Application of shape-based and pharmacophore-based in silico screens for identification of Type II protein kinase inhibitors

Daniel Mucs, Richard A. Bryce, Pascal Bonnet

    Research output: Contribution to journalArticlepeer-review


    The identification of new, potent and selective inhibitors of important protein kinase targets is a major goal of drug discovery. Here we analyze the crystal structures of 55 protein kinase complexes with Type II inhibitors and find they adopt a conserved twisted V-shape, with an angle of 121 ± 8° and twist of 78 ± 8°. The tightly conserved twist appears important in ensuring ligands curve around the protein backbone and towards the deep pocket. From this, we develop predictive pharmacophore-and shape-based screens to identify Type II inhibitors from a database which also contains Type I inhibitors as decoys. Both approaches exhibit a good level of discrimination for Type II molecules. The most effective pharmacophore model requires six features and three excluded volume regions. Shape-based screening using ROCS generally performs at least as well as pharmacophore approaches. There is only a moderate dependence of shape-based or pharmacophore-based screens on the underlying conformer generator (MOE, Macromodel, Omega and SPE), as well as on ligand linkage chemistry (amide and urea). Finally, we apply our approach to retrieval of Type II inhibitors from a modified version of the DUD database, containing over 104,000 compounds. We observe good enrichment, providing further evidence that the in silico screens developed here will constitute useful guides for identification of small molecule inhibitors targetting protein kinases in their inactive conformational state. © 2011 Springer Science+Business Media B.V.
    Original languageEnglish
    Pages (from-to)569-581
    Number of pages12
    JournalJournal of computer-aided molecular design
    Issue number6
    Publication statusPublished - Jun 2011


    • Pharmacophore
    • ROCS
    • Shape-based screening
    • Type II kinase inhibitors
    • Virtual screening


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