This study introduces a new way to navigate chemical space using hierarchical navigable small worlds (HNSW), a hierarchical graph-based data structure and algorithm designed for approximate nearest neighbor (ANN) search within high dimensional spaces. Although HNSW has predominantly served as the foundation for vector databases powering retrieval augmented generation (RAG), we leverage HNSW to structure virtual chemical libraries. Instead of following a conventional ANN search, we implement a greedy algorithm to traverse and dock the molecules within the graph's underlying structure in a process we call retrieval augmented docking (RAD).