Integrative multi-kinase approach for the identification of potent antiplasmodial hits
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2019
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Resumo
Malaria is a tropical infectious disease that affects over 219 million people worldwide.
Due to the constant emergence of parasitic resistance to the current antimalarial
drugs, the discovery of new antimalarial drugs is a global health priority. Multi-target
drug discovery is a promising and innovative strategy for drug discovery and it is
currently regarded as one of the best strategies to face drug resistance. Aiming to
identify new multi-target antimalarial drug candidates, we developed an integrative
computational approach to select multi-kinase inhibitors for Plasmodium falciparum
calcium-dependent protein kinases 1 and 4 (CDPK1 and CDPK4) and protein kinase
6 (PK6). For this purpose, we developed and validated shape-based and machine
learning models to prioritize compounds for experimental evaluation. Then, we applied
the best models for virtual screening of a large commercial database of drug-like
molecules. Ten computational hits were experimentally evaluated against asexual blood
stages of both sensitive and multi-drug resistant P. falciparum strains. Among them,
LabMol-171, LabMol-172, and LabMol-181 showed potent antiplasmodial activity at
nanomolar concentrations (EC50 ≤ 700 nM) and selectivity indices >15 folds. In addition,
LabMol-171 and LabMol-181 showed good in vitro inhibition of P. berghei ookinete
formation and therefore represent promising transmission-blocking scaffolds. Finally,
docking studies with protein kinases CDPK1, CDPK4, and PK6 showed structural
insights for further hit-to-lead optimization studies.
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Malaria, Shape-based, Machine learning, Virtual screening, Plasmodium falciparum, Multi-target
Citação
LIMA, Marilia N. N. et al. Integrative multi-kinase approach for the identification of potent antiplasmodial hits. Frontiers in Chemistry, Lausanne, v. 7, p. 773, 2019. DOI: 10.3389/fchem.2019.00773. Disponível em: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6881481/. Acesso em: 10 set. 2024.