ABSTRACT
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.
ABSTRACT
Malaria remains a major detrimental parasitic disease in the developing world, with more than 200 million cases annually. Widespread drug-resistant parasite strains push for the development of novel antimalarial drugs. Plant-derived natural products are key sources of antimalarial molecules. Euterpe oleracea Martius ("açaí") originates from Brazil and has anti-inflammatory and antineoplasic properties. Here, we evaluated the antimalarial efficacy of three phenolic fractions of açaí; total phenolics (1), nonanthocyanin phenolics (2), and total anthocyanins (3). In vitro, fraction 2 moderately inhibited parasite growth in chloroquine-sensitive (HB3) and multiresistant (Dd2) Plasmodium falciparum strains, while none of the fractions was toxic to noncancer cells. Despite the limited activity in vitro, the oral treatment with 20 mg/kg of fraction 1 reduced parasitemia by 89.4% in Plasmodium chabaudi-infected mice and prolonged survival. Contrasting in vitro and in vivo activities of 1 suggest key antiplasmodial roles for polyphenol metabolites rather than the fraction itself. Finally, we performed haploinsufficiency chemical genomic profiling (HIP) utilizing heterozygous Saccharomyces cerevisiae deletion mutants to identify molecular mechanisms of açaí fractions. HIP results indicate proteostasis as the main cellular pathway affected by fraction 2. These results open avenues to develop açaí polyphenols as potential new antimalarial candidates.
ABSTRACT
Aim: Computer-aided drug design approaches were applied to identify chalcones with antiplasmodial activity. Methodology: The virtual screening was performed as follows: structural standardization of in-house database of chalcones; identification of potential Plasmodium falciparum protein targets for the chalcones; homology modeling of the predicted P. falciparum targets; molecular docking studies; and in vitro experimental validation. Results: Using these models, we prioritized 16 chalcones with potential antiplasmodial activity, for further experimental evaluation. Among them, LabMol-86 and LabMol-87 showed potent in vitro antiplasmodial activity against P. falciparum, while LabMol-63 and LabMol-73 were potent inhibitors of Plasmodium berghei progression into mosquito stages. Conclusion: Our results encourage the exploration of chalcones in hit-to-lead optimization studies for tackling malaria.
