Journal of Computer-Aided Molecular Design

, Volume 27, Issue 6, pp 511–524 | Cite as

Protein pocket and ligand shape comparison and its application in virtual screening

  • Matthias Wirth
  • Andrea Volkamer
  • Vincent Zoete
  • Friedrich Rippmann
  • Olivier Michielin
  • Matthias Rarey
  • Wolfgang H. B. Sauer


Understanding molecular recognition is one major requirement for drug discovery and design. Physicochemical and shape complementarity between two binding partners is the driving force during complex formation. In this study, the impact of shape within this process is analyzed. Protein binding pockets and co-crystallized ligands are represented by normalized principal moments of inertia ratios (NPRs). The corresponding descriptor space is triangular, with its corners occupied by spherical, discoid, and elongated shapes. An analysis of a selected set of sc-PDB complexes suggests that pockets and bound ligands avoid spherical shapes, which are, however, prevalent in small unoccupied pockets. Furthermore, a direct shape comparison confirms previous studies that on average only one third of a pocket is filled by its bound ligand, supplemented by a 50 % subpocket coverage. In this study, we found that shape complementary is expressed by low pairwise shape distances in NPR space, short distances between the centers-of-mass, and small deviations in the angle between the first principal ellipsoid axes. Furthermore, it is assessed how different binding pocket parameters are related to bioactivity and binding efficiency of the co-crystallized ligand. In addition, the performance of different shape and size parameters of pockets and ligands is evaluated in a virtual screening scenario performed on four representative targets.


Protein binding sites Molecular shape Shape complementarity Molecular recognition Ligand efficiency Virtual screening 



We thank Volker Hähnke and Serge Christmann-Franck for constructive discussions and Jeffrey Shaw for performing the Glide docking runs. Andrea Volkamer acknowledges funding from the BMBF (Grant 0315292A) for the pocket analysis project as part of the Biokatalyse2021 cluster. Matthias Wirth thanks Merck Serono S.A. for a PhD fellowship.

Supplementary material

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Matthias Wirth
    • 1
    • 2
  • Andrea Volkamer
    • 3
  • Vincent Zoete
    • 2
  • Friedrich Rippmann
    • 4
  • Olivier Michielin
    • 2
  • Matthias Rarey
    • 3
  • Wolfgang H. B. Sauer
    • 1
  1. 1.Computational ChemistryMerck Serono S.A. GenevaGenevaSwitzerland
  2. 2.Swiss Institute of Bioinformatics, Molecular Modelling GroupUNIL Sorge-Bâtiment GénopodeLausanneSwitzerland
  3. 3.Center for BioinformaticsUniversity of HamburgHamburgGermany
  4. 4.Global Computational ChemistryMerck KGaA, Merck SeronoDarmstadtGermany

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