新的原子指数用于松茸和姬松茸QSRR研究  

Quantitative Structure-Retention Relationship Study of Volatile Components in Tricholoma matsutake and Agaricus blazei Using New Atomic Index

作　　者：堵锡华[1] 陈艳[1] 李靖[1] 田林[1] 徐艳[1] DU Xihua;CHEN Yan;LI Jing;TIAN Lin;XU Yan(School of Materials and Chemical Engineering,Xuzhou University of Technology,Xuzhou Jiangsu 221018,China)

机构地区：[1]徐州工程学院材料与化学工程学院,江苏徐州221018

出　　处：《西南大学学报（自然科学版）》2024年第10期80-89,共10页Journal of Southwest University(Natural Science Edition)

基　　金：国家自然科学基金项目(21472071);江苏省自然科学基金项目(BK20171168);江苏省高校自然科学基金重大项目(18KJA430015)。

摘　　要：松茸和姬松茸含有多种活性成分,不但具有较高的营养价值,还具有良好的保健功效.为构建松茸和姬松茸挥发性成分保留时间神经网络的定量结构—保留关系模型,根据松茸和姬松茸挥发性化合物中原子的特性和连接状态,提出了一种新的分子结构参数(原子指数A),并计算了松茸和姬松茸挥发性成分的电性拓扑状态指数(Em)和电性距离矢量(Mm).选取电性拓扑状态指数的E_(2)和电性距离矢量的M_(15)和M_(21)等3种指数,结合原子指数A共4种结构参数,作为BP神经网络法的输入层变量,松茸挥发性成分的色谱保留时间作为输出层变量,采用4-8-1的网络结构,构建的模型总相关系数r为0.9919,根据该模型计算得到的保留时间预测值与文献实验值的平均误差为0.57;同样采用这4种参数,与姬松茸挥发性成分的保留时间进行研究,采用4-7-1的网络结构,所得模型总相关系数r为0.9929,保留时间预测值与实验值的平均误差为0.58.结果表明:—CH_(3),—CH_(2)—和氧氮杂原子等基团片段及连接方式是影响松茸和姬松茸挥发性成分色谱保留时间的主要因素.Tricholoma matsutake and Agaricus blazei contain a variety of active ingredients,which not only have high nutritional value,but also good for health.In order to establish neural network model of quantitative structure-retention relationship(QSRR)for the chromatographic retention time of volatile components of T.matsutake and A.blazei,a novel molecular structure parameter-atomic index A was derived based on characteristics and connectivity of the atoms in volatile components molecules.The electrical topology state index(E m)and the electric distance vector(M m)of volatile components of the two substances were calculated.Three configuration parameters,including the electrical topology state indices E_(2)and the electric distance vector M_(15),M_(21)were selected.Then,the four parameters were used as input layer variables and the chromatographic retention time of T.matsutake was used as the output layer variable.Besides,the 4-8-1 network structure was adopted and BP neural network method was used to establish a neural network model.The total correlation coefficient r was 0.9919.The mean error between the predicted values and the experimental values of retention time was 0.57.Using the same method,the five configuration parameters were selected.The 4-7-1 network structure was adopted and BP neural network method was used to establish a model to study chromatographic retention time of volatile components of A.blazei.The total correlation coefficient r was 0.9929.The mean error between the predicted values and the experimental values of retention time was 0.58.The results showed that fragments of—CH_(3),—CH_(2)—and oxynitrogen heteroatoms groups and the way of connection were the main factors affecting the retention time of volatile components in T.matsutake and A.blazei.This study provides theoretical guidance for exploring the chromatographic retention mechanism of volatile components in T.matsutake and A.blazei.

关 键 词：松茸 姬松茸 挥发性成分 保留时间 神经网络 

分 类 号：TS262[轻工技术与工程—发酵工程]