In Silico Screening of Annona Metabolites Against CYP17A1 and β-tubulin Using PLANTS Docking

Prostate cancer progression is closely associated with androgen biosynthesis mediated by cytochrome P450 17A1 (CYP17A1) and with microtubule dynamics regulated by β-tubulin, making both proteins important therapeutic targets. The Annona genus is a rich source of acetogenins with reported anticancer potential; however, their interactions with prostate cancer–related targets remain insufficiently explored. In this study, an in silico exploratory approach was employed to evaluate 30 Annona-derived compounds against CYP17A1 (PDB ID: 3RUK) and β-tubulin (PDB ID: 1JFF) using the PLANTS (v1.1) molecular docking program. Docking protocol validation was based on RMSD values ≤ 2 Å, and compound prioritization was performed using docking scores and binding-site residue similarity relative to native ligands and reference drugs. The docking results identified squafosacin-C as the top-ranked compound for both targets, exhibiting docking scores of −133.289 for CYP17A1 and −131.825 for β-tubulin. These values were more favorable than those of the native ligands (−82.5591 and −103.071) and the reference drugs abiraterone and docetaxel (−83.6465 and −99.7319, respectively). Visualization analysis further revealed that squafosacin-C shares 7 of 8 key amino acid residues involved in native ligand binding at both targets, indicating a conserved binding mode. In conclusion, based on molecular docking and interaction analysis, squafosacin-C emerges as a promising lead compound at the computational level for targeting CYP17A1 and β-tubulin in prostate cancer. These findings provide a rationale for further investigation through molecular dynamics simulations and experimental validation to confirm its biological activity.