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This study evaluated the topical effect of Lepidium sativum lyophilized seed extract (LSLE) towards Sustanon-induced alopecia in male adult Wistar albino rats in vivo, compared to minoxidil topical reference standard drug (MRD). LC–MS/MS together with molecular networking was used to profile the metabolites of LSLE. LSLE treated group revealed significant changes in alopecia related biomarkers, perturbation of androgenic markers; decline in testosterone level and elevation in 5α-reductase (5-AR); decline in the cholesterol level. On the other hand, LSLE treated group showed improvement in vascular markers; CTGF, FGF and VEGF. Groups treated topically with minoxidil and LSLE showed significant improvement in hair length. LC–MS/MS profile of LSLE tentatively identified 17 constituents: mainly glucosinolates, flavonoid glycosides, alkaloids and phenolic acids. The results point to the potential role of LSLE in the treatment of alopecia through decreasing 5(alpha)-dihydrotestosterone levels. Molecular docking was attempted to evaluate the probable binding mode of identified compounds to androgen receptor (PDB code: 4K7A).

Seven avocado “Persea americana” seeds belonging to 4 varieties, collected from different localities across the world, were profiled using HPLC–MS/MS and GC/MS to explore the metabolic makeup variabilities and antidiabetic potential. For the first time, 51 metabolites were tentatively-identified via HPLC–MS/MS, belonging to different classes including flavonoids, biflavonoids, naphthodianthrones, dihydrochalcones, phloroglucinols and phenolic acids while 68 un-saponified and 26 saponified compounds were identified by GC/MS analysis. The primary metabolic variabilities existing among the different 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 different samples was explored using in-vitro amylase and glucosidase inhibition assays, which pointed out to Gwen (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.