As a transcription factor of T helper 17 cells, human retinoic acid receptor-related orphan receptor γ (RORγ) plays a crucial role in controlling the expression of pro-inflammatory cytokine IL-17. Since the overexpression of IL-17 can lead to various autoimmune disorders, such as Psoriasis, Crohn’s disease, and Ankylosing Spondylitis, RORγ has drawn the attention of scientists to its potential as a drug target. It is known that when an inverse agonist binds to the ligand-binding domain (LBD) of RORγ, the transcriptional function of RORγ is down-regulated, and IL-17 expression is suppressed. Accordingly, drugs targeting RORγ LBD will offer a strategy to treat autoimmune diseases. Compared with classic laboratory-based drug discovery, computer-aided drug discovery can dramatically improve efficiency and save costs of the initial ligand screening. In this project, we virtually screened a ligand-like compound library by iDock, a computer program docking every compound against the LBD. The performance of the compounds in the binding pocket was ranked based on iDock-predicted free energy, ligand efficiency, RF-Score, and hydrogen bonds. Approximately 1000 top-rated hits were structurally compared with the known inverse agonists by DataWarrior. About 100 hits with unique chemical structures were selected, and their bioactivity was tested <i>via</i> reporter gene assay. Two compounds RG14 and RG14-2, analog to each other, inhibited the RORγ transcriptional activity with IC<sub>50</sub> values at 3.2 µM and 1.5 µM, respectively. To further study the atomic interactions between the compounds and the protein, purified RORγ LBD was prepared in our lab. Binding affinities of RG14 and RG14-2 to the LBD are under investigation by thermal shift assay. By solving crystal structures of the protein-ligand complexes, we will obtain structural information to interpret the impact of the ligands on the protein. RORγ LBD will be mutated to explore the amino acid residues contributing to the binding. A novel lead compound of RORγ inverse agonists is expected to develop from the scaffold of RG14 and RG14-2 and their binding modes to RORγ LBD.

Computer-aided discovery of novel human RORγ inverse agonists

ACS Spring Meeting 2021

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