Discovery of N -substituted- endo -3-(8-aza-bicyclo[3.2.1]oct-3-yl)-phenol and -phenyl carboxamide series of μ-opioid receptor antagonists

Searching for Synthetic Opioid Rescue Agents: Identification of a Potent Opioid Agonist with Reduced Respiratory Depression

While in the process of designing more effective synthetic opioid rescue agents, we serendipitously identified a new chemotype of potent synthetic opioid. Here, we report that conformational constraint of a piperazine ring converts a mu opioid receptor (MOR) antagonist into a potent MOR agonist. The prototype of the series, which we have termed atoxifent (2), possesses potent in vitro agonist activity. In mice, atoxifent displayed long-lasting antinociception that was reversible with naltrexone. Repeated dosing of atoxifent produced antinociceptive tolerance and a level of withdrawal like that of fentanyl. In rats, while atoxifent produced complete loss of locomotor activity like fentanyl, it failed to produce deep respiratory depression associated with fentanyl-induced lethality. Assessment of brain biodistribution demonstrated ample distribution of atoxifent into the brain with a Tmax of approximately 0.25 h. These results indicate enhanced safety for atoxifent-like molecules compared to fentanyl.

ProfhEX: AI-based platform for small molecules liability profiling

Off-target drug interactions are a major reason for candidate failure in the drug discovery process. Anticipating potential drug's adverse effects in the early stages is necessary to minimize health risks to patients, animal testing, and economical costs. With the constantly increasing size of virtual screening libraries, AI-driven methods can be exploited as first-tier screening tools to provide liability estimation for drug candidates. In this work we present ProfhEX, an AI-driven suite of 46 OECD-compliant machine learning models that can profile small molecules on 7 relevant liability groups: cardiovascular, central nervous system, gastrointestinal, endocrine, renal, pulmonary and immune system toxicities. Experimental affinity data was collected from public and commercial data sources. The entire chemical space comprised 289'202 activity data for a total of 210'116 unique compounds, spanning over 46 targets with dataset sizes ranging from 819 to 18896. Gradient boosting and random forest algorithms were initially employed and ensembled for the selection of a champion model. Models were validated according to the OECD principles, including robust internal (cross validation, bootstrap, y-scrambling) and external validation. Champion models achieved an average Pearson correlation coefficient of 0.84 (SD of 0.05), an R² determination coefficient of 0.68 (SD = 0.1) and a root mean squared error of 0.69 (SD of 0.08). All liability groups showed good hit-detection power with an average enrichment factor at 5% of 13.1 (SD of 4.5) and AUC of 0.92 (SD of 0.05). Benchmarking against already existing tools demonstrated the predictive power of ProfhEX models for large-scale liability profiling. This platform will be further expanded with the inclusion of new targets and through complementary modelling approaches, such as structure and pharmacophore-based models. ProfhEX is freely accessible at the following address: https://profhex.exscalate.eu/ .

Endogenous opiates and behavior: 2017

This paper is the fortieth consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2017 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

Discovery of Axelopran (TD-1211): A Peripherally Restricted μ-Opioid Receptor Antagonist

The effects of opioids in the central nervous system (CNS) provide significant benefit in the treatment of pain but can also lead to physical dependence and addiction, which has contributed to a growing opioid epidemic in the United States. Gastrointestinal dysfunction is an additional serious consequence of opioid use, and this can be treated with a localized drug distribution of a non-CNS penetrant, peripherally restricted opioid receptor antagonist. Herein, we describe the application of Theravance's multivalent approach to drug discovery coupled with a physicochemical property design strategy by which the N-substituted-endo-3-(8-aza-bicyclo[3.2.1]oct-3-yl)-phenyl carboxamide series of μ-opioid receptor antagonists was optimized to afford the orally absorbed, non-CNS penetrant, Phase 3 ready clinical compound axelopran (TD-1211) 19i as a potential treatment for opioid-induced constipation.

Selective synthesis of N-protected exo-spiro[oxirane-3,2′-tropanes]

N-Cbz- and N-Boc-protected exo-spiro[oxirane-3,2′-tropanes] were selectively synthesized via either epoxidation or hydroxybromination/dehydrobromination of the corresponding alkenes.