Synthesis of novel chloroquine derivatives and insights into the interactions of a resistance protein
Bibliographic record
Abstract
The human toll caused by malaria remains devastating. In 2018 alone, there were 228 million cases, which resulted in 405,000 deaths. Malaria is caused by the Plasmodium parasite transmitted by the Anopheles mosquito. There are five species: P. malariae, P.falciparum, P. vivax, P. ovale and P. knowlesi, in which P. falciparum is the most common and most deadly. An antimalarial drug called chloroquine (CQ) was first introduced in the 1940s and is considered the gold-standard antimalarial drug due to its high efficacy, low-cost, and low-toxicity. It is listed under the World Health Organization (WHO) essential medicines and showed great promise in their endeavor to eradicate malaria.Unfortunately, after two decades of use resistance began to arise, which led to its gradual withdrawal for P. falciparum cases. The WHO has reported an increase in the number of malaria cases over the last six years (214, 216, 228 million cases in 2014, 2016 and 2018, respectively), this is alarming as it greatly hampers the effects of eradication. Therefore, it remains crucial to invest in the research and development of new antimalarial drug candidates. Recent studies have reported the re-sensitization of chloroquine in countries where it was once completely banned, such as Malawi, Zambia and certain regions of The Ivory Coast. This indicates that resistance is reversible because it requires a fitness deficit. When drug pressure is removed, the frequency of resistance alleles is reduced but not eliminated. Therefore, the reintroduction of drug pressure will cause a rapid reemergence of resistance. As CQ was the ideal drug, many derivatives with varying sidechains and aryl substituents such as amodiaquine and piperaquine have emerged as commercial drugs. Aminoquinolines (AQs) continue to be prepared and tested, and two AQs wereIIIrecently undergoing phase II clinical trials, demonstrating the robustness of the AQ core and their future potential.My research centres around the repurposing of chloroquine via modification at the 3-position of the quinoline ring. In chapter 2 I describe the synthesis and optimization of 3-aminochloroquine (3-NH2CQ). The synthesis of this derivative allows for expansion at the 3-position for the synthesis of a diverse library of antimalarial candidates.In chapter 3, I describe the synthesis of novel substituted chloroquine analogs. The structure- activity relationship (SAR) was determined as I synthesized a library of compounds with varying steric and electronic effects. It was determined that electron-withdrawing substituents at the para- position gave the best antimalarial activity. Although the synthesized compounds were not as effective as CQ, they may be candidates for combination therapy with chloroquine.In chapter 4, I describe the synthesis of a CQ photoaffinity label with minor modifications. An aryl azide is installed at the 3rd-position on the quinoline ring, making it the first AQ photoaffinity label in the literature with the least number of modifications whilst retaining all features of the parent compound, to our knowledge. Labelling studies were then carried out to determine the lability of the photoaffinity label.Lastly, the protein responsible for CQ resistance, Plasmodium falciparum chloroquine resistance transporter (PfCRT), has been isolated for the first time. In chapter 5, I describe binding studies carried out with PfCRT. In collaboration with Prof. Fidock's group at Columbia University,IVfluorescence and UV-Vis binding studies were carried out to determine binding affinities of heme and CQ with PfCRT
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".