Abstract:
Seven avocado “Persea americana” seeds belonging to 4 varieties, collected from diferent
localities across the world, were profled using HPLC–MS/MS and GC/MS to explore the metabolic
makeup variabilities and antidiabetic potential. For the frst time, 51 metabolites were tentatively-
identifed via HPLC–MS/MS, belonging to diferent classes including favonoids, bifavonoids,
naphthodianthrones, dihydrochalcones, phloroglucinols and phenolic acids while 68 un-saponifed
and 26 saponifed compounds were identifed by GC/MS analysis. The primary metabolic variabilities
existing among the diferent varieties were revealed via GC/MS-based metabolomics assisted by
unsupervised pattern recognition methods. Fatty acid accumulations were proved as competent, and
varietal-discriminatory metabolites. The antidiabetic potential of the diferent samples was explored
using in-vitro amylase and glucosidase inhibition assays, which pointed out toGwen (KG) as the most
potent antidiabetic sample. This could be attributed to its enriched content of poly-unsaturated
fatty acids and polyphenolics. Molecular docking was then performed to predict the most promising
phytoligands in KG variety to be posed as antidiabetic drug leads. The highest in-silico α-amylase
inhibition was observed with chrysoeriol-4′-O-pentoside-7-O-rutinoside, apigenin-7-glucuronide and
neoeriocitrin which might serve as potential drug leads for the discovery of new antidiabetic remedies.
