Modular Synthesis of 1,2- and 1,1′-Disubstituted Ferrocenyl Carbohydrate Chloroquine and Mefloquine Conjugates as Potential Antimalarial Agents
Bibliographic record
Abstract
The modular synthesis of novel organometallic antimalarials based on a 1,2- or 1,1′-disubstituted ferrocene scaffold ( 10 and 11 ) is presented. Ferrocenes were substituted via an ether linker with either 7-chloroquinoline or 2,8-bis(trifluoromethyl)quinoline, as a chloroquine or mefloquine derivative, respectively. Diisopropylidene-protected 6-amino-6-deoxyglucofuranose ( 18 ) or 6-amino-6-deoxygalactopyranose ( 21 ) was coupled via reductive amination to yield the target conjugates 24 – 27 and 30 . Yields could be substantially increased using a microwave reactor instead of conventional heating, which reduced the reaction time as well. After complete characterization these novel trifunctional conjugates were examined for their antiplasmodial activity in a chloroquine-susceptible (CQS) strain of Plasmodium falciparum (D10) and a chloroquine-resistant (CQR) strain (Dd2). The determined IC 50 values were in the low micromolar range. Introduction of the carbohydrate led to an increase in activity (>200 μM ( 16, D10) to 1.2 μM ( 24, D10)). The best activity was measured for 26 in Dd2 (IC 50 = 0.77 μM). Resistance indices (RI) for all measured compounds were <1, indicating a higher activity in the chloroquine-resistant Dd2 strain in comparison to the chloroquine-susceptible D10 strain (RI = 0.93 for 24, RI = 0.15 for 25 ).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".