How estrogen‐specific proteins discriminate estrogens from androgens: A common steroid‐binding site architecture
Bibliographic record
Abstract
Steroid hormones play an essential role in a wide range of physiological and pathological processes, such as growth, metabolism, aging, and hormone-sensitive cancers. Estrogens are no exception and influence growth, differentiation, and functioning of many target tissues, such as the mammary gland, uterus, hypothalamus, pituitary, bone, and liver. Although very similar in structure, each steroid class (i.e., estrogens, androgens, progestins, mineral corticoids, or glucocorticoids) is responsible for distinct physiological processes. To permit specific biological responses for a given steroid class, specific proteins are responsible for steroid bioactivation, action, and inactivation, yet they have low or no affinity to other classes. Estrogens make no exception and possess their own set of related proteins. To understand the molecular basis underlying estrogen recognition from other steroids, structural features of estrogen-specific proteins were analyzed along with their ability to discriminate between steroid hormones belonging to different classes. Hence, the study of all estrogen-specific proteins for which an atomic structure has been determined demonstrated that a common steroid-binding pocket architecture is shared by these proteins. This architecture is composed of the following elements: i) a glutamate residue acting as a proton acceptor coupled with a proton donor that interact with the steroid O3; ii) a proton donor (His or Ser) that interacts with O17; iii) a highly conserved sandwich-like structure providing steric hindrance and preventing C19 steroid from binding; and iv) several amino acid residues interacting with the C18. As these different estrogen-specific proteins are not related in overall sequence, the inference is that the steroid binding site in these proteins has originated by convergent evolution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".