Crystallogenesis of Steroid-Converting Enzymes and Their Complexes: Enzyme–Ligand Interaction Studies and Inhibitor Design Facilitated by Complex Structures
Why this work is in the frame
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Bibliographic record
Abstract
Crystal growth of steroid enzymes in complex with hydrophobic ligands is hindered by the low solubility of both partners. However, their interaction can promote highly soluble complexes, leading to well diffracting crystals and high-quality structures. The moderate amphiphilic property of polyethylene glycol increases steroid solubility and facilitates complex formation, but altered orders of soaking can lead to a variety of complex formations and different structures. Understanding the latter mechanism is important for inhibitor design. Thus, different enzyme–ligand complex structures have provided detailed pictures of steroid alternative binding and multispecificity of the enzymes, as, for example, in the case of human 17β-hydroxysteroid dehydrogenases (17β-HSD) type 1 due to C19 steroid pseudosymmetry or in human 17β-HSD type 5 due to the spatial binding site. These complex structures also provide insights into the dynamics of the enzyme binding and catalytic process. Hybrid inhibitors constituted by the steroid and adenine cores of the native substrate and cofactor can properly occupy their original binding sites in 17β-HSD1, leading to an inhibition constant at the nanomolar level. Altered complex crystallization and even a modified order of soaking may result in different complex structures, shedding light on detailed protein–ligand interactions as well as on the enzyme reaction mechanism. These results highlight the important contribution and high significance of the crystal growth mechanism to protein structure determination and function study, as well as to drug design for medicinal applications.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it