Dual-mechanism estrogen receptor inhibitors.

Efforts to improve estrogen receptor-α (ER)-targeted therapies in breast cancer have relied upon a single mechanism, with ligands having a single side chain on the ligand core that extends outward to determine antagonism of breast cancer growth. Here, we describe inhibitors with two ER-targeting moieties, one of which uses an alternate structural mechanism to generate full antagonism, freeing the side chain to independently determine other critical properties of the ligands. By combining two molecular targeting approaches into a single ER ligand, we have generated antiestrogens that function through new mechanisms and structural paradigms to achieve antagonism. These dual-mechanism ER inhibitors (DMERIs) cause alternate, noncanonical structural perturbations of the receptor ligand-binding domain (LBD) to antagonize proliferation in ER-positive breast cancer cells and in allele-specific resistance models. Our structural analyses with DMERIs highlight marked differences from current standard-of-care, single-mechanism antiestrogens. These findings uncover an enhanced flexibility of the ER LBD through which it can access nonconsensus conformational modes in response to DMERI binding, broadly and effectively suppressing ER activity.

Chemical systems biology reveals mechanisms of glucocorticoid receptor signaling.

Glucocorticoids display remarkable anti-inflammatory activity, but their use is limited by on-target adverse effects including insulin resistance and skeletal muscle atrophy. We used a chemical systems biology approach, ligand class analysis, to examine ligands designed to modulate glucocorticoid receptor activity through distinct structural mechanisms. These ligands displayed diverse activity profiles, providing the variance required to identify target genes and coregulator interactions that were highly predictive of their effects on myocyte glucose disposal and protein balance. Their anti-inflammatory effects were linked to glucose disposal but not muscle atrophy. This approach also predicted selective modulation in vivo, identifying compounds that were muscle-sparing or anabolic for protein balance and mitochondrial potential. Ligand class analysis defined the mechanistic links between the ligand-receptor interface and ligand-driven physiological outcomes, a general approach that can be applied to any ligand-regulated allosteric signaling system.