Agonists of G-Protein-Coupled Odorant Receptors Are Predicted from Chemical Features.

Predicting the activity of chemicals for a given odorant receptor is a longstanding challenge. Here the activity of 258 chemicals on the human G-protein-coupled odorant receptor (OR)51E1, also known as prostate-specific G-protein-coupled receptor 2 (PSGR2), was virtually screened by machine learning using 4884 chemical descriptors as input. A systematic control by functional in vitro assays revealed that a support vector machine algorithm accurately predicted the activity of a screened library. It allowed us to identify two novel agonists in vitro for OR51E1. The transferability of the protocol was assessed on OR1A1, OR2W1, and MOR256-3 odorant receptors, and, in each case, novel agonists were identified with a hit rate of 39-50%. We further show how ligands' efficacy is encoded into residues within OR51E1 cavity using a molecular modeling protocol. Our approach allows widening the chemical spaces associated with odorant receptors. This machine-learning protocol based on chemical features thus represents an efficient tool for screening ligands for G-protein-coupled odorant receptors that modulate non-olfactory functions or, upon combinatorial activation, give rise to our sense of smell.

Olfactory disturbances in ageing with and without dementia: towards new diagnostic tools.

BACKGROUND: Olfactory disorders increase with age and often affect elderly people who have pre-dementia or dementia. Despite the frequent occurrence of olfactory changes at the early stages of neurodegenerative disorders such as Alzheimer's disease, olfactory disorders are rarely assessed in daily clinical practice, mainly due to a lack of standardised assessment tools. The aims of this review were to (1) summarise the existing literature on olfactory disorders in ageing populations and patients with neurodegenerative disorders; (2) present the strengths and weaknesses of current olfactory disorder assessment tools; and (3) discuss the benefits of developing specific olfactory tests for neurodegenerative diseases. METHODS: A systematic review was performed of literature published between 2000 and 2015 addressing olfactory disorders in elderly people with or without Alzheimer's disease or other related disorders to identify the main tools currently used for olfactory disorder assessment. RESULTS: Olfactory disorder assessment is a promising method for improving both the early and differential diagnosis of Alzheimer's disease. However, the current lack of consensus on which tests should be used does not permit the consistent integration of olfactory disorder assessment into clinical settings. CONCLUSION: Otolaryngologists are encouraged to use olfactory tests in older adults to help predict the development of neurodegenerative diseases. Olfactory tests should be specifically adapted to assess olfactory disorders in Alzheimer's disease patients.