scholarly journals Comparison of an Addictive Potential of μ-Opioid Receptor Agonists with G Protein Bias: Behavioral and Molecular Modeling Studies

Pharmaceutics ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 55
Author(s):  
Lucja Kudla ◽  
Ryszard Bugno ◽  
Sabina Podlewska ◽  
Lukasz Szumiec ◽  
Lucja Wiktorowska ◽  
...  

Among different approaches to the search for novel—safer and less addictive—opioid analgesics, biased agonism has received the most attention in recent years. Some μ-opioid receptor agonists with G protein bias, including SR compounds, were proposed to induce diminished side effects. However, in many aspects, behavioral effects of those compounds, as well as the mechanisms underlying differences in their action, remain unexplored. Here, we aimed to evaluate the effects of SR-14968 and SR-17018, highly G protein-biased opioid agonists, on antinociception, motor activity and addiction-like behaviors in C57BL/6J mice. The obtained results showed that the compounds induce strong and dose-dependent antinociception. SR-14968 causes high, and SR-17018 much lower, locomotor activity. Both agonists develop reward-associated behavior and physical dependence. The compounds also cause antinociceptive tolerance, however, developing more slowly when compared to morphine. Interestingly, SR compounds, in particular SR-17018, slow down the development of antinociceptive tolerance to morphine and inhibit some symptoms of morphine withdrawal. Therefore, our results indicate that SR agonists possess rewarding and addictive properties, but can positively modulate some symptoms of morphine dependence. Next, we have compared behavioral effects of SR-compounds and PZM21 and searched for a relationship to the substantial differences in molecular interactions that these compounds form with the µ-opioid receptor.

1999 ◽  
Vol 126 (2) ◽  
pp. 451-456 ◽  
Author(s):  
Minoru Narita ◽  
Hirokazu Mizoguchi ◽  
Michiko Narita ◽  
Ichiro Sora ◽  
George R Uhl ◽  
...  

2020 ◽  
Vol 166 ◽  
pp. 107718 ◽  
Author(s):  
Mie Fabricius Pedersen ◽  
Tomasz Marcin Wróbel ◽  
Emil Märcher-Rørsted ◽  
Daniel Sejer Pedersen ◽  
Thor Christian Møller ◽  
...  

Author(s):  
Lucja Kudla ◽  
Ryszard Przewlocki

AbstractOpioid analgesics remain a gold standard for the treatment of moderate to severe pain. However, their clinical utility is seriously limited by a range of adverse effects. Among them, their high-addictive potential appears as very important, especially in the context of the opioid epidemic. Therefore, the development of safer opioid analgesics with low abuse potential appears as a challenging problem for opioid research. Among the last few decades, different approaches to the discovery of novel opioid drugs have been assessed. One of the most promising is the development of G protein-biased opioid agonists, which can activate only selected intracellular signaling pathways. To date, discoveries of several biased agonists acting via μ-opioid receptor were reported. According to the experimental data, such ligands may be devoid of at least some of the opioid side effects, such as respiratory depression or constipation. Nevertheless, most data regarding the addictive properties of biased μ-opioid receptor agonists are inconsistent. A global problem connected with opioid abuse also requires the search for effective pharmacotherapy for opioid addiction, which is another potential application of biased compounds. This review discusses the state-of-the-art on addictive properties of G protein-biased μ-opioid receptor agonists as well as we analyze whether these compounds can diminish any symptoms of opioid addiction. Finally, we provide a critical view on recent data connected with biased signaling and its implications to in vivo manifestations of addiction. Graphic abstract


2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Jeremy C. Cornelissen ◽  
Bruce E. Blough ◽  
Laura M. Bohn ◽  
S. Stevens Negus ◽  
Matthew L. Banks

2007 ◽  
Vol 15 (3) ◽  
pp. 1237-1251 ◽  
Author(s):  
Tingyou Li ◽  
Yunden Jinsmaa ◽  
Masahiro Nedachi ◽  
Anna Miyazaki ◽  
Yuko Tsuda ◽  
...  

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