The RMSD cutoff, number of features to use, and clustering cutoffs are left to the user to adjust based on the specific system. The number of features should be sufficiently large to encompass important and diverse pairs but not excessively high, as Euclidean distances used in regular space clustering become less informative with increasing dimensionality. It is recommended to select roughly the top 5% of all features, not exceeding a few hundred. The distance cutoff used in clustering determines the number of clusters identified. Depending on computational resources available, selecting 5 to 20 cluster centers is generally recommended.