Synthetic Opportunities and Challenges for Macrocyclic Kinase Inhibitors
Bibliographic record
Abstract
Macrocycles are typically cyclic variants of inhibitors derived from uncyclized canonical molecules or from natural products. For medicinal chemistry, drug-like macrocycles have received increasing interest over the past few years, since it has been demonstrated that macrocyclization can favorably alter the biological and physiochemical properties as well as selectivity in comparison to the acyclic analogue. Recent drug approvals such as Lorlatinib, glecaprevir, or voxilaprevir underline the clinical relevance of drug-like macrocycles. However, the synthesis of drug-like macrocycles can be challenging, since the ring-closing reaction is generally challenging with yields depending on the size and geometry of the bridging linker. Nevertheless, macrocycles are one opportunity to expand the synthetic toolbox for medicinal chemistry to provide bioactive molecules. Therefore, we reviewed the past literature of drug-like macrocycles highlighting reactions that have been successfully used for the macrocyclization. We classified the cyclization reactions by their type, ring-size, yield, and macrocyclization efficiency index.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".