Comparison of Assay Technologies for a Nuclear Receptor Assay Screen Reveals Differences in the Sets of Identified Functional Antagonists

Wu, Xiang; Glickman, J. Fraser; Bowen, Benjamin R.; Sills, Matthew A.

doi:10.1177/1087057103256466

Cited by 46 publications

(50 citation statements)

References 9 publications

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“…Typically, data sets generated by 2 different assays are visualized using a correlation plot, and the relationship between the 2 data sets is defined by the line of best fit and coefficient of determination (r 2 ). 7,8 If the relationship is linear (r 2 = 1), the data sets are said to agree with each other. However, this approach has been shown to be insufficient for agreement analysis between 2 data sets.…”

mentioning

confidence: 99%

Adopting a Practical Statistical Approach for Evaluating Assay Agreement in Drug Discovery

Sun

Whitty²,

Papadatos³

et al. 2005

SLAS Discovery

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The authors assess the equivalence of 2 assays and put forward a general approach for assay agreement analysis that can be applied during drug discovery. Data sets generated by different assays are routinely compared to each other during the process of drug discovery. For a given target, the assays used for high-throughput screening and structure-activity relationship studies will most likely differ in their assay reagents, assay conditions, and/or detection technology, which makes the interpretation of data between assays difficult, particularly as most assays are used to measure quantitative changes in compound potency against the target. To better quantify the relationship of data sets from different assays for the same target, the authors evaluated the agreement between results generated by 2 different assays that measure the activity of compounds against the same protein, ALK5. The authors show that the agreement between data sets can be quantified using correlation and Bland-Altman plots, and the precision of the assays can be used to define the expectations of agreement between 2 assays. They propose a scheme for addressing issues of assay data equivalence, which can be applied to address questions of how data sets compare during the lead identification and lead optimization processes in which assays are frequently added and changed. (Journal of Biomolecular Screening 2005:508-516)

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mentioning

confidence: 99%

Adopting a Practical Statistical Approach for Evaluating Assay Agreement in Drug Discovery

Sun

Whitty²,

Papadatos³

et al. 2005

SLAS Discovery

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“…This indicates a relatively good correlation among the 3 assay formats used for detecting the 3 biochemical activities of ITK, especially considering the observation that different assay technologies measuring the same activity can generate divergent hit sets. [29][30][31][32][33] For example, a smaller overlap of active compounds was observed when 30,000 compounds were evaluated in 3 different versions of the phosphoryl-transfer activity assay of a tyrosine kinase using scintillation proximity assay (SPA), homogeneous time-resolved fluorescence resonance energy transfer (TR-FRET), and FP technologies. 31 In another study from the same laboratory, about 42,000 compounds were evaluated in a nuclear receptor antagonist assay using 3 assay formats: amplified luminescent proximity homogeneous assay (AlphaScreen), DELFIA, and TR-FRET, which respectively identified 104, 23, and 57 active compounds with only 18 compounds active in all 3 assay formats (17% overlap).…”

Section: Resultsmentioning

confidence: 99%

“…31 In another study from the same laboratory, about 42,000 compounds were evaluated in a nuclear receptor antagonist assay using 3 assay formats: amplified luminescent proximity homogeneous assay (AlphaScreen), DELFIA, and TR-FRET, which respectively identified 104, 23, and 57 active compounds with only 18 compounds active in all 3 assay formats (17% overlap). 30 Also, the AlphaScreen identified the largest number of functional antagonists. 30 Another group demonstrated greater than 94% overlap of active compounds identified by screening 2133 compounds against the phosphoryl-transfer activity of a serine/threonine kinase using the ATP detection luminescence assay and a microfluidic assay that measures the change in mobility in an electric field of a fluorescently labeled peptide upon phosphorylation.…”

Section: Resultsmentioning

confidence: 99%

Three Mechanistically Distinct Kinase Assays Compared: Measurement of Intrinsic ATPase Activity Identified the Most Comprehensive Set of ITK Inhibitors

Kashem¹,

Nelson²,

Yingling³

et al. 2007

SLAS Discovery

113

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Numerous assay methods have been developed to identify small-molecule effectors of protein kinases, but no single method can be applied to all isolated kinases. The authors developed a set of 3 high-throughput screening (HTS)-compatible biochemical assays that can measure 3 mechanistically distinct properties of a kinase active site, with the goal that at least 1 of the 3 would be applicable to any kinase selected as a target for drug discovery efforts. Two assays measure catalytically active enzyme: A dissociation-enhanced lanthanide fluoroimmuno assay (DELFIA) uses an antibody to quantitate the generation of phosphorylated substrate; a second assay uses luciferase to measure the consumption of adenosine triphosphate (ATP) during either phosphoryl-transfer to a peptide substrate or to water (intrinsic ATPase activity). A third assay, which is not dependent on a catalytically active enzyme, measures the competition for binding to kinase between an inhibitor and a fluorescent ATP binding site probe. To evaluate the suitability of these assays for drug discovery, the authors compared their ability to identify inhibitors of a nonreceptor protein tyrosine kinase from the Tec family, interleukin-2-inducible T cell kinase (ITK). The 3 assays agreed on 57% of the combined confirmed hit set identified from screening a 10,208-compound library enriched with known kinase inhibitors and molecules that were structurally similar. Among the 3 assays, the one measuring intrinsic ATPase activity produced the largest number of unique hits, the fewest unique misses, and the most comprehensive hit set, missing only 2.7% of the confirmed inhibitors identified by the other 2 assays combined. Based on these data, all 3 assay formats are viable for screening and together provide greater options for assay design depending on the targeted kinase. (Journal of Biomolecular

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“…1,2 Historically, however, this approach has met with variable and somewhat limited success. [3][4][5][6][7] Pooling strategies typically use multiplexed library plates containing 10 or more compounds per well stored at high concentrations in DMSO over long periods of time. The difficulties with this approach likely arise from many factors, including the potential for reactivity between compounds, solubility issues due to high compound concentration and alterations in ionic strength, the negative effects of high organic load in the assay well, as well as the potential for synergistic and antagonistic interactions between compounds.…”

Section: Introductionmentioning

confidence: 99%

Just-in-Time Compound Pooling Increases Primary Screening Capacity without Compromising Screening Quality

et al. 2015

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Compound pooling, or multiplexing more than one compound per well during primary high-throughput screening (HTS), is a controversial approach with a long history of limited success. Many issues with this approach likely arise from long-term storage of library plates containing complex mixtures of compounds at high concentrations. Due to the historical difficulties with using multiplexed library plates, primary HTS often uses a one-compound-one-well approach. However, as compound collections grow, innovative strategies are required to increase the capacity of primary screening campaigns. Toward this goal, we have developed a novel compound pooling method that increases screening capacity without compromising data quality. This method circumvents issues related to the long-term storage of complex compound mixtures by using acoustic dispensing to enable "just-in-time" compound pooling directly in the assay well immediately prior to assay. Using this method, we can pool two compounds per well, effectively doubling the capacity of a primary screen. Here, we present data from pilot studies using just-in-time pooling, as well as data from a large >2-million-compound screen using this approach. These data suggest that, for many targets, this method can be used to vastly increase screening capacity without significant reduction in the ability to detect screening hits.

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Comparison of Assay Technologies for a Nuclear Receptor Assay Screen Reveals Differences in the Sets of Identified Functional Antagonists

Cited by 46 publications

References 9 publications

Adopting a Practical Statistical Approach for Evaluating Assay Agreement in Drug Discovery

Adopting a Practical Statistical Approach for Evaluating Assay Agreement in Drug Discovery

Three Mechanistically Distinct Kinase Assays Compared: Measurement of Intrinsic ATPase Activity Identified the Most Comprehensive Set of ITK Inhibitors

Just-in-Time Compound Pooling Increases Primary Screening Capacity without Compromising Screening Quality

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