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Nature communications
08 25, 2023;14 (1): 5205.

Propensity of selecting mutant parasites for the antimalarial drug cabamiquine.

Eva Stadler, Mohamed Maiga, Lukas Friedrich, Vandana Thathy, Claudia Demarta-Gatsi, Antoine Dara, Fanta Sogore, Josefine Striepen, Claude Oeuvray, Abdoulaye A Djimdé, Marcus C S Lee, Laurent Dembélé, David A Fidock, David S Khoury, Thomas Spangenberg
Author Information
  1. Eva Stadler: The Kirby Institute, UNSW Sydney, Kensington, NSW, 2052, Australia. ORCID
  2. Mohamed Maiga: Université des Sciences, des Techniques et des Technologies de Bamako (USTTB), Faculté de Pharmacie, Malaria Research and Training Center (MRTC), Point G, PB1805, Bamako, Mali. ORCID
  3. Lukas Friedrich: Medicinal Chemistry & Drug Design Global Research & Development, Discovery Technologies, Merck Healthcare, 64293, Darmstadt, Germany.
  4. Vandana Thathy: Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY, 10032, USA.
  5. Claudia Demarta-Gatsi: Global Health Institute of Merck, Ares Trading S.A., (an affiliate of Merck KGaA, Darmstadt, Germany), 1262, Eysins, Switzerland. ORCID
  6. Antoine Dara: Université des Sciences, des Techniques et des Technologies de Bamako (USTTB), Faculté de Pharmacie, Malaria Research and Training Center (MRTC), Point G, PB1805, Bamako, Mali. ORCID
  7. Fanta Sogore: Université des Sciences, des Techniques et des Technologies de Bamako (USTTB), Faculté de Pharmacie, Malaria Research and Training Center (MRTC), Point G, PB1805, Bamako, Mali.
  8. Josefine Striepen: Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY, 10032, USA. ORCID
  9. Claude Oeuvray: Global Health Institute of Merck, Ares Trading S.A., (an affiliate of Merck KGaA, Darmstadt, Germany), 1262, Eysins, Switzerland.
  10. Abdoulaye A Djimdé: Université des Sciences, des Techniques et des Technologies de Bamako (USTTB), Faculté de Pharmacie, Malaria Research and Training Center (MRTC), Point G, PB1805, Bamako, Mali. ORCID
  11. Marcus C S Lee: Wellcome Sanger Institute, Wellcome Genome Campus, CB10 1SA, Hinxton, UK. ORCID
  12. Laurent Dembélé: Université des Sciences, des Techniques et des Technologies de Bamako (USTTB), Faculté de Pharmacie, Malaria Research and Training Center (MRTC), Point G, PB1805, Bamako, Mali. laurent@icermali.org.
  13. David A Fidock: Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, NY, 10032, USA. df2260@cumc.columbia.edu. ORCID
  14. David S Khoury: The Kirby Institute, UNSW Sydney, Kensington, NSW, 2052, Australia. dkhoury@kirby.unsw.edu.au. ORCID
  15. Thomas Spangenberg: Global Health Institute of Merck, Ares Trading S.A., (an affiliate of Merck KGaA, Darmstadt, Germany), 1262, Eysins, Switzerland. thomas.spangenberg@merckgroup.com. ORCID
PMID: 37626093 DOI: 10.1038/s41467-023-40974-8

Abstract

We report an analysis of the propensity of the antimalarial agent cabamiquine, a Plasmodium-specific eukaryotic elongation factor 2 inhibitor, to select for resistant Plasmodium falciparum parasites. Through in vitro studies of laboratory strains and clinical isolates, a humanized mouse model, and volunteer infection studies, we identified resistance-associated mutations at 11 amino acid positions. Of these, six (55%) were present in more than one infection model, indicating translatability across models. Mathematical modelling suggested that resistant mutants were likely pre-existent at the time of drug exposure across studies. Here, we estimated a wide range of frequencies of resistant mutants across the different infection models, much of which can be attributed to stochastic differences resulting from experimental design choices. Structural modelling implicates binding of cabamiquine to a shallow mRNA binding site adjacent to two of the most frequently identified resistance mutations.

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MeSH Term

Animals
Mice
Antimalarials
Parasites
Amino Acids
Binding Sites
Disease Models, Animal

Chemicals

Antimalarials
Amino Acids
Journal Article Research Support, Non-U.S. Gov't
Article has an altmetric score of 9

Word Cloud

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