(2) Because constructing the HNSW data structure involves only the virtual chemical library, it is agnostic to specific protein binding pockets. Consequently, screening multiple protein targets does not incur additional computational overhead. Our method solely focuses on relating ligands' biological activity, measured by docking score, to their organization based on similarity, akin to many previous methods. This contrasts sharply with the active learning approach, which requires developing and tuning individual models for each binding pocket.