We used openmoltools (v0.8.1) 35 and OpenEye toolkits 36 to convert each ligand SMILES string to a 3D structure and then we assigned charges using the OEAM1BCC. 36,37 charging scheme from the OEQUAPAC library. . Then, we generated 1000 conformers of each charged ligand using OpenEye's OMEGA (20180212). These conformers were then docked into the SEH apo protein structure using FRED from OEDock(v3.2.0.2), generating 1000 docked poses, and scored with the Chemgauss4 scoring function. From the 1000 generated docked poses, we wanted to select the most distinct and use them as our starting positions for our simulations. Here, we define distinct docked poses as poses which are dissimilar from one another. Some studies have shown that docking is an unreliable method for identifying the true binding mode using the top scoring pose. Given Figure : 2D representation of molecules used in this study and their identifying label.. this, we believed that the top scoring poses would often be far from the true binding mode and thus, we did not retain them and use them as starting points for our MD simulations to ensure broad coverage of possible binding modes/sites. This was done without utilizing experimental binding modes. In analysis after our calculations, we confirmed that the top scoring docked poses are not generally close to the crystallographic binding modes (Fig. ).