Structure of the LBD of rat VDR in complex with a non-<i>seco</i>-steroidal vitamin D3 analogue YR301
Bibliographic record
Abstract
Glutathione S-transferase (GST) is a superfamily of detoxification enzymes, represented by GSTa, GSTm, GSTp, etc. GSTa is the predominant isoform of GST in human liver, playing important roles for our well being.GSTp is overexpressed in many forms of cancer, thus presenting an opportunity for selective targeting of cancer cells.Our structure-based design of prodrugs intended to release cytotoxic levels of nitric oxide in GSTp-overexpressing cancer cells yielded PABA/NO, which exhibited anticancer activity both in vitro and in vivo with a potency similar to that of cisplatin (Findlay et al.Mol.Pharmacol.2004, 65, 1070-1079).Here, we present the details on structural modification, molecular modeling, and enzymatic characterization for the design of PABA/NO.The design was efficient because it was on the basis of the reaction mechanism and the structures of related GST isozymes at both the ground state and the transition state.The ground-state structures outlined the shape and property of the substrate-binding site in different isozymes, and the structural information at the transition-state indicated distinct conformations of the Meisenheimer complex of lead compounds in the active site of different isozymes, providing guidance for the modifications of the molecular structure of lead molecules.Two key alterations of a GSTa-selective compound led to the GSTp-selective PABA/NO.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".