Garlic-Derived Phytochemical Candidates Predicted to Disrupt SARS-CoV-2 RBD-ACE2 Binding and Inhibit Viral Entry

大蒜来源的植物化学候选物预计可干扰SARS-CoV-2 RBD-ACE2结合并抑制病毒入侵

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作者:Martha Susana García-Delgado ,Aldo Fernando Herrera-Rodulfo ,Karen Y Reyes-Melo ,Ashly Mohan ,Fernando Góngora-Rivera ,Jesús Andrés Pedroza-Flores ,Alma D Paz-González ,Gildardo Rivera ,María Del Rayo Camacho-Corona ,Mauricio Carrillo-Tripp

Abstract

The emergence of SARS-CoV-2 and its rapid global spread underscores the urgent need for novel therapeutic strategies. This study investigates the antiviral potential of Allium sativum (garlic) extracts against SARS-CoV-2, focusing on disruption of the spike protein's receptor-binding domain (RBD) interaction with angiotensin-converting enzyme 2 (ACE2), a critical step in viral entry. Two garlic cultivars (Tigre and Fermín) were processed via oven-drying or freeze-drying, followed by maceration with CH2Cl2/MeOH (1:1) and fractionation with liquid-liquid partition. ELISA immunoassays revealed that freeze-dried Tigre (TL) extracts had the highest inhibitory activity (42.16% at 0.1 µg/mL), with its aqueous fraction achieving 57.26% inhibition at 0.01 µg/mL. Chemical profiling via GC-MS found sulfur and other types of compounds. Molecular docking identified three garlic TL-derived aqueous fraction compounds with strong binding affinities (ΔG = -7.5 to -6.9 kcal/mol) to the RBD-ACE2 interface. Furthermore, ADME in silico analysis highlighted one of them (L17) as the main candidate, having high gastrointestinal absorption, blood-brain barrier permeability, and compliance with drug-likeness criteria. These findings underscore garlic-derived compounds as promising inhibitors of SARS-CoV-2 entry, calling for further preclinical validation. The study integrates experimental and computational approaches to advance natural product-based antiviral discovery, emphasizing the need for standardized formulations to address therapeutic variability across viral variants. Keywords: Allium sativum; bioactive metabolite identification; computational drug discovery; drug-likeness; pharmacokinetic profiling.

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