GEORGIANA UȚĂ*,**, A. DIN*, DENISA ȘTEFANIA MANOLESCU*,**#, SPERANȚA AVRAM**
*Regional Research and Development Center for Innovative Materials, Products and Processes from Automotive Industry, University of Pitești, Argeș, Romania
**Department of Anatomy, Animal Physiology and Biophysics, Faculty of Biology, University of Bucharest, Bucharest, Romania
Over the years, experimental studies have shown that secondary metabolites have promising therapeutic potential in a variety of pathologies, but unfortunately, they are usually found in fairly small amounts, and their recovery in the highest possible concentration is a challenge. In view of this, the present project aimed to evaluate the effect of particle size on polyphenol extraction and antioxidant activity of the medicinal species Salvia officinalis L., determination of the pharmacokinetic properties and bioactivity score of two compounds (pinocembrin, luteolin) frequently encountered in sage extract, as well as the in silicoprediction of their biotargets. The data showed that the highest amount of polyphenolic compounds extracted from sage was obtained after maceration of the powder with the smallest particle size, in the range 63–90 μm: 32.47±0.24 milligrams of gallic acid equivalents (GAE) per 1 g dried weight (DW) of sample, in a system of binary solvents (pharmaceutical ethyl alcohol: distilled water). There was a high correlation between the total polyphenol content (TPC) values of the evaluated extracts and their antioxidant activities, the sample with the highest antioxidant activity expressed as Trolox equivalent antioxidant capacity (TEAC = 2.90 µg/mL) being also the one with the highest amount of polyphenols. Bioinformatics analyzes performed on the two compounds showed that both possess molecular properties similar to synthetic drugs: can act as enzyme inhibitors, ligands of nuclear receptors, also having an absolute probability score with a large number of biotargets.
Key words: Salvia officinalis L., polyphenols, particle size, antioxidant activity, in silico approaches.
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