ArticleParasites & vectors2022
Genomic analysis of single nucleotide polymorphisms in malaria parasite drug targets.
Article in Parasites & vectors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 6 citations in OpenAlex.
- Generalist Malaria Parasites and Host Imprinting: Unveiling Transcriptional Memory.Molecular biology and evolution · 2025Article
- Combating antimicrobial resistance in malaria, HIV and tuberculosis.Nature reviews. Drug discovery · 2024Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
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Abstract
Malaria is a life-threatening parasitic disease caused by members of the genus Plasmodium. The development and spread of drug-resistant strains of Plasmodium parasites represent a major challenge to malaria control and elimination programmes. Evaluating genetic polymorphism in a drug target improves our understanding of drug resistance and facilitates drug design. Approximately 450 and 19 whole-genome assemblies of Plasmodium falciparum and Plasmodium vivax, respectively, are currently available, and numerous sequence variations have been found due to the presence of single nucleotide polymorphism (SNP). In the study reported here, we analysed global SNPs in the malaria parasite aminoacyl-tRNA synthetases (aaRSs). Our analysis revealed 3182 unique SNPs in the 20 cytoplasmic P. falciparum aaRSs. Structural mapping of SNPs onto the three-dimensional inhibitor-bound complexes of the three advanced drug targets within aaRSs revealed a remarkably low mutation frequency in the crucial aminoacylation domains, low overall occurrence of mutations across samples and high conservation in drug/substrate binding regions. In contrast to aaRSs, dihydropteroate synthase (DHPS), also a malaria drug target, showed high occurrences of drug resistance-causing mutations. Our results show that it is pivotal to screen potent malaria drug targets against global SNP profiles to assess genetic variances to ensure success in designing drugs against validated targets and tackle drug resistance early on.
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