Target Identification of Compounds from a Cell Viability Phenotypic Screen Using a Bead/Lysate-Based Affinity Capture Platform
SLAS Discovery, ISSN: 2472-5552, Vol: 21, Issue: 2, Page: 201-211
2016
- 17Citations
- 38Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations17
- Citation Indexes17
- 17
- CrossRef16
- Captures38
- Readers38
- 38
Article Description
The pharmaceutical industry has been continually challenged by dwindling target diversity. To obviate this trend, phenotypic screens have been adopted, complementing target-centric screening approaches. Phenotypic screens identify drug leads using clinically relevant and translatable mechanisms, remaining agnostic to targets. While target anonymity is advantageous early in the drug discovery process, it poses challenges to hit progression, including the development of backup series, retaining desired pharmacology during optimization, discovery of markers, and understanding mechanism-driven toxicity. Consequently, significant effort has been expended to elaborate the targets and mechanisms at work for promising screening hits. Affinity capture is commonly leveraged, where the compounds are linked to beads and targets are abstracted from cell homogenates. This technique has proven effective for identifying targets of kinase, PARP, and HDAC inhibitors, and examples of new targets have been reported. Herein, a three-pronged approach to target deconvolution by affinity capture is described, including the implementation of a uniqueness index that helps discriminate between bona fide targets and background. The effectiveness of this approach is demonstrated using characterized compounds that act on known and noncanonical target classes. The platform is subsequently applied to phenotypic screening hits, identifying candidate targets. The success rate of bead-based affinity capture is discussed.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2472555222070721; http://dx.doi.org/10.1177/1087057115622431; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84954528369&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/26676096; https://linkinghub.elsevier.com/retrieve/pii/S2472555222070721
Elsevier BV
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