Breast cancer remains a major global health concern, with high incidence and mortality rates among women. Limitations of current chemotherapeutic agents, including resistance and adverse effects, highlight the need for safer, more effective alternatives. In this study, a statistically robust 2D-QSAR model was developed using multiple linear regression (MLR) approach and validated through internal and external statistical metrics such as; R² = 0.951, Q² = 0.921, R²ext = 0.722, cRp² = 0.713, and applicability domain analysis. The model facilitated virtual screening and was utilized for the design of seven novel naphthalene-based tubulin inhibitors. Molecular docking against tubulin target protein (PDB ID: 1SA0) revealed higher predicted binding affinities, particularly for compounds 1d with –142.358 and 1e with –147.636 binding affinities, compared to colchicine (–131.453). Stability and binding strength were further validated through 300-ns molecular dynamics simulations and MM/GBSA calculations, with compound 1e showing a favorable ΔG of –27.96 kcal/mol. Pharmacokinetics and pharmacodynamics profiling confirmed compliance with Lipinski’s rule, good oral bioavailability, low toxicity, and promising drug-like properties. These computational findings suggest that the designed naphthalene derivatives may serve as potential scaffolds for further experimental investigation as tubulin-targeting agents in breast cancer therapy. 

TBA