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Designer proteins that competitively inhibit Gαq by targeting its effector site
Authors:Mahmud Hussain  Matthew C Cummins  Stuart Endo-Streeter  John Sondek  Brian Kuhlman
Institution:1.Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill, North Carolina, USA;2.Department of Pharmacology, University of North Carolina, Chapel Hill, North Carolina, USA;3.Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, USA
Abstract:During signal transduction, the G protein, Gαq, binds and activates phospholipase C-β isozymes. Several diseases have been shown to manifest upon constitutively activating mutation of Gαq, such as uveal melanoma. Therefore, methods are needed to directly inhibit Gαq. Previously, we demonstrated that a peptide derived from a helix-turn-helix (HTH) region of PLC-β3 (residues 852–878) binds Gαq with low micromolar affinity and inhibits Gαq by competing with full-length PLC-β isozymes for binding. Since the HTH peptide is unstructured in the absence of Gαq, we hypothesized that embedding the HTH in a folded protein might stabilize the binding-competent conformation and further improve the potency of inhibition. Using the molecular modeling software Rosetta, we searched the Protein Data Bank for proteins with similar HTH structures near their surface. The candidate proteins were computationally docked against Gαq, and their surfaces were redesigned to stabilize this interaction. We then used yeast surface display to affinity mature the designs. The most potent design bound Gαq/i with high affinity in vitro (KD = 18 nM) and inhibited activation of PLC-β isozymes in HEK293 cells. We anticipate that our genetically encoded inhibitor will help interrogate the role of Gαq in healthy and disease model systems. Our work demonstrates that grafting interaction motifs into folded proteins is a powerful approach for generating inhibitors of protein–protein interactions.
Keywords:heterotrimeric G protein    q  Rosetta molecular modeling program  protein design  cancer  molecular modeling  phospholipase C  peptide interaction
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