Identification of novel umami molecules via QSAR models and molecular docking

文献类型： 外文期刊

第一作者： Xiu, Hongxia

作者： Xiu, Hongxia;Wang, Fengzhong;Wang, Yutang;Xiu, Hongxia;Zhang, Jingjian;Liu, Yajie;Yang, Huihui;Ren, Haibin;Luo, Bowen;Wang, Zhipeng;Shao, Hong;Shao, Hong;Wang, Yutang

作者机构：

期刊名称：FOOD & FUNCTION （ 影响因子：6.317； 五年影响因子：6.375 ）

ISSN： 2042-6496

年卷期： 2022 年 13 卷 14 期

页码：

收录情况： SCI

摘要： Umami substances can increase the overall taste of food and bring pleasure to people. However, it is still challenging to identify the umami molecules through virtual screening due to the crystal structure of the umami receptor being undefined. Herein, based on the hypothesis that the molecules with bitter and sweet taste characteristics may be umami molecules, this study proposed an in silico method to identify novel umami-tasting molecules in batch from SWEET-DB and BitterDB databases via the QSAR models, PCA, molecular docking and electronic tongue analysis. In total, 169 potential umami molecules were identified through QSAR modeling, PCA, and molecular docking. Of the 169 molecules, 18 were randomly selected, and all were identified as umami molecules via electronic tongue analysis. Among the 18 chosen molecules, 10 molecules could be traced back to their concentration range in food, and finally, 8 molecules were predicted to be nontoxic. This work provides a simple and efficient strategy to identify novel umami molecules, holding an excellent promise for demonstrating the crystal structure of umami receptors and taste-sensing mechanisms. Furthermore, this study opens the possibility for the practical application of new umami molecules in food.

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