Bespoke library docking for 5-HT2A receptor agonists with antidepressant activity

Anat Levit Kaplan, Danielle N. Confair, Kuglae Kim, Ximena Barros-Álvarez, Ramona M. Rodriguiz, Ying Yang, Oh Sang Kweon, Tao Che, John D. McCorvy, David N. Kamber, James P. Phelan, Luan Carvalho Martins, Vladimir M. Pogorelov, Jeffrey F. DiBerto, Samuel T. Slocum, Xi-Ping Huang, Jain Manish Kumar, Michael J. Robertson, Ouliana Panova, Alpay B. Seven, Autumn Q. Wetsel, William C. Wetsel (), John J. Irwin (), Georgios Skiniotis (), Brian K. Shoichet (), Bryan L. Roth () and Jonathan A. Ellman ()
Additional contact information
Anat Levit Kaplan: University of California
Danielle N. Confair: Yale University
Kuglae Kim: University of North Carolina, Chapel Hill School of Medicine
Ximena Barros-Álvarez: Stanford University School of Medicine
Ramona M. Rodriguiz: Duke University Medical Center
Ying Yang: University of California
Oh Sang Kweon: Yale University
Tao Che: Washington University School of Medicine
John D. McCorvy: Medical College of Wisconsin
David N. Kamber: Yale University
James P. Phelan: Yale University
Luan Carvalho Martins: University of California
Vladimir M. Pogorelov: Duke University Medical Center
Jeffrey F. DiBerto: University of North Carolina, Chapel Hill School of Medicine
Samuel T. Slocum: University of North Carolina, Chapel Hill School of Medicine
Xi-Ping Huang: University of North Carolina Chapel Hill School of Medicine
Jain Manish Kumar: University of North Carolina, Chapel Hill School of Medicine
Michael J. Robertson: Stanford University School of Medicine
Ouliana Panova: Stanford University School of Medicine
Alpay B. Seven: Stanford University School of Medicine
Autumn Q. Wetsel: Duke University Medical Center
William C. Wetsel: Duke University Medical Center
John J. Irwin: University of California
Georgios Skiniotis: Stanford University School of Medicine
Brian K. Shoichet: University of California
Bryan L. Roth: University of North Carolina, Chapel Hill School of Medicine
Jonathan A. Ellman: Yale University

Nature, 2022, vol. 610, issue 7932, 582-591

Abstract: Abstract There is considerable interest in screening ultralarge chemical libraries for ligand discovery, both empirically and computationally1–4. Efforts have focused on readily synthesizable molecules, inevitably leaving many chemotypes unexplored. Here we investigate structure-based docking of a bespoke virtual library of tetrahydropyridines—a scaffold that is poorly sampled by a general billion-molecule virtual library but is well suited to many aminergic G-protein-coupled receptors. Using three inputs, each with diverse available derivatives, a one pot C–H alkenylation, electrocyclization and reduction provides the tetrahydropyridine core with up to six sites of derivatization5–7. Docking a virtual library of 75 million tetrahydropyridines against a model of the serotonin 5-HT2A receptor (5-HT2AR) led to the synthesis and testing of 17 initial molecules. Four of these molecules had low-micromolar activities against either the 5-HT2A or the 5-HT2B receptors. Structure-based optimization led to the 5-HT2AR agonists (R)-69 and (R)-70, with half-maximal effective concentration values of 41 nM and 110 nM, respectively, and unusual signalling kinetics that differ from psychedelic 5-HT2AR agonists. Cryo-electron microscopy structural analysis confirmed the predicted binding mode to 5-HT2AR. The favourable physical properties of these new agonists conferred high brain permeability, enabling mouse behavioural assays. Notably, neither had psychedelic activity, in contrast to classic 5-HT2AR agonists, whereas both had potent antidepressant activity in mouse models and had the same efficacy as antidepressants such as fluoxetine at as low as 1/40th of the dose. Prospects for using bespoke virtual libraries to sample pharmacologically relevant chemical space will be considered.

Date: 2022
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DOI: 10.1038/s41586-022-05258-z

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