Title: | A System-Wide Understanding of the Human Olfactory Percept Chemical Space |
Author(s): | Kowalewski J; Huynh B; Ray A; |
Address: | "Interdepartmental Neuroscience Program, University of California, 3401 Watkins Drive, Riverside, CA 92521, USA. Department of Molecular, Cell and Systems Biology, University of California, 3401 Watkins Drive, Riverside, CA 92521, USA" |
ISSN/ISBN: | 1464-3553 (Electronic) 0379-864X (Linking) |
Abstract: | "The fundamental units of olfactory perception are discrete 3D structures of volatile chemicals that each interact with specific subsets of a very large family of hundreds of odorant receptor proteins, in turn activating complex neural circuitry and posing a challenge to understand. We have applied computational approaches to analyze olfactory perceptual space from the perspective of odorant chemical features. We identify physicochemical features associated with ~150 different perceptual descriptors and develop machine-learning models. Validation of predictions shows a high success rate for test set chemicals within a study, as well as across studies more than 30 years apart in time. Due to the high success rates, we are able to map ~150 percepts onto a chemical space of nearly 0.5 million compounds, predicting numerous percept-structure combinations. The chemical structure-to-percept prediction provides a system-level view of human olfaction and opens the door for comprehensive computational discovery of fragrances and flavors" |
Keywords: | Humans *Machine Learning Molecular Structure *Odorants Olfactory Perception/*physiology Smell/*physiology Software Volatile Organic Compounds/*chemistry flavors fragrances machine learning olfaction prediction;Neuroscience; |
Notes: | "MedlineKowalewski, Joel Huynh, Brandon Ray, Anandasankar eng England 2021/03/01 Chem Senses. 2021 Jan 1; 46:bjab007. doi: 10.1093/chemse/bjab007" |