Phytochemical-based discovery of a potent antimalarial candidate targeting PfPI4K: A hybrid structure-based and deep learning approach.

Malaria is a parasitic infection that poses a threat to life and continues to be a serious challenge to global health. The recent COVID-19 pandemic has further escalated the situation. The emergence of artemisinin partial resistance and insecticide resistance emphasizes the critical need for novel antimalarial drug targets and agents with alternative mechanisms of action. This study focuses on Plasmodium falciparum phosphatidylinositol 4-kinase (PfPI4K), a phosphoinositide lipid kinase essential for membrane trafficking and biogenesis across multiple stages of the Plasmodium life cycle. We investigated a dataset of 58 natural anthraquinones with reported antimalarial activity as potential PfPI4K inhibitors. Employing Modeller 10.5 for homology modeling, we constructed the PfPI4K structure, validated by quality testing parameters. Subsequent in silico screening identified potential drug candidates. The top-scoring inhibitors were investigated by ADMET analysis. The compound AD37 (6'-O-methyl-knipholone) was identified as a prominent candidate. It complied with Lipinski's rule of five, displayed favorable ADMET parameters, and reported the highest binding affinity of -5.983 kcal/mol to PfPI4K as determined by GLIDE analysis. The stability and molecular interactions of the PfPI4K-AD37 complex were further confirmed by a 100 ns molecular dynamics simulation employing GROMACS. This investigation identifies AD37 as a promising drug candidate for treating malaria and provides valuable information regarding the molecular interactions essential for the future design and development of antimalarial drugs.