Yun Lyan Luo

Docking-score landscapes shape active-learning performance across Vina, Glide, and SILCS

The rapid expansion of large chemical libraries has created a need for virtual screening workflows that are both efficient and accurate. Active learning (AL) offers a scalable strategy by iteratively training surrogate models to prioritize promising compounds and reduce the number of required docking calculations. Howe...