Evolutionary‑Driven Bayesian Optimization for Automated Molecular Docking with AutoDock Vina
This work introduces Evolutionary Driven Bayesian Optimization (EA-BO), a surrogate-based framework designed for efficient exploration under strict evaluation budgets and demonstrates that EA-BO provides data-efficient strategy for locating promising docking regions when computational cost limit traditional approaches.