摘要
气相色谱保留指数(RI)是色谱分析中的重要参数,但通过实验获取RI值的过程较为繁琐,需要建立一种简便、高效、准确的模型来预测RI值。本文搜集了60种植物精油成分的RI实验值,构建了精油成分化合物的结构性质与RI值之间的全息定量构效关系(HQSAR)模型。当碎片大小(fragment size)、碎片特征(fragment distinction)和全息长度(hologram length)模型参数分别设置为“1~4”、“C,Ch”和199时,可以建立最优HQSAR模型。利用外部测试集验证和留一交叉验证对模型进行检验,经外部测试集验证的预测均方根误差(RMSEP)、预测决定系数(Q_(F3)^(2))、一致性相关系数(CCC)和平均相对误差(MRE)分别为40.45、0.984、0.968和2.20%;经留一交叉验证的交叉验证均方根误差(RMSECV)和MRE分别为72.56和4.17%。此外,HQSAR模型的分子贡献图表明,芳香族化合物的烷基链在连接了羟基基团后,其RI值会增大;脂肪族化合物中存在的长链烷基也会导致RI值增大。研究结果表明,所建立的HQSAR模型能够用于预测植物精油成分的RI值,并为其他精油成分RI值的预测提供可靠依据。
The gas chromatography retention index(RI)is an important parameter for the identification of different types of compounds in the field of chromatographic analysis;however,the experimental collection of RI values is a extremely cumbersome process.Thus,there is an urgent need for the establishment of a simple,efficient,and accurate model for the prediction of the RI values of compounds.In this study,first,the experimental RI values for 60 plant essential oil constituents were obtained.Next,a model describing the hologram quantitative structure-activity relationship(HQSAR)between the structural properties of the essential oil constituents and their RI values was investigated and constructed.The optimal HQSAR model was established by setting the model parameters“fragment size”,“fragment distinction”,“hologram length”and“principal components”to“1-4”,“C,Ch”,“199”,and“4”,respectively.Finally,the predictive ability of the model was verified using external test set validation and leave-one-out cross-validation(LOO-CV).The experimental results were as follows,the root mean square error of prediction(RMSEP),predictive determination coefficient(Q_(F3)^(2)),concordance correlation coefficient(CCC),and mean relative error(MRE)for external test set validation were 40.45,0.984,0.968,and 2.20%,respectively.Meanwhile,the root mean square error of cross validation(RMSECV)and MRE for LOO-CV were 72.56 and 4.17%,respectively.These findings demonstrate that the established HQSAR model has a good predictive ability and can accurately predict the RI values of plant essential oil constituents.In addition,the molecular contribution maps of the HQSAR model revealed that the RI values of aromatic compounds increase when hydroxyl groups are connected to their alkyl chains.Aliphatic compounds feature long chain alkyl groups,which can lead to an increase in RI values.The above phenomena highlight the promising application prospects of HQSAR for studying the RI values of plant essential oil constituents.Therefore,this study provides a reliable theoretical basis for predicting the RI values of other essential oil constituents.
作者
郭锐
焦龙
胡祖彪
王清臣
钟汉斌
景明利
GUO Rui;JIAO Long;HU Zubiao;WANG Qingchen;ZHONG Hanbin;JING Mingli(College of Chemistry and Chemical Engineering,Xi’an Shiyou University,Xi’an 710065,China;Changqing General Drilling Company,CNPC Chuanqing Drilling Engineering Co.Ltd.,Xi’an 710016,China;School of Electronic Engineering,Xi’an Shiyou University,Xi’an 710065,China)
出处
《色谱》
CAS
CSCD
北大核心
2024年第4期380-386,共7页
Chinese Journal of Chromatography
基金
国家自然科学基金项目(21807068,21775118,22177066)
陕西省自然科学基金项目(2020KJXX-030,2021KJXX-51)
陕西省教育厅青年创新团队建设科研计划项目(21JP097)
陕西省教育厅科研计划资助项目(2023-JC-QN-0169)
陕西省自然科学基础研究计划资助项目(22JP064)
全国大学生创新创业培训计划项目(S202010705040)
西安石油大学研究生创新与实践能力培养项目(YCS23111002,YCS23113052,YCS23113053).
关键词
全息定量构效关系
气相色谱保留指数
植物精油
分子贡献图
hologram quantitative structure-activity relationship(HQSAR)
gas chromatographic retention index
plant essential oil
molecular contribution map
