Abstract

Overexpression of pro‐inflammatory cytokine IL‐17 can lead to various autoimmune disorders, including psoriasis, Crohn’s disease, and Ankylosing Spondylitis. However, when an inverse agonist binds to the ligand‐binding domain (LBD) of human retinoic acid receptor‐related orphan receptor γ (RORγ), the transcriptional function of RORγ is down‐regulated, resulting in diminished IL‐17 expression. It makes RORγ an ideal drug target for treating autoimmune diseases. This has been studied for over ten years, but only several RORγinverse agonists are under clinical trials. New methods may be needed to develop new drugs efficiently. In this project, we aim to discover potential RORγ inverse agonists by developing a structure‐based virtual screening method that effectively screens millions of compounds in a shorter time scale. We here applied the in silico program iDock to screen a ligand‐like compound library by docking every compound into the binding pocket of RORγ LBD. iDock evaluated the performance of each compound in the pocket and outputted the top 1000 hits. Through excluding the hits structurally similar to the known RORγ inverse agonists, we focused on the ones with unique chemical scaffolds and tested their bioactivity via luciferase reporter assay. A family of compounds sharing the same backbone was found. Two members in this family, RG14 and RG14‐2, inhibited the RORγ transcriptional function with IC50 values at 3.2 μM and 1.5 μM, respectively. To further study the interactions between the compounds and the protein, binding affinities of RG14 and RG14‐2 to the LBD are under investigation by thermal shift assay. RORγ LBD has been successfully co‐crystallized with RG14 and RG14‐2. With solving crystal structures of the protein‐ligand complexes, we will obtain more information to interpret the interactions structurally. A lead compound of a novel class of RORγ inverse agonists is expected to develop, basing on the chemical structures of RG14 and RG14‐2 and their binding actions to RORγ LBD.Support or Funding InformationNSF 1833181

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