A Structural Chemistry Perspective on the Antimalarial Properties of Thiosemicarbazone Metal Complexes
Bibliographic record
Abstract
Malaria is a potentially life-threatening disease, affecting approx. 214 million people worldwide. Malaria is caused by a protozoan, Plasmodium falciparum, which is transmitted through the Anopheles mosquito. Malaria treatment is becoming more challenging due to rising resistance against the antimalarial drug, chloroquine. Novel compounds that target aspects of parasite development are being explored in attempts to overcome this wide-spread problem. Anti-malarial drugs target specific aspects of parasite growth and development within the human host. One of the most effective targets is the inhibition of hematin formation, either through inhibition of cysteine proteases or through iron chelation. Metal-thiosemicarbazone (TSC) complexes have been tested for antimalarial efficacy against drug-sensitive and drug-resistant strains of P. falciparum. An array of TSC complexes with numerous transition metals, including ruthenium, palladium, and gold has displayed antiplasmodial activity. Au(I)- and Pd(II)-TSC complexes displayed the greatest potency; 4-amino-7-chloroquine moieties were also found to improve antiplasmodial activity of TSCs. Although promising metal-TSC drug candidates have been tested against laboratory strains of P. falciparum, problems arise when attempting to compare between studies. Future work should strive to completely characterize synthesized metal-TSC structures and assess antiplasmodial potency against several drug-sensitive and drugresistant strains. Future studies need to precisely determine IC50 values for antimalarial drugs, chloroquine and ferroquine, to establish accurate standard values. This will make future comparisons across studies more feasible and potentially help reveal structure-function relationships. Investigations that attempt to link drug structures or properties to antiplasmodial mechanism(s) of action will aid in the design of antimalarial drugs that may combat rising drug resistance.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".