A systematic in silico search for target similarity identifies several approved drugs with potential activity against the Plasmodium falciparum apicoplast.

Most of the drugs in use against Plasmodium falciparum share similar modes of action and, consequently, there is a need to identify alternative potential drug targets. Here, we focus on the apicoplast, a malarial plastid-like organelle of algal source which evolved through secondary endosymbiosis. We undertake a systematic in silico target-based identification approach for detecting drugs already approved for clinical use in humans that may be able to interfere with the P. falciparum apicoplast. The P. falciparum genome database GeneDB was used to compile a list of ≈600 proteins containing apicoplast signal peptides. Each of these proteins was treated as a potential drug target and its predicted sequence was used to interrogate three different freely available databases (Therapeutic Target Database, DrugBank and STITCH3.1) that provide synoptic data on drugs and their primary or putative drug targets. We were able to identify several drugs that are expected to interact with forty-seven (47) peptides predicted to be involved in the biology of the P. falciparum apicoplast. Fifteen (15) of these putative targets are predicted to have affinity to drugs that are already approved for clinical use but have never been evaluated against malaria parasites. We suggest that some of these drugs should be experimentally tested and/or serve as leads for engineering new antimalarials.

In silico repositioning of new drugs against Schistosoma mansoni

Schistosomiasis is a neglected tropical disease caused by parasites of the genus Schistosoma. In Brazil only Schistosoma mansoni causes this disease. The World Health Organization estimated in 2012 approximately 249 million people at risk of acquiring this disease around the world. The main strategy to control this disease is praziquantel treatment of individuals living in endemic areas. The drug praziquantel is used on a large scale in the treatment of schistosomiasis and currently there are reported cases of resistance, indicating the need to discover new drugs. In silico drug repositioning is a time and cost reducing strategy in the search for anti-Schistosoma agents. This work used bioinformatic tools to identify potential schistosomicidal drugs. A list was compiled of S. mansoni potential targets that are part of essential processes in the database TDR and the targets that are part of the tegument were obtained in the scientific literature. The file with S. mansoni targets contained 1,376 targets, and of these only 61 targets associated with 399 drugs had homology with drug targets. After removal of duplicate drugs, drugs found in previous studies and after the analysis of the conservation of the binding site, only 28 S. mansoni targets associated with 102 drugs had 60% or more of the active site conserved. Some of the drugs had activity and are interesting to validate this study such as: artemether, lumefantrine, meloxicam. Among the drugs found 18 drugs were selected to be tested in prospective experimental assays according to the following criteria: low toxicity in vivo, off-patent status, and logP <5.0.