Systems Structural Biology Analysis of Ligand Effects on ERα Predicts Cellular Response to Environmental Estrogens and Anti-hormone Therapies.

TitleSystems Structural Biology Analysis of Ligand Effects on ERα Predicts Cellular Response to Environmental Estrogens and Anti-hormone Therapies.
Publication TypeJournal Article
Year of Publication2017
AuthorsNwachukwu JC, Srinivasan S, Bruno NE, Nowak J, Wright NJ, Minutolo F, Rangarajan ES, Izard T, Yao X-Q, Grant BJ, Kojetin DJ, Elemento O, Katzenellenbogen JA, Nettles KW
JournalCell Chem Biol
Volume24
Issue1
Pagination35-45
Date Published2017 Jan 19
ISSN2451-9448
KeywordsAntineoplastic Agents, Hormonal, Breast Neoplasms, Cell Proliferation, Crystallography, X-Ray, Dimerization, Dose-Response Relationship, Drug, Drug Screening Assays, Antitumor, Estrogen Antagonists, Estrogen Receptor alpha, Estrogens, Female, Humans, Ligands, Models, Molecular, Protein Conformation, Structure-Activity Relationship, Tumor Cells, Cultured
Abstract

Environmental estrogens and anti-hormone therapies for breast cancer have diverse tissue- and signaling-pathway-selective outcomes, but how estrogen receptor alpha (ERα) mediates this phenotypic diversity is poorly understood. We implemented a statistical approach to allow unbiased, parallel analyses of multiple crystal structures, and identified subtle perturbations of ERα structure by different synthetic and environmental estrogens. Many of these perturbations were in the sub-Å range, within the noise of the individual structures, but contributed significantly to the activities of synthetic and environmental estrogens. Combining structural perturbation data from many structures with quantitative cellular activity profiles of the ligands enabled identification of structural rules for ligand-specific allosteric signaling-predicting activity from structure. This approach provides a framework for understanding the diverse effects of environmental estrogens and for guiding iterative medicinal chemistry efforts to generate improved breast cancer therapies, an approach that can be applied to understanding other ligand-regulated allosteric signaling pathways.

DOI10.1016/j.chembiol.2016.11.014
Alternate JournalCell Chem Biol
PubMed ID28042045
Grant ListR01 GM114420 / GM / NIGMS NIH HHS / United States