Abstract
Background: Genetic studies support a key role for RORγ and RORα in the differentiation of proinflammatory Th17 cells, and a growing body of evidence suggests a pathogenic role for Th17 in several autoimmune diseases, including MS, rheumatoid arthritis, inflammatory bowel disease, type I diabetes, and psoriasis. RORγ antagonists have been shown to suppress Th17 differentiation and delay the onset of disease in an experimental autoimmune encephalomyelitis mouse model of MS.
Objective: Given the high therapeutic interest of RORγ antagonists and the promising activity of currently known ligands, small molecules with higher potency and receptor selectivity (in particular within the ROR family) are highly desirable. We used our small molecule compound library to discover, characterize, and optimize novel RORγ antagonists for the treatment of autoimmune diseases from Mixture-based Combinatorial Chemical Libraries.
Methods: We screened the FIU collection of small molecule libraries (>30 million compounds) composed of 75 molecular scaffolds systematically arranged in positional scanning and scaffold ranking formats. We identified scaffolds that selectively inhibit the binding of RORγ, RORγ, and RORβ but not RORα, and others that function as antagonists of all three receptors.
Results: The deconvolution of selected PS-SCL mixtures led to the identification of novel chemical entities, trisubstituted piperazine and diketopiperazine that function as RORγ antagonists.
Conclusion: The screening of a large complex library led to the rapid identification of novel trisubstituted piperazine and diketopiperazine antagonists of the nuclear retinoic acid receptor-related orphan receptor gamma (RORγ).
Graphical Abstract
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