Pharmacophore Modeling, Virtual Screening and in Silico ADMET Analysis of Phenylpropanoid and Eugenol Derivatives as B-cell CLL/Lymphoma 2 (BCL-2) Inhibitors

Background: Bcl-2 family proteins regulate apoptosis, and their overexpression is linked to cancer progression and therapy resistance. Targeting Bcl-2 with novel inhibitors is a promising approach for anticancer drug development. Methods: Pharmacophore modeling was performed using a training set of 5 diverse Bcl-2 inhibitors with IC₅0 values ranging from 0. 00012 to 3. 37µM. Ten pharmacophore models were generated and validated using receiver operating characteristic (ROC) curves, enrichment factor (EF), and Güner-Henry (GH) scoring with a test set containing 24 active compounds and 1309 decoys. Model 8 demonstrated the best performance (AUC = 0. 83, EF₁% = 3. 66, GH score = 0. 58) and was used for virtual screening of 220 eugenol derivatives. Docking studies were conducted using AutoDock against Bcl-2 crystal structure (PDB ID: 4LXD), and in silico ADMET analysis assessed pharmacokinetic and toxicity profiles. Results: Model 8 effectively distinguished active Bcl-2 inhibitors with good sensitivity and selectivity. Virtual screening identified 24 eugenol derivatives with high pharmacophore fit scores (>45), among which compounds 57, 57', 71 and 91 exhibited favorable docking binding energies ranging from -5. 11 to -7. 35kcal/mol compare with ABT-263 with value -9. 82kcal/mol, overlapping well with the binding site of known inhibitor navitoclax. In silico ADMET profiling predicted good solubility, partition coefficients, and low toxicity risks, supporting their drug-likeness. Conclusion: The integrated pharmacophore and docking approach successfully identified promising eugenol derivative candidates as potential Bcl-2 inhibitors. These compounds demonstrate favorable binding affinity and pharmacokinetic properties, meriting further experimental validation and development as anticancer agents. Future work should include molecular dynamics simulations and in vitro bioactivity assays to confirm and optimize these leads.