New active drugs against liver stages of Plasmodium predicted by molecular topology.
Ontology highlight
ABSTRACT: We conducted a quantitative structure-activity relationship (QSAR) study based on a database of 127 compounds previously tested against the liver stage of Plasmodium yoelii in order to develop a model capable of predicting the in vitro antimalarial activities of new compounds. Topological indices were used as structural descriptors, and their relation to antimalarial activity was determined by using linear discriminant analysis. A topological model consisting of two discriminant functions was created. The first function discriminated between active and inactive compounds, and the second identified the most active among the active compounds. The model was then applied sequentially to a large database of compounds with unknown activity against liver stages of Plasmodium. Seventeen drugs that were predicted to be active or inactive were selected for testing against the hepatic stage of P. yoelii in vitro. Antiretroviral, antifungal, and cardiotonic drugs were found to be highly active (nanomolar 50% inhibitory concentration values), and two ionophores completely inhibited parasite development. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay was performed on hepatocyte cultures for all compounds, and none of these compounds were toxic in vitro. For both ionophores, the same in vitro assay as those for P. yoelii has confirmed their in vitro activities on Plasmodium falciparum. A similar topological model was used to estimate the octanol/water partition of each compound. These results demonstrate the utility of the QSAR and molecular topology approaches for identifying new drugs that are active against the hepatic stage of malaria parasites. We also show the remarkable efficacy of some drugs that were not previously reported to have antiparasitic activity.
SUBMITTER: Mahmoudi N
PROVIDER: S-EPMC2292524 | biostudies-literature | 2008 Apr
REPOSITORIES: biostudies-literature
ACCESS DATA