卷烟烟气中甜味化合物甜度的理论预测
Theoritical predictions for sweetness of some sweet compounds in cigarette smoke
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摘要: 为预测卷烟烟气中甜味化学成分的甜度,采用量子化学计算和统计学方法,以30种化合物为训练集,10种化合物为验证集,建立了甜味化合物的三维定量构效关系(3D-Quantitative Structure-Activity Relationship,3D-QSAR)的遗传函数逼近模型,并对卷烟烟气中一些甜味化合物甜度值进行了理论预测。结果表明该模型具有较高预测精度,验证集10个化合物甜度的实验值和预测值之间的相关性(R2)可达0.9538,可为理论预测卷烟烟气中化学成分的相对甜度提供理论依据。Abstract: 3D-Quantitative Structure-Activity Relationship (3D-QSAR) genetic function approximation model was established to predict the sweetness of some chemical constituents in cigarette smoke by quantum chemistry calculation and statistics method.Among them, 30 compounds were used as training set and 10 compounds as validate set.The results showed that it was the higher prediction accuracy in this model, and the coefficient of correlation between experimental values and predict value was up to 0.9538 in the validation of 10 compounds.The model supplied theoretical basis on predicting sweetness of compounds in cigarette smoke.