Back

Deletion of arrestin-3 does not alter compulsive morphine-seeking behavior in an oral operant self-administration paradigm

Felth, L.; Gooding, S.; Foxall, R.; Rosa, Z.; Ireton, K.; Sall, I. J.; Gipoor, J.; Gaur, A.; King, M.; Dirks, N.; Whistler, C. A.; Whistler, J. A.

2023-04-03 animal behavior and cognition
10.1101/2023.03.30.534994 bioRxiv
Show abstract

Opioid drugs are potent analgesics that mimic the endogenous opioid peptides, endorphins and enkephalins, by activating the {micro}-opioid receptor. Opioid use is limited by side effects, including significant risk of opioid use disorder. Improvement of the effect/side effect profile of opioid medications is a key pursuit of opioid research, yet there is no consensus on how to achieve this goal. One hypothesis is that the degree of arrestin-3 recruitment to the {micro}-opioid receptor impacts therapeutic utility. However, it is not clear whether increased or decreased interaction of the {micro}-opioid receptor with arrestin-3 would reduce compulsive drug-seeking. To examine this question, we utilized three genotypes of mice with varying abilities to recruit arrestin-3 to the {micro}-opioid receptor in response to morphine in a novel longitudinal operant self-administration model. We demonstrate that arrestin-3 knockout and wild type mice have highly variable drug-seeking behavior with few genotype differences. In contrast, in mice where the {micro}-opioid receptor strongly recruits arrestin-3, drug-seeking behavior is much less varied. We created a quantitative method to define compulsivity in drug-seeking and found that mice lacking arrestin-3 were more likely to meet the criteria for compulsivity whereas mice with enhanced arrestin-3 recruitment did not develop a compulsive phenotype. Our data suggest that opioids that engage both G protein and arrestin-3, recapitulating the endogenous signaling pattern, will reduce abuse liability.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.