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Open AccessArticle

Prediction of Terpenoid Toxicity Based on a Quantitative Structure–Activity Relationship Model

1
CQM, Centro de Química da Madeira, Universidade da Madeira, Campus da Penteada, 9020-105 Funchal, Portugal
2
BioLab, Instituto Universitario de Bio-Orgánica “Antonio González” (IUBO-AG), Universidad de La Laguna, C/ Astrofísico Francisco Sánchez 2, 38200 La Laguna, Spain
3
Faculdade de Ciências Exatas e da Engenharia, Universidade da Madeira, Campus da Penteada, 9020-105 Funchal, Portugal
*
Authors to whom correspondence should be addressed.
Foods 2019, 8(12), 628; https://doi.org/10.3390/foods8120628
Received: 30 September 2019 / Revised: 24 November 2019 / Accepted: 26 November 2019 / Published: 1 December 2019
(This article belongs to the Section Food Quality and Safety)
Terpenoids, including monoterpenoids (C10), norisoprenoids (C13), and sesquiterpenoids (C15), constitute a large group of plant-derived naturally occurring secondary metabolites with highly diverse chemical structures. A quantitative structure–activity relationship (QSAR) model to predict terpenoid toxicity and to evaluate the influence of their chemical structures was developed in this study by assessing in real time the toxicity of 27 terpenoid standards using the Gram-negative bioluminescent Vibrio fischeri. Under the test conditions, at a concentration of 1 µM, the terpenoids showed a toxicity level lower than 5%, with the exception of geraniol, citral, (S)-citronellal, geranic acid, (±)-α-terpinyl acetate, and geranyl acetone. Moreover, the standards tested displayed a toxicity level higher than 30% at concentrations of 50–100 µM, with the exception of (+)-valencene, eucalyptol, (+)-borneol, guaiazulene, β-caryophellene, and linalool oxide. Regarding the functional group, terpenoid toxicity was observed in the following order: alcohol > aldehyde ~ ketone > ester > hydrocarbons. The CODESSA software was employed to develop QSAR models based on the correlation of terpenoid toxicity and a pool of descriptors related to each chemical structure. The QSAR models, based on t-test values, showed that terpenoid toxicity was mainly attributed to geometric (e.g., asphericity) and electronic (e.g., maximum partial charge for a carbon (C) atom (Zefirov’s partial charge (PC)) descriptors. Statistically, the most significant overall correlation was the four-parameter equation with a training coefficient and test coefficient correlation higher than 0.810 and 0.535, respectively, and a square coefficient of cross-validation (Q2) higher than 0.689. According to the obtained data, the QSAR models are suitable and rapid tools to predict terpenoid toxicity in a diversity of food products.
Keywords: terpenoids; Vibrio fischeri; toxicity; QSAR; heuristic method terpenoids; Vibrio fischeri; toxicity; QSAR; heuristic method
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MDPI and ACS Style

Perestrelo, R.; Silva, C.; Fernandes, M.X.; Câmara, J.S. Prediction of Terpenoid Toxicity Based on a Quantitative Structure–Activity Relationship Model. Foods 2019, 8, 628.

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