In silico Evaluation of Pergularia daemia Steroidal Lactone Phytochemicals as Potential Multi-Target Modulators of PIK3CA and STAT3 Signaling Pathways in Pancreatic Cancer

Background

Pancreatic cancer remains a lethal disease, largely because of its aggressive biology and scant therapeutic options. Central to its progression are dysregulated oncogenic pathways-most notably PI3K/AKT/mTOR and STAT3, which drive tumor growth, survival, and resistance to therapy. Natural products, with their ability to target multiple nodes in these networks, offer a promising source of novel anticancer agents.

Objectives

Here we investigated a set of steroidal lactone phytochemicals isolated from Pergularia daemia for their potential interactions with key pancreatic cancer associated targets.

Materials and Methods

Five compounds-Calotropin, Calactin, Calotropagenin, Coroglaucinin, and Corotoxigenin-were screened using an integrative network-pharmacology pipeline. SwissTargetPrediction identified 45 putative targets, and pathway enrichment (KEGG and GO) highlighted a strong signal for the pancreatic cancer pathway (9 genes, fold enrichment ≈ 150, -log10 FDR ≈ 12). The PI3K/AKT/mTOR axis emerged as the most enriched network. Drug-likeness and pharmacokinetic predictions (Swiss ADME) confirmed favorable ADME profiles, with high gastrointestinal absorption and low predicted toxicity. Molecular docking against six pancreatic-cancer-associated proteins (PIK3CA, STAT3, AKT1, EGFR, mTOR, BRAF) using SwissDock revealed favorable predicted binding affinities (-4.84 to -8.87 kcal mol⁻¹).

Results

Calotropagenin and Coroglaucinin showed the strongest interactions with PIK3CA (-8.87 and -8.81 kcal mol⁻¹, respectively), while Calactin and Calotropin showed favorable docking interactions with STAT3 (-7.65 and -7.44 kcal mol⁻¹).

Conclusion

Collectively, these findings suggest that steroidal lactones from Pergularia daemia may exhibit potential multi-target interactions with pancreatic cancer-associated proteins particularly within the PI3K/AKT/mTOR and STAT3 signaling pathways. However, these findings are based on computational predictions and require further experimental validation.