Predicting human olfactory perception by odorant structure and receptor activation profile

气味 药效团 结构相似性 相似性(几何) 丁香酚 化学 香兰素 感知 嗅觉 分子描述符 嗅觉系统 生物系统 模式识别(心理学) 计算生物学 人工智能 数量结构-活动关系 心理学 生物 立体化学 神经科学 生物化学 计算机科学 图像(数学) 有机化学
作者
Yusuke Ihara,Chiori Ijichi,Yasuko Nogi,Masayuki Sugiki,Yuko Kodama,Sayoko Ihara,Mika Shirasu,Takatsugu Hirokawa,Kazushige Touhara
出处
期刊:Chemical Senses [Oxford University Press]
标识
DOI:10.1093/chemse/bjaf002
摘要

Abstract Humans possess a remarkable ability to discriminate a wide range of odors with high precision. This process begins with olfactory receptors (ORs) detecting and responding to the molecular structures of odorants. Recent studies have aimed to associate the activity of a single OR to an odor descriptor or predict odor descriptors using 2D molecular representation. However, predicting a limited number of odor descriptors is insufficient to fully understand the widespread and elaborate olfactory perception process. Therefore, we conducted structure-activity relationship analyses for ORs of eugenol, vanillin, and structurally similar compounds, investigating the correlation between molecular structures, OR activity profiles, and perceptual odor similarity. Our results indicated that these structurally similar compounds primarily activated six ORs, and the activity profiles of these ORs correlated with their perception. This enabled the development of a prediction model for the eugenol-similarity score from OR activity profiles (coefficient of determination, R2 = 0.687). Furthermore, the molecular structures of odorants were represented as 3D shapes and pharmacophore fingerprints, considering the 3D structural similarities between various odorants with multiple conformations. These 3D shape and pharmacophore fingerprints could also predict the perceptual odor similarity (R2 = 0.514). Finally, we identified key molecular structural features that contributed to predicting sensory similarities between compounds structurally similar to eugenol and vanillin. Our models, which predict odor from OR activity profiles and similarities in the 3D structure of odorants, may aid in understanding olfactory perception by compressing the information from a vast number of odorants into the activity profiles of 400 ORs.
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