In Vitro Antioxidant and In Vivo Antigenotoxic Features of a Series of 61 Essential Oils and Quantitative Composition-Activity Relationships Modeled through Machine Learning Algorithms

Milan Mladenović; Roberta Astolfi; Nevena Tomašević; Sanja Matić; Mijat Božović; Filippo Sapienza; Rino Ragno

doi:10.3390/antiox12101815

In Vitro Antioxidant and In Vivo Antigenotoxic Features of a Series of 61 Essential Oils and Quantitative Composition-Activity Relationships Modeled through Machine Learning Algorithms

Antioxidants (Basel). 2023 Sep 29;12(10):1815. doi: 10.3390/antiox12101815.

Authors

Milan Mladenović¹, Roberta Astolfi², Nevena Tomašević¹, Sanja Matić³, Mijat Božović⁴, Filippo Sapienza², Rino Ragno²

Affiliations

¹ Kragujevac Center for Computational Biochemistry, Department of Chemistry, Faculty of Science, University of Kragujevac, Radoja Domanovića 12, P.O. Box 60, 34000 Kragujevac, Serbia.
² Rome Center for Molecular Design, Department of Drug Chemistry and Technology, Faculty of Pharmacy and Medicine, Rome Sapienza University, P. le A. Moro 5, 00185 Rome, Italy.
³ Department of Science, Institute for Information Technologies Kragujevac, University of Kragujevac, Jovana Cvijića bb, 34000 Kragujevac, Serbia.
⁴ Faculty of Science and Mathematics, University of Montenegro, Džordža Vašingtona bb, 81000 Podgorica, Montenegro.

Abstract

The antioxidant activity of essential oils (EOs) is an important and frequently studied property, yet it is not sufficiently understood in terms of the contribution of EOs mixtures' constituents and biological properties. In this study, a series of 61 commercial EOs were first evaluated as antioxidants in vitro, following as closely as possible the cellular pathways of reactive oxygen species (ROS) generation. Hence, EOs were assessed for the ability either to chelate metal ions, thus interfering with ROS generation within the respiratory chain, or to neutralize 2,2-diphenyl-1-picrylhydrazyl (DPPH^•) and lipid peroxide radicals (LOO^•), thereby halting lipid peroxidation, as well as to neutralize 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid cation radicals (ABTS^•+) and hydroxyl radicals (OH^•), thereby preventing the ROS species from damaging DNA nucleotides. Showing noteworthy potencies to neutralize all of the radicals at the ng/mL level, the active EOs were also characterized as protectors of DNA double strands from damage induced by peroxyl radicals (ROO^•), emerging from 2,2'-azobis-2-methyl-propanimidamide (AAPH) as a source, and OH^•, indicating some genome protectivity and antigenotoxicity effectiveness in vitro. The chemical compositions of the EOs associated with the obtained activities were then analyzed by means of machine learning (ML) classification algorithms to generate quantitative composition-activity relationships (QCARs) models (models published in the AI4EssOil database available online). The QCARs models enabled us to highlight the key features (EOSs' chemical compounds) for exerting the redox potencies and to define the partial dependencies of the features, viz. percentages in the mixture required to exert a given potency. The ML-based models explained either the positive or negative contribution of the most important chemical components: limonene, linalool, carvacrol, eucalyptol, α-pinene, thymol, caryophyllene, p-cymene, eugenol, and chrysanthone. Finally, the most potent EOs in vitro, Ylang-ylang (Cananga odorata (Lam.)) and Ceylon cinnamon peel (Cinnamomum verum J. Presl), were promptly administered in vivo to evaluate the rescue ability against redox damage caused by CCl₄, thereby verifying their antioxidant and antigenotoxic properties either in the liver or in the kidney.

Keywords: antioxidant and antigenotoxic features in vitro and in vivo; essential oils; machine learning.

Grants and funding

This work was supported by the Serbian Ministry of Science, Technological Development, and Innovation (Agreement Nos. 451-03-47/2023-01/200122 and 451-03-47/2023-01/200378) and supported by two grants from Progetti di Ricerca di Università 2015, Sapienza Università di Roma (C26A15RT82 and C26A15J3BB).