In Silico Identification of Rosmarinic Acid as a Putative Natural Product Binder of the PI3Kα Allosteric Site

PIK3CA mutations drive tumorigenesis by activating phosphatidylinositol 3-kinase alpha (PI3Kα). The allosteric inhibitor STX-478 exhibits high selectivity toward PI3Kα and avoids adverse effects such as hyperglycemia. Hyperglycemia is the main reason for the limited clinical application of ATP-competitive PI3Kα inhibitors. To date, no allosteric PI3Kα inhibitors have been approved for clinical use. Consequently, developing novel allosteric PI3Kα inhibitors represents a promising therapeutic strategy for patients harboring PIK3CA mutations. This study establishes a workflow for discovering computationally prioritized allosteric PI3Kα inhibitor candidates, integrating virtual screening, multi-platform druggability evaluation, molecular dynamics simulations, metabolic pathways and metabolites analysis. We used virtual screening to identify computationally prioritized allosteric PI3Kα inhibitor candidates from a small molecule library based on the binding mode between STX-478 and PI3Kα, and further filtered compounds with favorable drug-like properties. Molecular dynamics simulations were carried out to assess the binding stability of these candidates with the protein. We also characterized the metabolic profile of the hit compound. Rosmarinic acid (an ester of caffeic acid and 3,4-dihydroxyphenyllactic acid compound) was screened out as a computationally prioritized allosteric PI3Kα inhibitor candidate. The CDOCKER energy of rosmarinic acid (−69.4529 kcal/mol) in complex with PI3Kα was lower than that of STX-478 (−66.7128 kcal/mol). Molecular dynamics simulations revealed that rosmarinic acid can stably bind to PI3Kα. ADMET prediction suggested that rosmarinic acid possesses favorable safety profiles and acceptable pharmacokinetic properties. This study lays a computational foundation for screening potential allosteric PI3Kα inhibitor candidates.