We will now present a demonstration of HiMap clustering and design optimization using inhibitory ligands of the enzyme 𝛽-secretase 1, BACE1. The first step in HiMap is to calculate the similarity scores of the BACE1 ligands, where 𝑛 = 75 (Fig. ). For similarity scores, we used LOMAP 2.0 scoring which is the default in HiMap (Software Methods). Subsequently, to cluster the ligands, we used a neighbor distance cutoff of 0.4 which produced three distinct clusters, {𝑑 𝑖 |0 ≤ 𝑖 ≤ 2}. HiMap clustering results in the division of ligands into logical groupings, based on difficulty of alchemical transformations. To illustrate this, macrocycle ligands are in cluster 𝑑 0 , ligands with a six-member ring attached to a N-Phenyl-pyridine-2-carboxamide scaffold are in cluster 𝑑 1 , and ligands with an additional five-member ring fused to the 𝑑 1 scaffold are in cluster 𝑑 2 (Fig. ). The chemical structures of the ligands which are most similar to each cluster -lig_09, lig_22, and lig_76 -highlight the differences between the clusters detected by HiMap (Fig. ). Due to ring breaking and opening, transformations between the clusters of BACE1 ligands would be challenging to perform with many RBFE methods.