3.3.2. Molecular Docking of Compounds 1–3

Self-docking was used to validate the docking protocol, as well as to determine the protein structure’s suitability to successfully dock the native ligand. The native ligand, 4YQ, was docked using the following docking parameters: placement: triangle matcher, placement score algorithm: London dG, returned poses: 100, refinement: induced fit, iterations: 1000, refinement score algorithm: GBVI/WSA dG, and scored poses: 5. The free energy of binding of the ligand molecule was estimated using the force field-based scoring function (GBVI/WSA) with the implicit solvent model. The implicit solvent model, however, does have its limitations, as it under- or overestimates the strength of the solvation binding free energy of water-solvation hydrogen bonds, resulting in varying binding free energy scores. However, even though the scores can be influenced by the inclusion of crystallographic waters, previous studies have shown that the inclusion of these waters increases docking pose accuracy [50,73,74,75]. Furthermore, previous studies have shown that there is minimal statistical significance between binding affinity scores and experimentally determined ligand affinities to their respective targets [73]. Therefore, we considered the accuracy of the docked binding pose to be more important than the influenced docking scores caused by the crystallographic waters.

The successfulness of the docked ligands was determined using a root mean squared deviation (RMSD)-based criteria between the docked 4YQ and the crystallographic 4YQ. A RMSD value of <2 Å for both the top pose (lowest binding affinity score pose) and average RMSD across the top five docked poses, was used to validate the ability of the docking protocol to predict realistic binding conformations and interactions. The self-docked 4YQ top pose obtained an RMSD of 1.65 Å, and an average RMSD over the top five poses of 1.33 Å. Therefore, the validated molecular docking protocol was employed in this study. Test compounds 1–3 were imported into a combined database, and were docked using the validated docking protocol. The best docked ligand conformation of each compound was selected using the following criteria: lowest binding affinity score within the top five binding conformations, and best interactions with important 11β-HSD1 active site residues. The best binding pose of each compound was visually inspected, and the interactions with the binding pocket residues were analyzed using the online servers Protein-Ligand Interaction Profiler (PLIP, https://plip-tool.biotec.tu-dresden.de, accessed on 10 December 2021) [76], Analysis of Protein-Ligand Interactions (nAPOLI, http://bioinfo.dcc.ufmg.br/napoli/, accessed on 10 December 2021) [77], Pymol molecular graphics system [78], and the MOE 2020 software suite [70]. The nAPOLI binding interaction analysis tool parameters were set to default, except for the hydrogen bond parameters: maximum donor atom to acceptor atom distance, and maximum donor to hydrogen distance were set to 4.1 Å and 3.5 Å, respectively. The nAPOLI hydrogen bond parameters were altered to correlate with the PLIP hydrogen bond parameters. The built-in scoring function of MOE, S-score, was used to predict the binding affinity (kcal/mol) of each ligand with the protein active site after docking.