A multi-dimensional, time-lapse, high content screening platform applied to schistosomiasis drug discovery

Steven Chen; Brian M. Suzuki; Jakob Dohrmann; Rahul Singh; Michelle R. Arkin; Conor R. Caffrey

doi:10.1038/s42003-020-01402-5

Communications Biology (Dec 2020)

A multi-dimensional, time-lapse, high content screening platform applied to schistosomiasis drug discovery

Steven Chen,
Brian M. Suzuki,
Jakob Dohrmann,
Rahul Singh,
Michelle R. Arkin,
Conor R. Caffrey

Affiliations

Steven Chen: Department of Pharmaceutical Chemistry and Small Molecule Discovery Center, University of California
Brian M. Suzuki: Center for Discovery and Innovation in Parasitic Diseases, Department of Pathology, University of California
Jakob Dohrmann: Department of Computer Science, San Francisco State University
Rahul Singh: Department of Computer Science, San Francisco State University
Michelle R. Arkin: Department of Pharmaceutical Chemistry and Small Molecule Discovery Center, University of California
Conor R. Caffrey: Center for Discovery and Innovation in Parasitic Diseases, Department of Pathology, University of California

DOI: https://doi.org/10.1038/s42003-020-01402-5
Journal volume & issue: Vol. 3, no. 1
pp. 1 – 9

Abstract

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Steven Chen et al. develop an automated, time-lapsed, high-content screen to quantify the responses of Schistosoma mansoni larvae to chemical insult. They apply their method to evaluate 45 static and kinetic response endpoints for seven drugs and screen 1323 approved drugs. Their work identifies anti-schistosomal compounds and underscores the value of quantifying motion in phenotypic drug discovery.

Published in Communications Biology

ISSN: 2399-3642 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science: Biology (General)
Website: https://www.nature.com/commsbio/

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