Accepted

Neuropathic pain, a specific type of chronic pain resulting from persistent nervous tissue lesions, is a debilitating condition that affects about 7% of the population. This condition remains particularly difficult to treat because of the poor understanding of its underlying mechanisms. Drugs currently used to alleviate this chronic pain syndrome are of limited benefit due to their lack of efficacy and the elevated risk of side effects, especially after a prolonged period of treatment. Although drugs targeting G protein-coupled receptors (GPCR) also have several limitations, such as progressive loss of efficacy due to receptor desensitization or unavoidable side effects due to wide receptor distribution, the identification of several molecular partners that contribute to the fine-tuning of receptor activity has raised new opportunities for the development of alternative therapeutic approaches. Regulators of G protein signalling (RGS) act intracellularly by influencing the coupling process and activity of G proteins, and are amongst the best-characterized physiological modulators of GPCR. Changes in RGS expression have been documented in a range of models of neuropathic pain, or after prolonged treatment with diverse analgesics, and could participate in altered pain processing as well as impaired physiological or pharmacological control of nociceptive signals. The present review summarizes the experimental data that implicates RGS in the development of pain with focus on the pathological mechanisms of neuropathic pain, including the impact of neuropathic lesions on RGS expression and, reciprocally, the influence of modifying RGS on GPCRs involved in the modulation of nociception as well as on the outcome of pain. In this context, we address the question of the relevance of RGS as promising targets in the treatment of neuropathic pain.

Opioids such as morphine-acting at the mu opioid receptor-are the mainstay for treatment of moderate to severe pain and have good efficacy in these indications. However, these drugs produce a plethora of unwanted adverse effects including respiratory depression, constipation, immune suppression and with prolonged treatment, tolerance, dependence and abuse liability. Studies in β-arrestin 2 gene knockout (βarr2(-/-)) animals indicate that morphine analgesia is potentiated while side effects are reduced, suggesting that drugs biased away from arrestin may manifest with a reduced-side-effect profile. However, there is controversy in this area with improvement of morphine-induced constipation and reduced respiratory effects in βarr2(-/-) mice. Moreover, studies performed with mice genetically engineered with G-protein-biased mu receptors suggested increased sensitivity of these animals to both analgesic actions and side effects of opioid drugs. Several new molecules have been identified as mu receptor G-protein-biased agonists, including oliceridine (TRV130), PZM21 and SR-17018. These compounds have provided preclinical data with apparent support for bias toward G proteins and the genetic premise of effective and safer analgesics. There are clinical data for oliceridine that have been very recently approved for short term intravenous use in hospitals and other controlled settings. While these data are compelling and provide a potential new pathway-based target for drug discovery, a simpler explanation for the behavior of these biased agonists revolves around differences in intrinsic activity. A highly detailed study comparing oliceridine, PZM21 and SR-17018 (among others) in a range of assays showed that these molecules behave as partial agonists. Moreover, there was a correlation between their therapeutic indices and their efficacies, but not their bias factors. If there is amplification of G-protein, but not arrestin pathways, then agonists with reduced efficacy would show high levels of activity at G-protein and low or absent activity at arrestin; offering analgesia with reduced side effects or 'apparent bias'. Overall, the current data suggests-and we support-caution in ascribing biased agonism to reduced-side-effect profiles for mu-agonist analgesics.