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将荧光光谱,人工神经网络和主客体化学方法相结合,建立了一种色氨酸对映异构体组成的定量测定方法。该方法基于牛血清蛋白的手性识别功能,运用荧光光谱表征色氨酸对映异构体与牛血清蛋白之间的非对映异构相互作用,利用加入了牛血清蛋白的色氨酸溶液的荧光光谱会随其中色氨酸对映异构体组成的变化而变化的现象,以人工神经网络方法建立了荧光光谱与对映异构体组成之间的数学模型。对于建立的人工神经网络模型用留一交叉验证方法进行了检验。检验结果表明,该方法是一种可行的、灵敏度较高的色氨酸对映异构体组成的测定方法,能够用于测定浓度为2.500μmol·L~(-1)的色氨酸溶液中2种色氨酸对映异构体的摩尔分数。
A fluorescence spectrometry, artificial neural network and host-guest chemistry were combined to establish a quantitative method for the determination of tryptophan enantiomers. Based on the chiral recognition function of bovine serum albumin (BSA), the method uses fluorescence spectroscopy to characterize the diastereomeric interaction between the tryptophan enantiomer and bovine serum albumin. The tryptophan solution containing bovine serum albumin The fluorescence spectrum changes with the change of tryptophan enantiomer. The artificial neural network method is used to establish the mathematical model between fluorescence spectrum and enantiomer composition. The established artificial neural network model was tested with a cross-validation method. The test results show that this method is a feasible and sensitive method for the determination of tryptophan enantiomers and can be used to determine tryptophan solution with a concentration of 2.500μmol·L -1 The mole fraction of two tryptophan enantiomers.