Library docking for Cannabinoid-2 Receptor ligands
Rachman, M. M.; Iliopoulos-Tsoutsouvas, C.; Dominic Sacco, M.; Xu, X.; Wu, C.-G.; Santos, E.; Glenn, I. S.; Paris, L.; Cahill, M. K.; Ganapathy, S.; Tummino, T. A.; Moroz, Y. S.; Radchenko, D. S.; Okorie, M.; Tawfik, V. L.; Irwin, J. J.; Makriyannis, A.; Skiniotis, G.; Shoichet, B. K.
Show abstract
Cannabinoid receptors are therapeutically promising GPCRs that are also interesting test systems for structure-based methods, which have targeted them previously. Here we used the CB2 receptor as a template to explore several topical questions in library docking. Whereas an earlier campaign against the CB1 receptor led to potent but relatively non-selective ligands, here we found that targeting interactions with polar, orthosteric site residues led to subtype-selective ligands. Docking hit rate and especially hit affinity improved in moving from a 7 million to a 2.6 billion molecule library. Similar to earlier studies, docking against active and inactive states of the receptor did not reliably bias toward the discovery of agonists or inverse agonists. Cryo-EM structures of two of the new agonists, each in a different chemotype, superposed well on the docking predictions. Correspondingly, structure-based optimization led to 10- to 140-fold improvements within three different series, also consistent with well-behaved ligand families. Hit rates with a fully enumerated 2.6 billion molecule library resembled those of an implied 11 billion molecule library from a building-block method, consistent with the latters ability to explore this space, though higher affinities were discovered from the fully enumerated set. Overall, eight diverse families of ligands, with potencies <100 nM and mostly unrelated to previously known ligands were found. Implications for future studies are considered.
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