title: Modern approaches to accelerate discovery of new antischistosomal drugs.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: a LabMol - Laboratory for Molecular Modeling and Drug Design, Faculdade de Farmácia , Universidade Federal de Goiás , Goiânia , Brazil.
authors.forename: Bruno Junior
authors.initials: BJ
authors.lastname: Neves
authors.affiliation: b Laboratory for Molecular Modeling, Eshelman School of Pharmacy , University of North Carolina , Chapel Hill , NC , USA.
authors.forename: Eugene
authors.initials: E
authors.lastname: Muratov
authors.affiliation: c GenoBio - Laboratory of Genomics and Biotechnology, Instituto de Patologia Tropical e Saúde Pública , Universidade Federal de Goiás , Goiânia , Brazil.
authors.forename: Renato Beilner
authors.initials: RB
authors.lastname: Machado
authors.affiliation: a LabMol - Laboratory for Molecular Modeling and Drug Design, Faculdade de Farmácia , Universidade Federal de Goiás , Goiânia , Brazil.
authors.forename: Carolina Horta
authors.initials: CH
authors.lastname: Andrade
authors.affiliation: c GenoBio - Laboratory of Genomics and Biotechnology, Instituto de Patologia Tropical e Saúde Pública , Universidade Federal de Goiás , Goiânia , Brazil.|d Instituto de Higiene e Medicina Tropical , Universidade Nova de Lisboa , Lisbon , Portugal.
authors.forename: Pedro Vitor Lemos
authors.initials: PV
authors.lastname: Cravo
mesh_terms: D000818:Animals; D017076:Computer-Aided Design; D062126:Databases, Chemical; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods; D004351:Drug Resistance; D006801:Humans; D012552:Schistosomiasis / Q000188:drug therapy* / Q000469:parasitology; D012556:Schistosomicides / Q000494:pharmacology / Q000627:therapeutic use*
chemical_list: D012556:Schistosomicides
keywords: Schistosomiasis; automated assays; computer-aided molecular design; data quality; drug discovery; perspectives; virtual screening