Using structure-function information from IFN-γ-binding proteins and biased agonists to uncouple immunostimulatory and immunosuppressive activities

Abstract

IFN-γ is a pleiotropic antiviral cytokine that coordinates innate and adaptive immune responses and induces both immunostimulatory and immunosuppressive activities, limiting its use in the clinic. Due to its antiviral role, several viruses express proteins that bind IFN-γ, blocking its interaction with the IFN-γ receptor (IFNGR). However, varicella zoster virus glycoprotein C binds IFN-γ and induces the expression of a subset of specific ISGs, similar to biased IFN-γ agonists generated based on the crystal structure of the IFN-γ - IFNGR complex. Here, we propose using structural and mechanistic information from viral proteins and biased agonists to design novel IFN-γ agonists that fine-tune IFN-γ - IFNGR activity, reducing the immunosuppressive and toxic effects of this cytokine.

Keywords: IFN-γ; IFN-γ receptor; biased agonist; generative artificial intelligence; viral IFN-binding protein.