Finally, the use of the lowest RMSD pose vs. the best score pose does not make a substantial difference in ranking the relative strength of binding for a ligand to a single protein of interest, allowing one to use the relatively inexpensive semi-flexible method for the generation of ligand poses. We believe that the release of this code under the GPL license will give the community a valuable tool for generating chemically relevant ligand poses for use in drug discovery efforts as the codebase is developed in a modular manner so that it can be embedded in drug-design pipelines. Ligand fragments from the previous step are translated and rotated within this grid to produce a collection of the same ligand fragment throughout the binding site (d). This collection of ligand fragments is clustered using a greedy clustering algorithm using RMSD to determine if two fragments are similar. If two fragments are within a 2.0A of each other, the fragment with a higher RMR6 is deleted. Remaining docked fragments are referred to as seeds (e). The score distribution of a typical seed is given in (f) to show the exponential score shape of the distribution. given in gray and cyan respectively showing that the energy minization moved the zinc ion considerably. The complexes in (c) and (d) show the interactions between sulfonyl amide groups and a zinc ion. The interactions of a compound with a heme group via a nitrogen lone pair is shown in (e) and the interaction of an aromatic carbon with a heme group is given in (f). Finally, panels (g) and (h) show the interactions of compounds with other cofactors, such as a π-π interaction of a compound with flavin-adenine dinucleotide and interaction of a compound with zinc and magnesium in a binding pocket.