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Cited by 599

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Evolution of Hormone-Receptor Complexity by Molecular Exploitation

Bridgham, Jamie T., Carroll, Sean M., Thornton, Joseph W.·2006·Science

Abstract

According to Darwinian theory, complexity evolves by a stepwise process of elaboration and optimization under natural selection. Biological systems composed of tightly integrated parts seem to challenge this view, because it is not obvious how any element's function can be selected for unless the partners with which it interacts are already present. Here we demonstrate how an integrated molecular system—the specific functional interaction between the steroid hormone aldosterone and its partner the mineralocorticoid receptor—evolved by a stepwise Darwinian process. Using ancestral gene resurrection, we show that, long before the hormone evolved, the receptor's affinity for aldosterone was present as a structural by-product of its partnership with chemically similar, more ancient ligands. Introducing two amino acid changes into the ancestral sequence recapitulates the evolution of present-day receptor specificity. Our results indicate that tight interactions can evolve by molecular exploitation—recruitment of an older molecule, previously constrained for a different role, into a new functional complex.

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Crossref · 10.1126/science.1123348

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Metadata

Authors
Bridgham, J. T., Carroll, S. M., & Thornton, J. W.
Venue
Science
Published
2006-04-07
Volume
312
Issue
5770
Pages
97-101
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2123653059
Cited by
599
References
3
FWCI
23.33
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Evolution of Hormone-Receptor Complexity by Molecular Exploitation. https://app.cochat.ai/papers/10.1126/science.1123348
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Bridgham, J. T., Carroll, S. M., & Thornton, J. W. (2006). Evolution of Hormone-Receptor Complexity by Molecular Exploitation. Science. https://doi.org/10.1126/science.1123348

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.