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New Phenolic Derivatives of Thiazolidine-2,4-dione with Antioxidant and Antiradical Properties: Synthesis, Characterization, In Vitro Evaluation, and Quantum Studies

Gabriel Marc, Anca Stana, Smaranda Dafina Oniga, Adrian Pı̂rnău, Laurian Vlase, Ovidiu Oniga

Molecules, 2019

59 citations

Abstract

Oxidative stress has been incriminated in the physiopathology of many diseases, such as diabetes, cancer, atherosclerosis, and cardiovascular and neurodegenerative diseases. There is a great interest in developing new antioxidants that could be useful for preventing and treating conditions for which oxidative stress is suggested as the root cause. The thiazolidine-2,4-dione derivatives have been reported to possess various pharmacological activities and the phenol moiety is known as a pharmacophore in many naturally occurring and synthetic antioxidants. Twelve new phenolic derivatives of thiazolidine-2,4-dione were synthesized and physicochemically characterized. The antioxidant capacity of the synthesized compounds was assessed through several in vitro antiradical, electron transfer, and Fe2+ chelation assays. The top polyphenolic compounds 5f and 5l acted as potent antiradical and electron donors, with activity comparable to the reference antioxidants used. The ferrous ion chelation capacity of the newly synthesized compounds was modest. Several quantum descriptors were calculated in order to evaluate their influence on the antioxidant and antiradical properties of the compounds and the chemoselectivity of the radical generation reactions has been evaluated. The correlation with the energetic level of the frontier orbitals partially explained the antioxidant activity, whereas a better correlation was found while evaluating the O–H bond dissociation energy of the phenolic…

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Evidence Hub reads this as a experimental / empirical study, done in cell cultures (in vitro), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.

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