Predictive modeling of anti-malarial molecules inhibiting apicoplast formation.

ABSTRACT:

Background

Malaria is a major healthcare problem worldwide resulting in an estimated 0.65 million deaths every year. It is caused by the members of the parasite genus Plasmodium. The current therapeutic options for malaria are limited to a few classes of molecules, and are fast shrinking due to the emergence of widespread resistance to drugs in the pathogen. The recent availability of high-throughput phenotypic screen datasets for antimalarial activity offers a possibility to create computational models for bioactivity based on chemical descriptors of molecules with potential to accelerate drug discovery for malaria.

Results

In the present study, we have used high-throughput screen datasets for the discovery of apicoplast inhibitors of the malarial pathogen as assayed from t

SUBMITTER: Jamal S 

PROVIDER: S-EPMC3599641 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature