Natural Products in Medicine: Transformational Outcome of Synthetic Chemistry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This review brings to the forefront key synthetic modifications on natural products (NPs) that have yielded successful drugs. The emphasis is placed on the power of targeted chemical transformations in enhancing the therapeutic value of NPs through optimization of pharmacokinetics, stability, potency, and/or selectivity. Multiple classes of NPs such as macrolides, opioids, steroids, and β-lactams used to treat a variety of conditions such as cancers, infections, inflammation are exemplified. Molecular modeling or X-ray structures of NP/protein complexes supporting the observed boost in therapeutic value of the modified NPs are also discussed. Significant advancement in synthetic chemistry, in structure determination, and in the understanding of factors controlling pharmacokinetics can now better position drug discovery teams to undertake NPs as valuable leads. We hope that the beneficial NPs synthetic modifications outlined here will reignite medicinal chemists' interest in NPs and their derivatives.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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