Modern approaches to accelerate discovery of new antischistosomal drugs

ABSTRACT

Introduction: The almost exclusive use of only praziquantel for the treatment of schistosomiasis has raised concerns about the possible emergence of drug-resistant schistosomes. Consequently, there is an urgent need for new antischistosomal drugs. The identification of leads and the generation of high quality data are crucial steps in the early stages of schistosome drug discovery projects.

Areas covered: Herein, the authors focus on the current developments in antischistosomal lead discovery, specifically referring to the use of automated in vitro target-based and whole-organism screens and virtual screening of chemical databases. They highlight the strengths and pitfalls of each of the above-mentioned approaches, and suggest possible roadmaps towards the integration of several strategies, which may contribute for optimizing research outputs and led to more successful and cost-effective drug discovery endeavors.

Expert opinion: Increasing partnerships and access to funding for drug discovery have strengthened the battle against schistosomiasis in recent years. However, the authors believe this battle also includes innovative strategies to overcome scientific challenges. In this context, significant advances of in vitro screening as well as computer-aided drug discovery have contributed to increase the success rate and reduce the costs of drug discovery campaigns. Although some of these approaches were already used in current antischistosomal lead discovery pipelines, the integration of these strategies in a solid workflow should allow the production of new treatments for schistosomiasis in the near future.

KEYWORDS:

• Schistosomiasis
• drug discovery
• computer-aided molecular design
• automated assays
• data quality
• virtual screening
• perspectives

Article highlights

• The possible evolution of PZQ-resistant schistosomes and the lack of new effective drugs call for a paradigm shift from contemporary to modern antischistosomal lead discovery strategies.

• The main advances in high- and medium-throughput led screening technologies have opened up new possibilities for antischistosomal drug discovery pipelines.

• Data produced on extract bioactivity from medium- and high-throughput assays, that is open data available on publicly databases, can now be explored in a computational data-driven process.

• Both experimental (i.e. target-based assays, automated whole-organism assays, and luminescence- and fluorescence-based assays) and computational (i.e. structure-based and ligand-based strategies) drug discovery approaches have strengths and pitfalls, but carefully planned integration of these strategies could lead to new treatments for schistosomiasis in the near future.

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Declaration of interests

The authors would like to thank Brazilian funding agencies, CNPq, CAPES, and FAPEG, for financial support and fellowships. E Muratov thanks the financial support from NIH (GM 096967 and GM66940), CNPq (grant 400760/2014-2), and UNC for Junior Faculty Development Award. CH Andrade and PVL Cravo are Research Fellows in productivity of CNPq. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.