Though different species of the genus Plasmodium may be responsible for malaria, 
the variant caused by P. falciparum is often very dangerous and even fatal if 
untreated. Hemoglobin degradation is one of the key metabolic processes for the 
survival of the Plasmodium parasite in its host. Plasmepsins, a family of 
aspartic proteases encoded by the Plasmodium genome, play a prominent role in 
host hemoglobin cleavage. In this paper we demonstrate the use of virtual 
screening, in particular molecular docking, employed at a very large scale to 
identify novel inhibitors for plasmepsins II and IV. A large grid 
infrastructure, the EGEE grid, was used to address the problem of large 
computation resources required for docking hundreds of thousands of chemical 
compounds on different plasmepsin targets of P. falciparum. A large compound 
library of about 1 million chemical compounds was docked on 5 different targets 
of plasmepsins using two different docking software, namely FlexX and AutoDock. 
Several strategies were employed to analyze the results of this virtual 
screening approach including docking scores, ideal binding modes, and 
interactions to key residues of the protein. Three different classes of 
structures with thiourea, diphenylurea, and guanidino scaffolds were identified 
to be promising hits. While the identification of diphenylurea compounds is in 
accordance with the literature and thus provides a sort of "positive control", 
the identification of novel compounds with a guanidino scaffold proves that high 
throughput docking can be effectively used to identify novel potential 
inhibitors of P. falciparum plasmepsins. Thus, with the work presented here, we 
do not only demonstrate the relevance of computational grids in drug discovery 
but also identify several promising small molecules which have the potential to 
serve as candidate inhibitors for P. falciparum plasmepsins. With the use of the 
EGEE grid infrastructure for the virtual screening campaign against the malaria 
causing parasite P. falciparum we have demonstrated that resource sharing on an 
eScience infrastructure such as EGEE provides a new model for doing 
collaborative research to fight diseases of the poor.