State Key Laboratory of Chemical Resource Engineering, Dept. of Pharmaceutical Engineering, Beijing Univ. of Chemica Technology, Beijing, China.
J Food Sci. 2013 Sep;78(9):S1445-50. doi: 10.1111/1750-3841.12199. Epub 2013 Aug 5.
The sweetness of a compound is of large interest for the food additive industry. In this work, 2 quantitative models were built to predict the logSw (the logarithm of sweetness) of 320 unique compounds with a molecular weight from 132 to 1287 and a sweetness from 22 to 22500000. The whole dataset was randomly split into a training set including 214 compounds and a test set including 106 compounds, represented by 12 selected molecular descriptors. Then, logSw was predicted using a multilinear regression (MLR) analysis and a support vector machine (SVM). For the test set, the correlation coefficients of 0.87 and 0.88 were obtained by MLR and SVM, respectively. The descriptors found in our quantitative structure-activity relationship models are prone to a structural interpretation and support the AH/B System model proposed by Shallenberger and Acree.
甜味化合物对于食品添加剂工业具有重要意义。在这项工作中，我们建立了两个定量模型，用于预测具有分子量为 132 至 1287 和甜度为 22 至 22500000 的 320 种独特化合物的 logSw（甜度对数）。整个数据集被随机分为训练集和测试集，其中训练集包括 214 种化合物，测试集包括 106 种化合物，分别由 12 种选定的分子描述符表示。然后，使用多元线性回归（MLR）分析和支持向量机（SVM）来预测 logSw。对于测试集，MLR 和 SVM 分别获得了 0.87 和 0.88 的相关系数。在我们的定量构效关系模型中发现的描述符易于进行结构解释，并支持 Shallenberger 和 Acree 提出的 AH/B 系统模型。
