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Schistosomiasis drug discovery in the era of automation and artificial intelligence

DOI: 10.3389/fimmu.2021.642383 DOI Help

Authors: José T. Moreira-Filho (Universidade Federal de Goiás – UFG) , Arthur C. Silva (Universidade Federal de Goiás – UFG) , Rafael F. Dantas (Fundação Oswaldo Cruz) , Barbara F. Gomes (Fundação Oswaldo Cruz) , Lauro R. De Souza Neto (Fundação Oswaldo Cruz) , Jose Brandao-Neto (Diamond Light Source; Research Complex at Harwell) , Raymond J. Owens (The Rosalind Franklin Institute; he Wellcome Centre for Human Genetic, University of Oxford) , Nicholas Furnham (London School of Hygiene and Tropical Medicine) , Bruno J. Neves (Universidade Federal de Goiás – UFG) , Floriano P. Silva-Junior (Fundação Oswaldo Cruz) , Carolina H. Andrade (Universidade Federal de Goiás – UFG)
Co-authored by industrial partner: No

Type: Journal Paper
Journal: Frontiers In Immunology , VOL 12

State: Published (Approved)
Published: May 2021
Diamond Proposal Number(s): 16978

Open Access Open Access

Abstract: Schistosomiasis is a parasitic disease caused by trematode worms of the genus Schistosoma and affects over 200 million people worldwide. The control and treatment of this neglected tropical disease is based on a single drug, praziquantel, which raises concerns about the development of drug resistance. This, and the lack of efficacy of praziquantel against juvenile worms, highlights the urgency for new antischistosomal therapies. In this review we focus on innovative approaches to the identification of antischistosomal drug candidates, including the use of automated assays, fragment-based screening, computer-aided and artificial intelligence-based computational methods. We highlight the current developments that may contribute to optimizing research outputs and lead to more effective drugs for this highly prevalent disease, in a more cost-effective drug discovery endeavor.

Journal Keywords: schistosomiasis; drug discovery; artificial intelligence; fragment-based drug discovery; phenotypic screening; target-based screening

Diamond Keywords: Schistosomiasis

Subject Areas: Biology and Bio-materials, Medicine, Information and Communication Technology

Diamond Offline Facilities: XChem
Instruments: I04-1-Macromolecular Crystallography (fixed wavelength)

Added On: 21/06/2021 14:43

Documents:
fimmu-12-642383.pdf

Discipline Tags:

Information & Communication Technologies Artificial Intelligence Life Sciences & Biotech Health & Wellbeing Disease in the Developing World Drug Discovery Infectious Diseases Structural biology Parasitology

Technical Tags:

Diffraction Macromolecular Crystallography (MX) Fragment Screening