Abstract

Abstract Biologics targeting multiple pathways and/or multiple cell types simultaneously have the potential to restore normal immune homeostasis. Inhibitory checkpoint receptor agonism by antibodies benefits from higher order clustering for strong activation, which can be achieved by antibody Fc binding to Fc gamma receptors (FcγRs). However, many of the current agonist antibodies non discriminately bind activating FcγRs. This has the potential to trigger inflammatory cytokines by antigen presenting cells (APCs) or cause antibody dependent cellular cytotoxicity (ADCC). Clustering by Fc binding to the inhibitory Fc receptor, FcγRIIb has the potential to provide superior clustering by avoiding inflammatory cytokine responses and limiting APC activation. However, FcγRIIb is 93% homologous to the activating receptor FcγRIIa, and designing molecules that specifically bind FcγRIIb presents a challenge that our IMPACT platform can address. Using integrated machine learning, structural biology and traditional antibody campaigns, we have identified selective FcγRIIb binding molecules, and characterized their potential for IMPACTing immune-mediated diseases.

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