GC-MS Metabolomic Profiling and PPARγ Docking Data for Traditional Rice Varieties

Saranya Nallusamy's research dataset contains GC-MS metabolomic profiling of six traditional rice varieties, identifying 561 compounds. The data includes results from network analysis, ADMET prediction, and virtual screening against the PPARγ receptor, identifying oleic acid as a promising compound. The dataset was last updated on 2026-05-05.

Use Cases

• Virtual screening for PPARγ agonists based on the identified 561 rice metabolites.
• ADMET property prediction for phytochemical compounds from traditional rice.
• Molecular dynamics simulation analysis based on the provided 200 ns simulation parameters and results.
• Pathway enrichment analysis for bioactive compounds in functional foods.

Strengths

• Metabolomic profiling identified 561 distinct compounds across six rice varieties.
• Includes specific molecular docking scores (e.g., -9.451 kcal/mol for oleic acid) and binding free energy calculations.
• Analysis includes a 200 ns molecular dynamics simulation for stability assessment.

Limitations

• The dataset is very small at 40.2 KB, indicating limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Saranya Nallusamy via figshare

Collection Method

Gas chromatography–mass spectrometry (GC-MS) profiling and computational in silico analysis.

Freshness

Last updated 2026-05-05 07:24:58; freshness should be verified.