Successful in Silico Discovery of Novel Nonsteroidal Ligands for Human Sex Hormone Binding Globulin
Bibliographic record
Abstract
Using "in silico" drug design methodologies, we have discovered several nonsteroidal compounds of natural origin that bind to human sex hormone binding globulin (SHBG) with affinity constants of 0.1 x 10(6) to 1.2 x 10(6) M(-1). The computational solutions we developed involved pharmacophore-aided database search, virtual protein-ligand docking, and structure-activity modeling with "inductive" QSAR descriptors. By screening 23 836 natural substance structures, we identified 29 potential SHBG ligands, and eight of these bound the protein in vitro. These nonsteroidal ligands belong to four classes of molecular scaffolds with several available substitution positions that could allow chemical modification to enhance SHBG-binding activity. Interestingly, one of these compounds is structurally similar to a dicyclohexane derivative that binds to rat SHBG and causes azospermia when administered to male rats. Taken together, the in silico strategy we have developed will aid in the discovery of nonsteroidal ligands of SHBG with novel pharmacological properties.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".