The extensive utilization of the low-energy dipeptide sweetener aspartame in foods leads to various studies on searching for new sweeteners in series. However, the real mechanistic cause of their sweetness power is st...The extensive utilization of the low-energy dipeptide sweetener aspartame in foods leads to various studies on searching for new sweeteners in series. However, the real mechanistic cause of their sweetness power is still not completely known owing to their complex interactions with human sweet receptor, which may be different from that of other sweeteners to some extent. In this contribution, predictive quantitative structure-property relationship(QSPR) models have been developed for diverse aspartame analogues using Materials Studio 5.0 software. The optimal QSPR model(r2 = 0.913, r2 CV = 0.881 and r2 pred = 0.730) constructed by the genetic function approximation method has been validated by the tests of cross validation, randomization, external prediction and other statistical criteria, which shows that their sweetness power is mainly governed by their electrotopological-state indices(SssCH and SsNH), spatial descriptors(Shadow length: LX, ellipsoidal volume and Connolly surface occupied volume) and topological descriptors(Chi(3): cluster and Chi(0)(valence modified)), which partially supports both multipoint attachment theory proposed by Nofre and Tinti et al. and B-X theory proposed by Kier et al.. Present exploited results provide the key structural features for the sweetness power of aspartame analogues, supplement the mechanistic understanding of the sweet perception, and would be also helpful for the design of potent sweetener analogs prior to their synthesis.展开更多
基金Supported by the National Natural Science Foundation of China(No.21673207)Special Fundamental Research Fund for the Central Public Scientific Research Institutes(No.562018Y-5983)Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition(No.2017SICR115,2017SICR101)
文摘The extensive utilization of the low-energy dipeptide sweetener aspartame in foods leads to various studies on searching for new sweeteners in series. However, the real mechanistic cause of their sweetness power is still not completely known owing to their complex interactions with human sweet receptor, which may be different from that of other sweeteners to some extent. In this contribution, predictive quantitative structure-property relationship(QSPR) models have been developed for diverse aspartame analogues using Materials Studio 5.0 software. The optimal QSPR model(r2 = 0.913, r2 CV = 0.881 and r2 pred = 0.730) constructed by the genetic function approximation method has been validated by the tests of cross validation, randomization, external prediction and other statistical criteria, which shows that their sweetness power is mainly governed by their electrotopological-state indices(SssCH and SsNH), spatial descriptors(Shadow length: LX, ellipsoidal volume and Connolly surface occupied volume) and topological descriptors(Chi(3): cluster and Chi(0)(valence modified)), which partially supports both multipoint attachment theory proposed by Nofre and Tinti et al. and B-X theory proposed by Kier et al.. Present exploited results provide the key structural features for the sweetness power of aspartame analogues, supplement the mechanistic understanding of the sweet perception, and would be also helpful for the design of potent sweetener analogs prior to their synthesis.
