Use of P450 Enzymes for Late-Stage Functionalization in Drug Discovery
Bibliographic record
Abstract
Abstract Herein, we demonstrate the use of a commercially available enzymatic kit to achieve late-stage hydroxylation of biologically relevant compounds by using the PolyCYPs screening kit. A selection of promising biotransformations were scaled up, products isolated, and structures elucidated. Isolated compounds were screened against a range of pathogens, namely, Schistosoma mansoni, Leishmania donovani, Trypanosoma cruzi, and Trypanosoma brucei to obtain biological data. This approach has allowed data generation more efficiently than the chemical synthesis of the same molecules. Importantly, it has been demonstrated that production of hits of interest can also be scaled up to enable further study. We also demonstrate the biosynthetic synthesis of a lead compound in fewer steps than using standard synthetic chemistry, offering faster access to compounds for screening or further transformation. This approach has the potential to save time and resources in a drug discovery program, by reducing the necessity to synthesize late-stage intermediates and develop new chemistry.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".