Dietary Flavonoid Network Pharmacology Predictions with Multi-Evidence Validation

A network pharmacology framework predicts therapeutic properties of 14 dietary flavonoids based on a master network of 17,869 human proteins and 1,496 FDA-approved drugs, comprising 278,768 interactions. The dataset was created by Koyo Fujisaki and last updated in April 2026. It includes computational predictions validated by experimental cytotoxicity data and epidemiological evidence from 506 foods and PubMed analysis.

Use Cases

• Predicting multi-target therapeutic effects of dietary flavonoids based on protein interaction networks.
• Validating computational predictions with experimental cytotoxicity data (LC50 values) from cancer cell models.
• Identifying literature-supported food-therapeutic combinations based on systematic PubMed analysis.
• Comparing target protein profiles of flavonoids against FDA-approved drugs for cardiovascular and anticancer applications.

Strengths

• Quantitative network includes 278,768 interactions among 17,869 proteins, 14 flavonoids, and 1,496 drugs.
• Experimental validation shows computational association strength explains 84% of variance in experimental potency (R² = 0.843).
• Systematic evidence integration includes 685 food-ATC therapeutic combinations and 96 literature-supported associations from 132 references.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is small (43.9 KB), indicating limited scope or highly summarized content.

Provenance

Source

Koyo Fujisaki via figshare

Collection Method

Constructed via a multi-tiered network pharmacology framework integrating computational, experimental, and epidemiological evidence.

Freshness

Last updated 2026-04-14 04:14:44; freshness should be verified.