall quality of top-ranked poses by prioritizing interaction patterns already visited in the PDB. Importantly, this challenge enables us to refine the applicability domain of the method by better defining the conditions of its success. We notably show that rescoring apolar ligands in hydrophobic pockets leads to frequent GRIM failures. In the second phase, 102 FXR agonists were ranked by decreasing affinity according to the Gibbs free energy of the corresponding GRIM-selected poses, computed by the HYDE scoring function. Interestingly, this fast and simple rescoring scheme provided the third most accurate ranking method among 57 contributions. Although the obtained ranking is still unsuitable for hit to lead optimization, the GRIM–HYDE scoring scheme is accurate and fast enough to post-process virtual screening data.

Keywords

Docking D3R Drug discovery data resource Grand Challenge 

Notes

Acknowledgements

We thank the CAPES foundation and the Ministry of Education of Brazil for a postdoctoral fellowship to P.S.F.C.G (Computational Biology program Grant, Issue No. 51/2013). The Computing Center of the IN2P3 (CNRS, Villeurbanne, France) is acknowledged for allocation of computing time and excellent support.

Supplementary material

10822_2017_46_MOESM1_ESM.xlsx (14 kb)
Supplementary material 1 (XLSX 14 KB)
10822_2017_46_MOESM2_ESM.xlsx (12 kb)
Supplementary material 2 (XLSX 11 KB)

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Laboratoire d’Innovation ThérapeutiqueUMR 7200 CNRS-Université de StrasbourgIllkirchFrance
  2. 2.Instituto de Biofísica Carlos Chagas FilhoUniversidade Federal do Rio de JaneiroRio de JaneiroBrazil

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