Book chapter
Quantitative High‐Content Screening‐Based Drug Discovery against Helmintic Diseases
Parasitic Helminths, pp.159-179
Wiley‐VCH Verlag GmbH & Co. KGaA
07/18/2012
DOI: 10.1002/9783527652969.ch10
Abstract
At the state‐of‐the‐art, high‐throughput and high‐content screening (HTS/HCS) have become key technologies in modern drug discovery. These highly automated techniques allow rapid analysis of a large number of drug molecules and selection of candidates for lead optimization. Drug discovery for helmintic diseases, however, presents significant challenges to the standard HTS/HCS framework as well as opportunities for its further development. The central problem lies in the fact that discovery of efficacious leads against helminths often requires screening molecules against the entire parasite. Ideally, the effect of a drug needs to be studied in terms of effects on the parasite morphology, motility, and behavior, in addition to measuring often oversimplistic end‐points for parasite death. Such an enhanced approach to screening can help in forming a more holistic understanding of the drug–parasite interactions and ensure that molecules that do not lead to immediate death, yet perturb the parasite's ability to survive, are not missed. The tasks of data acquisition, processing, and analysis in such settings require addressing technical problems that are different and arguably richer than those underlying the corresponding stages in both molecular‐target‐based HTS, as well as cell‐based screening. In the first part of this chapter, using the specific context of two diseases, schistosomiasis and filariasis, the key problems that confront further development of HTS/HCS, especially in the context of its applicability against helmintic diseases, are identified and analyzed. This is followed by an introduction to the basics of automated image analysis using a typical image analysis workflow for HTS as the backdrop. Next, we briefly review the progress to date in quantitative whole‐organism phenotyping and screening. Finally, we present results from our own research on segmentation and automated phenotyping, which provide a detailed perspective on how some of the critical challenges in this area can be addressed.
Details
- Title: Subtitle
- Quantitative High‐Content Screening‐Based Drug Discovery against Helmintic Diseases
- Creators
- Rahul Singh - San Francisco State University
- Contributors
- Conor R Caffrey (Editor) - University of California, San Francisco
- Resource Type
- Book chapter
- Publication Details
- Parasitic Helminths, pp.159-179
- Publisher
- Wiley‐VCH Verlag GmbH & Co. KGaA; Weinheim, Germany
- DOI
- 10.1002/9783527652969.ch10
- Number of pages
- 21
- Language
- English
- Date published
- 07/18/2012
- Academic Unit
- Computer Science
- Record Identifier
- 9984446544102771
Metrics
1 Record Views