Advancing translational neuroscience research for eating disorders

Machine learning models to predict ligand binding affinity for the orexin 1 receptor

The orexin 1 receptor (OX1R) is a G-protein coupled receptor that regulates a variety of physiological processes through interactions with the neuropeptides orexin A and B. Selective OX1R antagonists exhibit therapeutic effects in preclinical models of several behavioral disorders, including drug seeking and overeating. However, currently there are no selective OX1R antagonists approved for clinical use, fueling demand for novel compounds that act at this target. In this study, we meticulously curated a dataset comprising over 1300 OX1R ligands using a stringent filter and criteria cascade. Subsequently, we developed highly predictive quantitative structure-activity relationship (QSAR) models employing the optimized hyper-parameters for the random forest machine learning algorithm and twelve 2D molecular descriptors selected by recursive feature elimination with a 5-fold cross-validation process. The predictive capacity of the QSAR model was further assessed using an external test set and enrichment study, confirming its high predictivity. The practical applicability of our final QSAR model was demonstrated through virtual screening of the DrugBank database. This revealed two FDA-approved drugs (isavuconazole and cabozantinib) as potential OX1R ligands, confirmed by radiolabeled OX1R binding assays. To our best knowledge, this study represents the first report of highly predictive QSAR models on a large comprehensive dataset of diverse OX1R ligands, which should prove useful for the discovery and design of new compounds targeting this receptor.

Recent advances in drug discovery efforts targeting the sigma 1 receptor system: Implications for novel medications designed to reduce excessive drug and food seeking

Psychiatric disorders characterized by uncontrolled reward seeking, such as substance use disorders (SUDs), alcohol use disorder (AUD) and some eating disorders, impose a significant burden on individuals and society. Despite their high prevalence and substantial morbidity and mortality rates, treatment options for these disorders remain limited. Over the past two decades, there has been a gradual accumulation of evidence pointing to the sigma-1 receptor (S1R) system as a promising target for therapeutic interventions designed to treat these disorders. S1R is a chaperone protein that resides in the endoplasmic reticulum, but under certain conditions translocates to the plasma membrane. In the brain, S1Rs are expressed in several regions important for reward, and following translocation, they physically associate with several reward-related GPCRs, including dopamine receptors 1 and 2 (D1R and D2R). Psychostimulants, alcohol, as well as palatable foods, all alter expression of S1R in regions important for motivated behavior, and S1R antagonists generally decrease behavioral responses to these rewards. Recent advances in structural modeling have permitted the development of highly-selective S1R antagonists with favorable pharmacokinetic profiles, thus providing a therapeutic avenue for S1R-based medications. Here, we provide an up-to-date overview of work linking S1R with motivated behavior for drugs of abuse and food, as well as evidence supporting the clinical utility of S1R antagonists to reduce their excessive consumption. We also highlight potential challenges associated with targeting the S1R system, including the need for a more comprehensive understanding of the underlying neurobiology and careful consideration of the pharmacological properties of S1R-based drugs.

Sleep disruption as a potential contributor to the worsening of eating disorder pathology during the COVID-19-pandemic

The acute phase of the COVID-19 pandemic was associated with significant increases in the prevalence and severity of eating disorders (EDs). Studies also highlighted changes to sleep quality and duration in many individuals throughout this period. Although these two phenomena have been examined separately, here we highlight the need to investigate the potential link between these outcomes. Sleep dysregulation and EDs have previously been hypothesized to interact via a positive feedback loop, wherein poor sleep exacerbates ED symptomatology which, in turn, further worsens sleep. Thus, we speculate that the aggravation of sleep disturbances and EDs during COVID-19 lockdowns may have been somewhat interdependent. We further hypothesize that the worsening of depression and anxiety symptomology during the acute phase of the pandemic may have served as an additional mediating variable. Altogether, in our view, these observations highlight a need for future work to examine the possible causal relationship between sleep and ED pathology, which may ultimately lead to improved clinical management of disordered eating.