Computational Pharmacology Towards RGS12 Inhibitors
Background/Introduction: "Regulator of G protein Signaling" proteins, also referred to as RGS proteins, inhibit signal transduction by accelerating the hydrolysis of guanosine triphophate (GTP) to guanosine diphosphate (GDP) on the G-alpha subunit of G protein-coupled receptors (GPCRs). Sequence variations of RGS12, which is a member of the RGS protein superfamily, have been observed in some genetic profiles of people with attention-deficit hyperactivity disorder (ADHD), bipolar disorder, and schizophrenia. Hence the purpose of this study was to perform an in silico exploration of the structure/function correlation of small molecule inhibitors of the RGS12 RGS-box domain predicted to inhibit RGS12. Using these small molecule inhibitors in the mouse or rat brain would provide information on whether inhibition of RGS12 can lead to brain changes and/or behavioral changes similar to the human mental health disorders of ADHD, bipolar disorder, or schizophrenia. Method: In silico visualization and exploration of predicted small molecule inhibitors of the RGS box of RGS proteins were evaluated using the Schrodinger software suite (version 2020-3). Ninety-six predicted inhibitors underwent ligand preparation (e.g., tautomer resolution) and Glide docking within structural models of RGS4, RGS12 and RGS14. The resulting ligand and receptor interactions were quantified using Schrodinger Maestro (2020-3). In parallel, all 96 compounds were sent to BellBrook Labs for in vitro testing of GAP inhibitory activity. Results: Three compounds Z##6112, Z##0043, and Z##6197 with shared chemical features, i.e., thioether linkages, and linked sulfur and nitrogen heteroatoms, were observed to inhibit RGS12's GAP activity at least three standard deviations away from the average assay signal. Two unique features of the Z##6197 compound, a carboxylic acid group and a halogenated, ether-coupled phenolic ring, were found to inhibit in silico Glide docking or be docked in varied poses with differing chemical-bond engagements within the RGS-box receptor grids, respectively. Conclusions: Discrepancies between the in silico Glide docking and in vitro biochemical results bring into question the validity of the Glide algorithm to correctly predict the geometry and chemical-bonding character of RGS-box / small molecule inhibitor engagement. Further testing of the three identified compounds in other in vitro assays and in establishing three-dimensional structural models of their RGS-box engagement will assist in resolving these discrepancies and reveal both shared and unique determinants of RGS12 inhibition necessary for future in vivo and clinical applications.