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首页> 外文期刊>Journal of the Serbian Chemical Society >Quantitative structure-retention relationship model for predicting retention indices of constituents of essential oils of Thymus vulgaris (Lamiaceae)
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Quantitative structure-retention relationship model for predicting retention indices of constituents of essential oils of Thymus vulgaris (Lamiaceae)

机译:预测百里香(唇形科)精油成分保留指数的定量结构-保留关系模型

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In this paper, a quantitative structure–retention relationship (QSRR) model was developed for predicting the retention indices (log RI) of 36 constituents of essential oils. First, the chemical structure of each compound was sketched using HyperChem software. Then, molecular descriptors covering different information of molecular structures were calculated by Dragon software. The results illustrated that linear techniques, such as multiple linear regression (MLR), combined with a successful variable selection procedure are capable of generating an efficient QSRR model for predicting the retention indices of different compounds. This model, with high statistical significance (R2 = 0.9781, Q2 LOO = 0.9691, Q2 ext = 0.9546, Q2 L(5)O = 0.9667, F = 245.27), could be used adequately for the prediction and description of the retention indices of other essential oil compounds. The reliability of the proposed model was further illustrated using various evaluation techniques: leave-5-out cross-validation, bootstrap, randomization test and validation through the test set.
机译:在本文中,建立了定量结构-保留关系(QSRR)模型来预测36种精油的保留指数(log RI)。首先,使用HyperChem软件绘制每种化合物的化学结构图。然后,通过Dragon软件计算涵盖分子结构的不同信息的分子描述符。结果表明,线性技术(例如多元线性回归(MLR))与成功的变量选择程序相结合,能够生成有效的QSRR模型,以预测不同化合物的保留指数。此模型具有较高的统计显着性(R2 = 0.9781,Q2 LOO = 0.9691,Q2 ext = 0.9546,Q2 L(5)O = 0.9667,F = 245.27),可以充分用于预测和描述该化合物的保留指数。其他精油化合物。使用各种评估技术进一步说明了所提出模型的可靠性:留出5交叉验证,自举,随机化测试和通过测试集的验证。

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