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Prediction of terpenoid toxicity based on a quantitative structure–activity relationship model

2019Journal article Open access
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dc.contributor.authorPerestrelo, Rosa
dc.contributor.authorSilva, Catarina
dc.contributor.authorFernandes, Miguel X.
dc.contributor.authorCâmara, José S.
dc.date.accessioned2022-10-04T13:19:46Z
dc.date.available2022-10-04T13:19:46Z
dc.date.issued2019
dc.description.abstractTerpenoids, 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.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationPerestrelo, R., Silva, C., Fernandes, M. X., & Câmara, J. S. (2019). Prediction of terpenoid toxicity based on a quantitative structure–activity relationship model. Foods, 8(12), 628.pt_PT
dc.identifier.doi10.3390/foods8120628pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/4683
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationMadeira Chemistry Research Centre
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectTerpenoidspt_PT
dc.subjectVibrio fischeript_PT
dc.subjectToxicitypt_PT
dc.subjectQSARpt_PT
dc.subjectHeuristic methodpt_PT
dc.subject.pt_PT
dc.subjectFaculdade de Ciências Exatas e da Engenhariapt_PT
dc.subjectCentro de Química da Madeira
dc.titlePrediction of terpenoid toxicity based on a quantitative structure–activity relationship modelpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleMadeira Chemistry Research Centre
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FQUI%2F00674%2F2019/PT
oaire.citation.issue12pt_PT
oaire.citation.startPage628pt_PT
oaire.citation.titleFoodspt_PT
oaire.citation.volume8pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNamePerestrelo
person.familyNameSousa Luís
person.familyNameFernandes
person.familyNameCâmara
person.givenNameRosa
person.givenNameCatarina Grace
person.givenNameMiguel Xavier
person.givenNameJosé
person.identifier1441319
person.identifierC-1300-2019
person.identifierG-3003-2013
person.identifier.ciencia-id251A-D5F7-9E32
person.identifier.ciencia-id9813-3B88-BA8D
person.identifier.ciencia-idED1D-3C7A-467C
person.identifier.ciencia-id481C-08CE-90E5
person.identifier.orcid0000-0002-7223-1022
person.identifier.orcid0000-0002-3018-3165
person.identifier.orcid0000-0002-1840-616X
person.identifier.orcid0000-0003-1965-3151
person.identifier.ridI-2307-2014
person.identifier.ridA-4373-2013
person.identifier.scopus-author-id16686828800
person.identifier.scopus-author-id57194492726
person.identifier.scopus-author-id35466972500
person.identifier.scopus-author-id10140393000
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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