Development of New Analgesics: An Answer to Opioid Epidemic

Finding new analgesics: Computational pharmacology faces drug discovery challenges

Despite the worldwide prevalence and huge burden of pain, pain is an undertreated phenomenon. Currently used analgesics have several limitations regarding their efficacy and safety. The discovery of analgesics possessing a novel mechanism of action has faced multiple challenges, including a limited understanding of biological processes underpinning pain and analgesia and poor animal-to-human translation. Computational pharmacology is currently employed to face these challenges. In this review, we discuss the theory, methods, and applications of computational pharmacology in pain research. Computational pharmacology encompasses a wide variety of theoretical concepts and practical methodological approaches, with the overall aim of gaining biological insight through data acquisition and analysis. Data are acquired from patients or animal models with pain or analgesic treatment, at different levels of biological organization (molecular, cellular, physiological, and behavioral). Distinct methodological algorithms can then be used to analyze and integrate data. This helps to facilitate the identification of biological molecules and processes associated with pain phenotype, build quantitative models of pain signaling, and extract translatable features between humans and animals. However, computational pharmacology has several limitations, and its predictions can provide false positive and negative findings. Therefore, computational predictions are required to be validated experimentally before drawing solid conclusions. In this review, we discuss several case study examples of combining and integrating computational tools with experimental pain research tools to meet drug discovery challenges.

A systematic study of key elements underlying molecular property prediction

Artificial intelligence (AI) has been widely applied in drug discovery with a major task as molecular property prediction. Despite booming techniques in molecular representation learning, key elements underlying molecular property prediction remain largely unexplored, which impedes further advancements in this field. Herein, we conduct an extensive evaluation of representative models using various representations on the MoleculeNet datasets, a suite of opioids-related datasets and two additional activity datasets from the literature. To investigate the predictive power in low-data and high-data space, a series of descriptors datasets of varying sizes are also assembled to evaluate the models. In total, we have trained 62,820 models, including 50,220 models on fixed representations, 4200 models on SMILES sequences and 8400 models on molecular graphs. Based on extensive experimentation and rigorous comparison, we show that representation learning models exhibit limited performance in molecular property prediction in most datasets. Besides, multiple key elements underlying molecular property prediction can affect the evaluation results. Furthermore, we show that activity cliffs can significantly impact model prediction. Finally, we explore into potential causes why representation learning models can fail and show that dataset size is essential for representation learning models to excel.

Opioids and opioid receptors; understanding pharmacological mechanisms as a key to therapeutic advances and mitigation of the misuse crisis

Opioids are a mainstay in acute pain management and produce their effects and side effects (e.g., tolerance, opioid-use disorder and immune suppression) by interaction with opioid receptors. I will discuss opioid pharmacology in some controversial areas of enquiry of anaesthetic relevance. The main opioid target is the µ (mu,MOP) receptor but other members of the opioid receptor family, δ (delta; DOP) and κ (kappa; KOP) opioid receptors also produce analgesic actions. These are naloxone-sensitive. There is important clinical development relating to the Nociceptin/Orphanin FQ (NOP) receptor, an opioid receptor that is not naloxone-sensitive. Better understanding of the drivers for opioid effects and side effects may facilitate separation of side effects and production of safer drugs. Opioids bind to the receptor orthosteric site to produce their effects and can engage monomer or homo-, heterodimer receptors. Some ligands can drive one intracellular pathway over another. This is the basis of biased agonism (or functional selectivity). Opioid actions at the orthosteric site can be modulated allosterically and positive allosteric modulators that enhance opioid action are in development. As well as targeting ligand-receptor interaction and transduction, modulating receptor expression and hence function is also tractable. There is evidence for epigenetic associations with different types of pain and also substance misuse. As long as the opioid narrative is defined by the 'opioid crisis' the drive to remove them could gather pace. This will deny use where they are effective, and access to morphine for pain relief in low income countries.

Alternative pain management via endocannabinoids in the time of the opioid epidemic: Peripheral neuromodulation and pharmacological interventions

The use of opioids in pain management is hampered by the emergence of analgesic tolerance, which leads to increased dosing and side effects, both of which have contributed to the opioid epidemic. One promising potential approach to limit opioid analgesic tolerance is activating the endocannabinoid system in the CNS, via activation of CB1 receptors in the descending pain inhibitory pathway. In this review, we first discuss preclinical and clinical evidence revealing the potential of pharmacological activation of CB1 receptors in modulating opioid tolerance, including activation by phytocannabinoids, synthetic CB1 receptor agonists, endocannabinoid degradation enzyme inhibitors, and recently discovered positive allosteric modulators of CB1 receptors. On the other hand, as non-pharmacological pain relief is advocated by the US-NIH to combat the opioid epidemic, we also discuss contributions of peripheral neuromodulation, involving the electrostimulation of peripheral nerves, in addressing chronic pain and opioid tolerance. The involvement of supraspinal endocannabinoid systems in peripheral neuromodulation-induced analgesia is also discussed. LINKED ARTICLES: This article is part of a themed issue on Advances in Opioid Pharmacology at the Time of the Opioid Epidemic. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v180.7/issuetoc.

Association between NMDAR antagonists, drug abuse and dependence: A disproportionality analysis from the WHO pharmacovigilance database

Ketamine and dextromethorphan are widely abused psychoactive substances. Inhibition of N-methyl-d-aspartate receptors (NMDARs) results in neurobehavioural effects including hallucinations, "out of body" sensations and dissociative effects. However, little is known about a possible extended addictive class effect linked to pharmacologically-related amino-adamantane derivatives (e.g., amantadine and memantine). Using a quasi-Bayesian analytic method, we investigated the potential association between the use of approved NMDAR antagonists (i.e., dextromethorphan, ketamine, amantadine and memantine) and the reporting of drug abuse and dependence in the WHO pharmacovigilance database (VigiBase®), which includes >21 million individual case safety reports collected from >130 countries. This disproportionality analysis identified a significant association for all investigated drugs: dextromethorphan (IC = 3.03 [2.97-3.09]), ketamine (IC = 1.70 [1.57-1.83]), amantadine (IC = 0.21 [0.06-0.35]) and memantine (IC = 0.27 [0.13-0.40]), suggesting a class effect for drug abuse and dependence. This first signal requires further investigations, but health professionals need to be alert to the potential of abuse of NMDAR antagonists, especially in the current "opioid epidemic" context, due to their growing interest as non-opioid antinociceptive drugs.

Activation of GPR183 by 7α,25-Dihydroxycholesterol Induces Behavioral Hypersensitivity through Mitogen-Activated Protein Kinase and Nuclear Factor-κB

Emerging evidence implicates the G-protein coupled receptor (GPCR) GPR183 in the development of neuropathic pain. Further investigation of the signaling pathways downstream of GPR183 is needed to support the development of GPR183 antagonists as analgesics. In rodents, intrathecal injection of its ligand, 7α,25-dihydroxycholesterol (7α,25-OHC), causes time-dependent development of mechano-and cold- allodynia (behavioral hypersensitivity). These effects are blocked by the selective small molecule GPR183 antagonist, SAE-14. However, the molecular mechanisms engaged downstream of GPR183 in the spinal cord are not known. Here, we show that 7α,25-OHC-induced behavioral hypersensitivity is Gα i dependent, but not β-arrestin 2-dependent. Non-biased transcriptomic analyses of dorsal-horn spinal cord (DH-SC) tissues harvested at the time of peak hypersensitivity implicate potential contributions of mitogen-activated protein kinase (MAPK) and nuclear factor κB (NF-κB). In support, we found that the development of 7α,25-OHC/GPR183-induced mechano-allodynia was associated with significant activation of MAPKs (extracellular signal-regulated kinase [ERK], p38) and redox-sensitive transcription factors (NF-κB) and increased formation of inflammatory and neuroexcitatory cytokines. SAE-14 blocked these effects and behavioral hypersensitivity. Our findings provide novel mechanistic insight into how GPR183 signaling in the spinal cord produces hypersensitivity through MAPK and NF-κB activation. SIGNIFICANCE STATEMENT: Using a multi-disciplinary approach, we have characterized the molecular mechanisms underpinning 7α,25-OHC/GPR183-induced hypersensitivity in mice. Intrathecal injections of the GPR183 agonist 7α,25-OHC induce behavioral hypersensitivity, and these effects are blocked by the selective GPR183 antagonist SAE-14. We found that 7α,25-OHC-induced allodynia is dependent on MAPK and NF-κB signaling pathways and results in an increase in pro-inflammatory cytokine expression. This study provides a first insight into how GPR183 signaling in the spinal cord is pronociceptive.

Sexual Dimorphism in the Expression of Pain Phenotype in Preclinical Models of Rheumatoid Arthritis

Rheumatoid arthritis is one of most frequent rheumatic diseases, affecting around 1% of the population worldwide. Pain impacting the quality of life for the patient with rheumatoid arthritis, is often the primary factor leading them to seek medical care. Although sex-related differences in humans and animal models of rheumatoid arthritis are described, the correlation between pain and sex in rheumatoid arthritis has only recently been directly examined. Here we review the literature and explore the mechanisms underlying the expression of the pain phenotype in females and males in preclinical models of rheumatoid arthritis.

A new hypertonic saline assay for analgesic screening in mice: effects of animal strain, sex, and diurnal phase

PURPOSE

There exists a pressing need for the identification of novel analgesics. We recently reported on a new preclinical assay for rapid analgesic screening based on intraplantar (i.pl.) injection of 10% hypertonic saline (HS) in female outbred (CD-1) mice. Herein, we characterized the HS assay's performance in inbred (C57BL/6) mice, sensitivity to sex differences, and effects of diurnal rhythm phase.

METHODS

In randomized, controlled, blinded in vivo animal experiments, we studied nociceptive responses induced by i.pl. HS in C57BL/6 (vs CD-1) mice of both sexes (n = 240) and determined diurnal rhythm phase effects in female animals. We established the HS assay's sensitivity to morphine by constructing dose-response curves and calculating half-maximal inhibitory doses (ID₅₀s).

RESULTS

The injection of i.pl. HS produced nociceptive (licking and biting) responses in all C57BL/6 mice tested. In both C57BL/6 and CD-1 mice, the mean (95% confidence interval [CI]) response magnitudes were greater in females vs males (C57BL/6: 87 sec [64 to 110] vs 45 sec [29 to 61]; difference in means, 42 sec; 95% CI, 17 to 68; P < 0.001; n = 10/group; CD-1: 110 sec [95 to 126] vs 53 sec [32 to 74]; difference in means, 57 sec; 95% CI, 34 to 79; P < 0.001; n = 10/group). The mean (95% CI) nociceptive responses were greater at 24:00 hr than at 12:00 hr in C57BL/6 mice (64 sec [40 to 88] vs 37 sec [24 to 51]; difference in means, 27 sec; 95% CI, 7 to 47; P = 0.007; n = 10/group), but not in CD-1 mice (P = 0.97). Intravenous morphine dose-dependently attenuated nociceptive responses of both C57BL/6 and CD-1 mice (ID₅₀, 0.6 and 2.5 mg·kg^-1, respectively; P = 0.41).

CONCLUSION

These findings in inbred and outbred mice solidify the utility of the HS assay as an effective, rapid, robust, and versatile preclinical tool for analgesic screening.

Soluble epoxide hydrolase inhibitor mediated analgesia lacks tolerance in rat models

Effectively treating chronic pain remains a therapeutic challenge in the clinic. Recent evidence has shown the inhibition of the soluble epoxide hydrolase (sEH) to be an effective strategy to limit chronic pain in preclinical models, horses and companion animals. Determining the safety of sEH inhibition in addition to this demonstrated efficacy is a critical step to the further development of sEH inhibitors (sEHI) as analgesics. Here we describe a comparison of the sEHI TPPU with other first in class analgesics for human chronic pain. We assess the development of tolerance to the analgesia mediated by TPPU with extended use. We also assess for CNS effects by measuring changes in motor control and functioning. The sEHI are multimodal analgesics that have demonstrated potent efficacy against chronic pain. They have previously been tested and show no reward potential using operant methods. The results of the current experiments show that they lack motor function effects and also lack the development of tolerance with extended dosing.