antimalarial

Support vector machine (SVM) and general regression neural network (GRNN) were used to develop classification models for predicting the antimalarial activity against Plasmodium falciparum. Only 15 molecular descriptors were used to build the classification models for the antimalarial activities of 4750 compounds, which were divided into a training set (3887 compounds) and a test set (863 compounds).

Malaria remains a serious worldwide health danger and massive economic trouble to disease-endemic nations. Presently, 250 million of malarial cases are expected worldwide. The emergence of fighting of the Plasmodium parasite against the first-line antimalarial drugs has fueled research attention in the way of designing new scaffolds as well as strategies to counter the drug resistance.

Malaria is a global health problem leading to the death of 435,000 cases in tropical and sub-tropical zones. Spread and emergence of increasing resistance to the antimalarial drugs are the major challenges in the control of malaria. Therefore, searching for alternative antimalarial drugs is urgently needed, and combination treatment preferred as an approach to address this. This study aimed to evaluate in vivo antimalarial activity of zingerone (ZN), and its combination with dihydroartemisinin (DHA) against Plasmodium berghei infected mice.

Coccinia barteri (Hook. F.) is traditional used in Southeast of Nigeria in management of fever. This study aimed to evaluate the antimalarial activities of hydro-methanol crude extract and solvent fractions of Coccinia barteri leaf.

In this study, 44 flavonoids found mainly in the fruit juice of Citrus species having traditional use in malaria-associated fever were selected for in silico multiple-target directed screening against three vital targets of the parasite namely dihydrooroate dehydrogenase (PfDHODH), dihydrofolate reductase thymidine synthase (PfDHFR-TS) and plasma membrane P-type cation translocating ATPase (PfATP4) to find out new lead molecule(s).