In Silico Repositioning-Chemogenomics Strategy Identifies New Drugs with Potential Activity against Multiple Life Stages of Schistosoma mansoni

Abstract

Morbidity and mortality caused by schistosomiasis are serious public health problems in developing countries. Because praziquantel is the only drug in therapeutic use, the risk of drug resistance is a concern. In the search for new schistosomicidal drugs, we performed a target-based chemogenomics screen of a dataset of 2,114 proteins to identify drugs that are approved for clinical use in humans that may be active against multiple life stages of Schistosoma mansoni. Each of these proteins was treated as a potential drug target, and its amino acid sequence was used to interrogate three databases: Therapeutic Target Database (TTD), DrugBank and STITCH. Predicted drug-target interactions were refined using a combination of approaches, including pairwise alignment, conservation state of functional regions and chemical space analysis. To validate our strategy, several drugs previously shown to be active against Schistosoma species were correctly predicted, such as clonazepam, auranofin, nifedipine, and artesunate. We were also able to identify 115 drugs that have not yet been experimentally tested against schistosomes and that require further assessment. Some examples are aprindine, gentamicin, clotrimazole, tetrabenazine, griseofulvin, and cinnarizine. In conclusion, we have developed a systematic and focused computer-aided approach to propose approved drugs that may warrant testing and/or serve as lead compounds for the design of new drugs against schistosomes.

Author Summary

Schistosomiasis is a neglected tropical disease caused by schistosome parasites that affects millions of people worldwide. The current reliance on a single drug (Praziquantel) for treatment and control of the disease calls for the urgent discovery of novel schistosomicidal agents. One approach that can expedite drug discovery is to find new uses for existing approved drugs, a practice known as drug repositioning. Currently, modern drug repositioning strategies entail the search for compounds that act on a specific target, often a protein known or suspected to be required for survival of the parasite. Drug repositioning approaches for schistosomiasis are now greatly facilitated by the availability of comprehensive schistosome genome data in user-friendly databases. Here, we report a drug repositioning computational strategy that involves identification of novel schistosomicidal drug candidates using similarity between schistosome proteins and known drug targets. Researchers can now use the list of predicted drugs as a basis for deciding which potential schistosomicidal candidates can be tested experimentally.