Network pharmacology and machine learning nominate PPARG as a candidates target of Aegle marmelos (L.) Correa phytochemicals in breast cancer.

Abstract

Breast cancer remains a leading cause of cancer death in women, and toxicity, tumor heterogeneity and acquired resistance sustain the search for multi-targeted agents of natural origin. Aegle marmelos (L.) Correa is a traditional medicinal species whose molecular targets in breast cancer have not been defined systematically. Filtering 138 reported phytochemicals on drug-likeness, oral bioavailability and predicted toxicity left six leads, whose 252 predicted targets yielded ten hub genes by protein-protein interaction degree. Three classifiers trained on GSE42568 (104 tumor, 17 normal) under nested tenfold cross-validation reached pooled areas under the curve of 0.939-0.974, and their marker sets intersected in PPARG and ERBB2; a composite score adding differential expression, network degree and out-of-fold SHAP importance ranked BCL2 a clear second, with EP300, EGFR and ERBB2 clustered within 0.02 of one another for third, too close to call. All compounds were docked with six targets; marmeline was the strongest lead at four of the six receptors. Molecular dynamics and Hartree-Fock-level quantum-chemical characterization, completed for marmeline at PPARG against its own co-crystallized reference ligand, rosiglitazone, found both complexes stable over 200 ns (backbone RMSD 2.4-2.6 Å) with MM/PBSA binding free energies of -26.5 and -29.6 kcal mol-1, and confirmed marmeline's optimized geometry as a genuine minimum (zero imaginary frequencies; HOMO-LUMO gap 9.97 eV). Together, these findings identify PPARG as the best-supported target by almost every measure and marmeline as a structurally supported lead for experimental validation.

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