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Abstract

Glucocorticoids (GCs) coordinate immunity, inflammation, and metabolism through allosteric regulation of the glucocorticoid receptor (GR) transcription factor. GCs are indispensable anti-inflammatory drugs yet linking specific ligand-receptor structural states to specific biological outcomes has remained a major barrier to designing safer, more selective therapies. Using structure-based design, we developed selective glucocorticoid receptor modulators (SGRMs) of immune function by extending a steroidal scaffold from the ligand-binding pocket into an adjacent solvent channel. These SGRMs suppressed T cell pro-inflammatory cytokines and promoted differentiation of memory precursor T cells while showing minimal induction of M2 macrophage polarization or T cell checkpoint proteins PD-1 and CTLA-4, all key targets of immunotherapy. Molecular dynamics simulations revealed that solvent-channel substituents function as a lever arm to drive dynamic oscillations in the steroid core, thereby allosterically tuning GR activity states. Systematic perturbation of immune cells with a graded series of ligands enabled a ligand perturbation with machine learning (LPML) framework to map coregulated responses across cell types and identified effector T cell gene networks tightly coupled with immune checkpoint induction. This approach outlines a general strategy for decoding the logic of allosteric drug action, enabling the rational design of SGRMs with tailored immunomodulatory profiles.

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