Library docking for Cannabinoid-2 Receptor ligands

Тип публікації :
Препринт
Дата випуску :
21 березня 2026 р.
Автор(и) :
Moira Rachman
Christos Iliopoulos-Tsoutsouvas
M. Sacco
Xinyu Xu
Cheng-Guo Wu
Emma Santos
Isabella Glenn
Lu Paris
Michelle K. Cahill
Suthakar Ganapathy
Tia A. Tummino
Yurii S Moroz
Dmytro S. Radchenko
Meri Okorie
Vivianne L. Tawfik
John J. Irwin
Alexandros Makriyannis
Georgios Skiniotis
Brian K. Shoichet
Мова основного тексту :
Англійська
eKNUTSHIR URL :
DOI :
Журнал :
bioRxiv (Cold Spring Harbor Laboratory)
Цитування :
[APA 7] Moira, R., Christos, I., M., S., Xinyu, X., Cheng-Guo, W., Emma, S., Isabella, G., Lu, P., Michelle, K. C., Suthakar, G., Tia, A. T., Yurii, S. M., Dmytro, S. R., Meri, O., Vivianne, L. T., John, J. I., Alexandros, M., Georgios, S., & Brian, K. S. (2026). Library docking for Cannabinoid-2 Receptor ligands. bioRxiv (Cold Spring Harbor Laboratory),. https://doi.org/10.64898/2026.03.19.713017
[ДСТУ] Library docking for Cannabinoid-2 Receptor ligands / R. Moira et al. bioRxiv (Cold Spring Harbor Laboratory). 2026. DOI: 10.64898/2026.03.19.713017 (date of access: 11.09.2026).
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 latter's 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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Attribution 4.0 International
Якщо не вказано інше, ця робота розповсюджується на умовах ліцензії Attribution 4.0 International