The nuclear receptor (NR) superfamily of ligand-regulated transcription factors has proven to be an excellent target for therapeutic intervention of a broad range of diseases. REV-ERBs, TLX and ERRs are members of the NR superfamily and play important roles in the etiology of metabolic disorders, skeletal muscle related disorders, and neurodegenerative diseases. However limited availability of structural information about these receptors hampered the different efforts for the discovery of novel modulators that can be used as chemical probes or as hits in drug discovery campaigns. We used combined approaches of homology modelling, conventional and enhanced molecular simulations to investigate receptor conformations associated with ligand binding. Predicted ligand binding poses generated by molecular simulations were validated using mutagenesis studies. Employing structure-based virtual screening targeting different ensembles, several nanomolar modulators targeting all three receptors were identified and verified using cell-based functional assays. The identified modulators will serve as chemical probes to further probe the function of these receptors in different disease models which is important step towards the discovery of improved and novel therapeutics. This research highlights the importance of using computational approaches for acceleration of drug discovery and biomedical research.

Discovery of novel modulators of nuclear hormone receptors using combined approaches of molecular simulations and structure-based virtual screening

ACS Spring Meeting 2021

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