Multi-target computational pharmacology and molecular docking study of chromone-based flavonoids from Phyllanthus genus
DOI:
https://doi.org/10.47552/ijam.v17i3.7366Keywords:
Chromone-based flavonoids, Phyllanthus genus, Molecular docking, Multi-target pharmacology, Natural product drug discoveryAbstract
Natural products continue to serve as a prolific source of bioactive scaffolds for drug discovery, particularly in the context of multifactorial diseases such as cancer and chronic inflammation. Chromone-based flavonoids derived from the Phyllanthus genus have attracted considerable attention due to their diverse pharmacological activities; however, their multi-target molecular mechanisms remain insufficiently elucidated.
The present study aimed to investigate the multi-target therapeutic potential of selected chromone-derived flavonoids—quercetin, rutin, Kaempferol, and luteolin—through a comprehensive in silico approach integrating molecular docking and ADMET prediction. Target proteins associated with oxidative stress, inflammation, and cancer progression, including NF-κB, TNF-α, IL-6, matrix metalloproteinases (MMPs), nitric oxide synthase (NOS), PIK3CA, EGFR, and prostaglandin E2 (PGE-2), were selected based on their established roles in disease pathogenesis.
Docking simulations revealed significant binding affinities across multiple targets, with rutin exhibiting superior interactions against key oncogenic and inflammatory proteins such as NOS and PIK3CA (binding scores up to −11.2 kcal/mol). Flavonoids demonstrated notable interactions with MMPs and EGFR, suggesting potential roles in inhibiting tumor invasion and proliferation. ADMET profiling further indicated acceptable pharmacokinetic characteristics, with rutin and quercetin displaying comparatively favorable toxicity profiles.
Collectively, these findings highlight the polypharmacological potential of chromone-based flavonoids from Phyllanthus species and support their prospective development as multi-target therapeutic agents. However, further experimental validation is warranted to substantiate these computational insights and facilitate clinical translation.
These findings provide a strong computational basis for the development of multi-target therapeutics derived from natural products.
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