Table 2_GC–MS metabolomic profiling and PPARγ-targeted in silico approaches for identifyin

561 compounds were identified via gas chromatography–mass spectrometry (GC–MS) from six traditional rice varieties. The dataset includes results from network analysis, ADMET prediction, and virtual screening against the PPARγ protein, identifying oleic acid as a promising compound. Authored by Saranya Nallusamy and last updated on 2026-05-05, the data is shared under a CC-BY-4.0 license.

Use Cases

• Virtual screening of natural compounds against PPARγ based on molecular docking scores
• Comparative metabolomic analysis of bioactive compounds across traditional rice varieties
• Predicting ADMET properties for candidate anti-diabetic compounds
• Validating molecular dynamics simulation stability for protein-ligand complexes

Strengths

• Identifies 561 distinct compounds from six rice varieties using GC–MS
• Includes specific docking scores and binding free energy values for oleic acid and pioglitazone
• Results are based on a 200 ns molecular dynamics simulation for stability analysis

Limitations

• Dataset size is only 21.7 KB, indicating very 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

figshare

Collection Method

Metabolic profiling via GC–MS followed by computational analysis including network/pathway enrichment, ADMET prediction, molecular docking, and molecular dynamics simulation.

Freshness

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