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PLS regression-based chemometric modeling of odorant properties of diverse chemical constituents of black tea and coffee

机译：基于回归的红茶和咖啡不同化学成分的气味性能的化学计量型建模

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摘要

Tea and coffee are the most attractive non-alcoholic beverages used worldwide due to the odorant properties of diverse components present in these beverages. The aim of this work is to investigate the key structural features which regulate the odorant properties of constituents present in black tea and coffee using regression-based chemometric models. We have also investigated the key structural properties which create the odor difference between tea and coffee. We have employed different variable selection strategies to extract the most relevant variables prior to development of final partial least squares (PLS) models. The models were extensively validated using different validation metrics, and the results justify the reliability and usefulness of the developed predictive PLS models. The best PLS model captured the necessary structural information on relative hydrophobic surface area, heteroatoms with higher number of multiple bonds, hydrogen atoms connected to C-3(sp(3))/C-2(sp(2))/C-3(sp(2))/C-3(sp) fragments, electron-richness, C-O atom pairs at the topological distance 10 and surface weighted charged partial negative surface areas for explaining the odorant properties of the constituents present in black tea. On the other hand, C-S atom pairs at the topological distance 1, C-C atom pairs at the topological distance 5, donor atoms like N and O for hydrogen bonds, hydrogen atoms connected to C-3(sp(3))/C-2(sp(2))/C-3(sp(2))/C-3(sp) fragments and R-CX-X fragments (where, R represents any group linked through carbon and X represents any heteroatom (O, N, S, P, Se, and halogens)) are the key structural components captured by the PLS model developed from the constituents present in coffee. The developed models can thus be successfully utilized for in silico prediction of odorant properties of diverse classes of compounds and exploration of the structural information which creates the odor difference between black tea and coffee.
机译：茶叶和咖啡是全球最具吸引力的非酒精饮料，由于这些饮料中存在的不同组件的气味性质。这项工作的目的是研究使用回归的化学计量模型调节红茶和咖啡中存在的成分的气味性能的关键结构特征。我们还研究了在茶叶和咖啡之间产生气味差异的关键结构性。我们已经使用不同的可变选择策略来提取最终部分最小二乘（PLS）模型之前提取最相关的变量。使用不同的验证度量广泛验证模型，结果证明了开发的预测PLS模型的可靠性和有用性。最佳PLS模型捕获了关于相对疏水表面积的必要结构信息，杂原子具有较多多键的杂原子，连接到C-3的氢原子（SP（3））/ C-2（SP（2））/ C-3 （SP（2））/ C-3（SP）片段，富含电子，CO原子对在拓扑距离10和表面加权带电的部分负面区域，用于解释在红茶中存在的成分的气味性质。另一方面，CS原子对在拓扑距离1，CC原子对拓扑距离5，供体原子如N和O用于氢键，氢原子连接到C-3（SP（3））/ C-2 （SP（2））/ C-3（SP（2））/ C-3（SP）片段和R-CX-X片段（其中，R表示通过碳连接的任何组，X代表任何杂原子（O，N ，S，p，se和卤素））是由从咖啡中存在的组分开发的PLS模型捕获的关键结构组件。因此，开发的模型可以成功地用于不同类化合物的异味性质的硅预测，并探索了黑茶和咖啡之间的气味差异。

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  • 来源
    《RSC Advances》 |2018年第5期|共12页
  • 作者

    Ojha Probir Kumar; Roy Kunal;

  • 作者单位

    Jadavpur Univ Dept Pharmaceut Technol Drug Theoret &

    Cheminformat Lab Kolkata 700032 India;

    Jadavpur Univ Dept Pharmaceut Technol Drug Theoret &

    Cheminformat Lab Kolkata 700032 India;

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  • 正文语种 eng
  • 中图分类 化学;
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