The phytochemical profiles of leaves and pollen grains' extracts of S. causiarum, S. palmetto and S. yapa were investigated and characterised by LC-HR-MS-based metabolomic analysis. Further, biomarker metabolites were determined using multivariate and clustering analysis. S. causiarum leaves extract along with both S. palmetto and S. yapa pollen grains extracts showed interesting in vitro cytotoxic activity using MTT assay against PC-3 cell lines. While, both S. yapa leaves and pollen grains-derived extracts and S. causiarum pollen grains-derived extracts were active against A-172 cell line. OPLS-DA models was generated, to putatively determine the most active cytotoxic metabolites, these models suggested that alkaloids, flavonoids and phenolic acids are the most important metabolites in the active extracts. In silico analysis (neural-networking-based activity prediction and docking studies) of these top-scoring metabolites further supported OPLS-DA models predictability. This study could be considered as primary step in the in-depth exploration of bioactive natural products from Sabal.
Keywords: Sabal; in silico analysis; Metabolomic; antitumor; docking; multivariate analysis.