Computational identification of natural CXCR4-binding candidates relevant to endometriosis and ovarian cancer progression

Endometriosis and ovarian cancer share invasive, inflammatory, and pro-survival mechanisms in which CXCR4 signaling may play an important role, yet phytochemical modulators of this receptor remain insufficiently characterized. This study addressed that gap by integrating receptor reconstruction, ligand-guided docking, pharmacokinetic and toxicity prediction, pharmacophore mapping, density functional theory, replicated membrane-embedded molecular dynamics, and MM/GBSA analysis. A native human CXCR4 model was generated using SWISS-MODEL with 98.2% template coverage and 100% sequence identity, while the co-crystallized IT1t ligand defined the docking cavity. Eighteen phytochemicals were screened, and naringenin achieved the most favorable predicted docking score (−6.361 kcal/mol), exceeding apigenin (−5.927 kcal/mol) and IT1t (−5.155 kcal/mol). Naringenin formed predicted interactions with Tyr116, Arg188, and Tyr255, showed acceptable drug-likeness, solubility, and gastrointestinal absorption, and displayed a wider HOMO–LUMO gap than apigenin. Two independent 100 ns simulations of the CXCR4 complexes with naringenin, apigenin, and IT1t indicated comparatively consistent structural behavior for naringenin, supported by RMSD, SASA, radius of gyration, hydrogen-bond, PCA, FEL, and DCCM analyses. MM/GBSA estimates were also more favorable for naringenin than apigenin across both replicas. Its predicted LD50 was 2000 mg/kg (toxicity class 4), emphasizing that favorable receptor interactions do not establish safety and require experimental toxicological assessment during further preclinical development. Collectively, naringenin emerged as the most coherent in silico prioritized CXCR4-binding candidate. However, the absence of receptor-binding assays, functional validation, and in vivo confirmation remains a major limitation.