Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewedSupporting research

Integration of Network Pharmacology and Molecular Docking to Explore the Multi-Target Mechanism of Green Tea against Coronary Artery Disease

Riya Singla; Sonia Kamboj; Anurag Bhargava; Akash Jain; Jasmine Chaudhary

Letters in Applied NanoBioScience · 2026

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Summary

This in silico study integrated network pharmacology and molecular docking to elucidate the multi-target mechanism by which five bioactive compounds from green tea (Camellia sinensis) may act against coronary artery disease. Through analysis of 102 key CAD targets, the compounds were shown to interact with 48 common genes involved in inflammatory, oxidative stress, and metabolic pathways relevant to CAD pathogenesis. The findings suggest that green tea's cardioprotective effects may be mediated through multiple molecular targets and could inform development of herbal therapeutics, though the authors note that in vivo validation is necessary.

Regional applicability

The study is a computational analysis with no geographic restriction; findings on green tea phytochemistry and putative molecular targets are globally relevant. However, translation to United Kingdom clinical practice or dietary recommendations would require human clinical trials and evidence on bioavailability and efficacy in the target population.

Key measures

Gene-compound interactions, binding affinity scores, number of common target genes, interaction frequency with CAD-associated genes

Outcomes reported

The study identified 48 common genes through which five green tea compounds (theanine, caffeine, rutin, quercetin, epigallocatechin) interact with coronary artery disease targets, with five key genes (TERT, MMP2, MPO, CA2, MMP9) selected for further mechanistic analysis based on binding affinity and biological relevance.

Supporting research

Explicit green-tea constituents and their candidate cardiovascular mechanisms fit documented food-derived supporting mechanisms.

Limits: Computational network/docking hypothesis only; abstract prevention/treatment wording exceeds demonstrated evidence and must not be reproduced as established efficacy.

Theme
Nutrition & health
Subject
Phytochemicals & bioactive compounds
Study type
Research
Study design
Laboratory / in silico (network pharmacology and molecular docking)
Source type
Peer-reviewed study
Status
Published
System type
Laboratory / in vitro
DOI
10.33263/lianbs153.090
Catalogue ID
NRmuqx0eqe-00r

Topic tags

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