Facultad de Ciencia y Tecnología, Univ. del Azuay, Av. 24 de Mayo 7-77 y Hernán Malo, Cuenca, Ecuador.
Inst. de Investigaciones Fisicoquímicas Teóricas y Aplicadas (INIFTA), CONICET, UNLP, Diag. 113 y 64, s/n, 1900, La Plata, Argentina.
J Food Sci. 2019 Apr;84(4):770-781. doi: 10.1111/1750-3841.14477. Epub 2019 Feb 27.
The aim of this work was the foodinformatic (chemoinformatic) modeling of volatile organic compounds (VOCs) of different samples of peppers based on a quantitative structure-property relationship (QSPR) for the retention indices of 273 identified compounds. The experimental retention indices were measured by means of comprehensive two-dimensional gas chromatography combined with quadrupole-mass spectrometry (GC × GC/qMS) using the BPX5 and BP20 column coupled system. All the VOCs were represented by means of both conformation-independent molecular descriptors and molecular fingerprints calculated in the Dragon and PaDEL-Descriptor software. The dataset was divided into training, validation and test sets of molecules according to the Balanced Subsets Method (BSM). Subsequently, the V-WSP unsupervised variable reduction method was used to reduce the presence of multicollinearity, redundancy, and noise in the initial pool of 4,336 molecular descriptors and fingerprints. Using this method, a reduced pool of 1,664 was submitted to the supervised selection by means of the replacement method (RM) variable subset selection in order to define a four-descriptor model. The quality of the model was measured by means of the coefficient of determination and the root-mean-square deviation in fitting ( and ), validation ( and ), and prediction ( and ). The negligible differences among the parameters in the three sets indicate a stable and predictive QSPR model. This quantitative structure-activity relationship was developed keeping in mind the five principles defined by the Organization for Economic Co-operation and Development (OECD) to make it applicable. PRACTICAL APPLICATION: This predictive mathematical model developed from the retention indices of 273 volatile organic compounds (VOCs) detected in pepper samples could be useful for chromatographers working on the identification of other common VOCs in peppers or other foods by means of comprehensive two-dimensional gas chromatography combined with quadrupole-mass spectrometry (GC × GC/qMS) using a bi-dimensional stationary phase coupled system (BPX5 and BP20).
本工作旨在基于 273 种已鉴定化合物的保留指数，建立不同辣椒样品挥发性有机化合物（VOCs）的食品信息学（ chemoinformatic ）模型，即定量构效关系（QSPR）。采用 BPX5 和 BP20 柱偶联系统的全二维气相色谱-四级杆质谱联用（GC×GC/qMS）实验测量了保留指数。所有 VOCs 均采用 Dragon 和 PaDEL-Descriptor 软件计算的构象独立分子描述符和分子指纹表示。根据平衡子集方法（BSM），将数据集分为训练、验证和测试分子集。随后，采用 V-WSP 无监督变量缩减方法，减少初始 4336 个分子描述符和指纹中存在的多重共线性、冗余和噪声。使用这种方法，将 1664 个缩减的分子池提交给有监督选择，采用替换方法（RM）变量子集选择，以定义一个四变量模型。通过拟合（ 和 ）、验证（ 和 ）和预测（ 和 ）的决定系数和均方根偏差来衡量模型的质量。三个集合中参数的可忽略差异表明模型具有稳定的预测能力。该定量构效关系是根据经济合作与发展组织（OECD）定义的五项原则制定的，使其具有适用性。实际应用：该预测数学模型是基于从辣椒样品中检测到的 273 种挥发性有机化合物（VOCs）的保留指数开发的，对于使用二维固定相偶联系统（BPX5 和 BP20）的全二维气相色谱-四级杆质谱联用（GC×GC/qMS）通过综合二维气相色谱对辣椒或其他食品中其他常见 VOCs 进行鉴定的色谱工作者可能很有用。
