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A methodology for creating mutants of G‐protein coupled receptors stabilized in active state by combining statistical thermodynamics and evolutionary molecular engineering

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We challenged the stabilization of a G‐protein coupled receptor (GPCR) in the active state solely by multiple amino‐acid mutations without the agonist binding. For many GPCRs, the free energy of… Click to show full abstract

We challenged the stabilization of a G‐protein coupled receptor (GPCR) in the active state solely by multiple amino‐acid mutations without the agonist binding. For many GPCRs, the free energy of the active state is higher than that of the inactive state. When the inactive state is stabilized through the lowering of its free energy, the apparent midpoint temperature of thermal denaturation Tm exhibits a significant increase. However, this is not always the case for the stabilization of the active state. We constructed a modified version of our methodology combining statistical thermodynamics and evolutionary molecular engineering, which was recently developed for the inactive state. First, several residues to be mutated are determined using our statistical‐thermodynamics theory. Second, a gene (mutant) library is constructed using Escherichia coli cells to efficiently explore most of the mutational space. Third, for the mutant screening, the mutants prepared in accordance with the library are expressed in engineered Saccharomyces cerevisiae YB14 cells which can grow only when a GPCR mutant stabilized in the active state has signaling function. For the adenosine A2A receptor tested, the methodology enabled us to sort out two triple mutants and a double mutant. It was experimentally corroborated that all the mutants exhibit much higher binding affinity for G protein than the wild type. Analyses indicated that the mutations make the structural characteristics shift toward those of the active state. However, only slight increases in Tm resulted from the mutations, suggesting the unsuitability of Tm to the stability measure for the active state.

Keywords: statistical thermodynamics; state; methodology; active state; protein

Journal Title: Protein Science
Year Published: 2022

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