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MDPI, Toxins, 3(15), p. 225, 2023

DOI: 10.3390/toxins15030225

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In-Vitro and In-Silico Investigation for the Spent-Coffee Bioactive Phenolics as a Promising Aflatoxins Production Inhibitor

Journal article published in 2023 by Amr Farouk ORCID, Tawfiq Alsulami, Hatem S. Ali ORCID, Ahmed Noah Badr ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Aflatoxin, is a naturally occurring polyketide generated by Aspergillus flavus via biosynthetic pathways, including polyketide synthase (PKS) and non-ribosomal enzymes. The in vitro analysis supported by molecular dynamics (MD) techniques was used to examine the antifungal and anti-aflatoxigenic activity of spent coffee grounds (SCGs) methanol extract. The High-Performance Liquid Chromatography results revealed the presence of 15 phenolic acids and five flavonoids. (R)-(+)-Rosmarinic acid (176.43 ± 2.41 µg/g) was the predominant of the detected acids, followed by gallic acid (34.83 ± 1.05 µg/g). At the same time, apigenin-7-glucoside is the dominant flavonoid in the SCGs extract by 1717.05 ± 5.76 µg/g, and naringin (97.27 ± 1.97 µg/g) comes next. The antifungal and anti-aflatoxigenic activity of the SCGs extracts was 380 µL/mL and 460 µL/mL, respectively. The SGGs’ effect of inhibiting five Aspergillus strains’ growth on the agar media ranged between 12.81 ± 1.71 to 15.64 ± 1.08 mm by two diffusion assays. Molecular docking results confirmed the inhibitory action of different phenolics and flavonoids on the PKS and NPS key enzymes of the aflatoxin biosynthetic mechanism. The SCGs extract components with the highest free binding energy, naringin (−9.1 kcal/mL) and apigenin 7-glucoside (−9.1 kcal/mol), were subjected to an MD simulation study. The computational results infer the stabilizing effects on the enzymes upon ligand binding led to the impairment in its functionality. The current study represents a novel attempt to assess the anti aflatoxins mechanism of phenolics and flavonoids targeting PKS and NPS via computational approaches compared to in-vitro assays.