Abstract
Predicting the sensory properties of compounds is challenging due to the subjective nature of the experimental measurements. This testing relies on a panel of human participants and is therefore also expensive and time-consuming. We describe the application of a state-of-the-art deep learning method, Alchemite™, to the imputation of sparse physicochemical and sensory data and compare the results with conventional quantitative structure-activity relationship methods and a multi-target graph convolutional neural network. The imputation model achieved a substantially higher accuracy of prediction, with improvements in R2 between 0.26 and 0.45 over the next best method for each sensory property. We also demonstrate that robust uncertainty estimates generated by the imputation model enable the most accurate predictions to be identified and that imputation also more accurately predicts activity cliffs, where small changes in compound structure result in large changes in sensory properties. In combination, these results demonstrate that the use of imputation, based on data from less expensive, early experiments, enables better selection of compounds for more costly studies, saving experimental time and resources.
Highlights
The olfactive system is highly evolved to translate chemical information in food and our surroundings into essential impressions of beauty, events, or even imminent danger [1, 2, 3]
The basis of smell and aroma perception in humans is an array of sensory neurons that extend into the sensory epithelium and present an array of approximately 400 unique olfactory receptors, with each sensory neuron expressing a single receptor type [5, 6, 7]
We have demonstrated that this approach gains more value from limited and noisy experimental data than quantitative structure-activity relationship (QSAR) models, to improve the accuracy of the resulting predictions [33] [34]
Summary
The olfactive system is highly evolved to translate chemical information in food and our surroundings into essential impressions of beauty, events, or even imminent danger [1, 2, 3]. The chemical information in the environment is generally sensed through the nose directly (orthonasally), whereas the impact of food aroma is sensed both orthonasally and retronasally (through the back of the throat) [4]. The science and art of perfumery and flavour seeks to accentuate and mimic key sensory experiences in our surroundings. It can evoke a sense of beauty, soothe with a sense of familiarity, reinforce authenticity, or can startle with creative novelty [10]
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