Evaluating Real-Life High-Throughput Screening Data

Gribbon, Philip; Lyons, Richard; Laflin, Philip; Bradley, Joe; Chambers, Chris; Williams, Bruce S.; Keighley, Wilma; Sewing, Andreas

doi:10.1177/1087057104271957

Cited by 64 publications

(43 citation statements)

References 7 publications

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“…The outer wells containing the controls used for assessing the Z′ factor on future screening plates accurately reflected the activity of interior wells, which is important to consider when using the Z′ factor as a criterion for rejecting whole plates during screening. 26 The dynamic range of this lysis method was good, with a signalto background ratio that was typically in the range between 20 and 30fold throughout the screen. The variability (percent coefficient of variation) around the positive controls ranged ]glycine specific activity = 0.07 mCi/nmol) for 96 and 384well formats, respectively.…”

Section: Validation Of [ 3 H]glycine Uptake Assay Using Cho-k1/hglyt1mentioning

confidence: 99%

Successful Identification of Glycine Transporter Inhibitors Using an Adaptation of a Functional Cell-Based Assay

Kopec¹,

Jones²,

Thomas³

et al. 2009

SLAS Discovery

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Glycine transporter (GlyT1) function is typically measured by radiolabeled glycine uptake using lysis methods or scintilla tion proximity assays (SPAs), which have limited throughput. This study shows the adaptation of the standard cell lysis method to a screening assay with improved throughput and assay characteristics. The assay takes advantage of the 384well format, standard laboratory automation, and cryopreserved CHOK1 cells stably overexpressing human GlyT1a transporter (CHOK1/hGlyT1a) that were validated and banked in advance of screening. The assay was evaluated for the time course of glycine uptake, K m , V max , Z′ factor analysis, and IC 50 value determination with reference GlyT1 inhibitors. Screening of 118,000 compounds at 10 mM identified 4556 compounds (3.9%) as inhibitors. Positive compounds (>50% inhibition) were retested in the assay at 4 inhibitor concentrations. Compounds demonstrating greater than 40% inhibition at 10 mM were considered as confirmed positives, yielding a 68% confirmation rate from the original screen. To eliminate compounds that nonspecifically inhibited glycine uptake, IC 50 values were determined in both GlyT1 and GlyT2 assays, and those com pounds that inhibited GlyT2 were removed from consideration. The screening campaign identified 300 small molecules as selective GlyT1 inhibitors for lead optimization, demonstrating the utility of this costeffective method. (Journal of Biomolecular

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Section: Validation Of [ 3 H]glycine Uptake Assay Using Cho-k1/hglyt1mentioning

confidence: 99%

Successful Identification of Glycine Transporter Inhibitors Using an Adaptation of a Functional Cell-Based Assay

Kopec¹,

Jones²,

Thomas³

et al. 2009

SLAS Discovery

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“…Average Z′ was 0.60 ± 0.10, and standard deviation of raw inhibition for all compounds was 13.4%, acceptable for a cell-based HTS assay. 13 To minimize position-related biasing of data, selection criteria of mean + 3× standard deviation were set for raw as well as median-polished and normalized data sets, respectively (inhibition of 41%-46%). Compounds exceeding any of these criteria, 949 in total (hit rate ca.…”

Section: High-throughput Screeningmentioning

confidence: 99%

“…To insert the raw and calculated data into the Oracle database, we have used an in-house developed Tcl/Oratcl program. To assess and eliminate the effect of patterning within plates, both normalization with vehicle-treated plates and the median-polishing algorithm 13 were implemented into data analysis.…”

Section: Realization Of the Htsmentioning

confidence: 99%

Application of the BD ACTOne™ Technology for the High-Throughput Screening of Gs-Coupled Receptor Antagonists

Visegrády¹,

Boros²,

Némethy³

et al. 2007

SLAS Discovery

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“…[1][2][3] These SAR data mining methods conceptually depart from commonly used statistical, graphical, and molecular classification approaches. [4][5][6][7][8][9][10] Among other SAR features, our methods focus on the identification of local SAR environments that are rich in interpretable structure-activity information. [1][2][3] In order to study relationships between global and local SAR features, Networklike Similarity Graphs (NSGs) have been introduced that represent an annotated similarity-based molecular network structure integrating different levels of SAR-relevant chemical information.…”

mentioning

confidence: 99%

Extracting SAR Information from a Large Collection of Anti-Malarial Screening Hits by NSG-SPT Analysis

Wawer

Bajorath

2011

ACS Med. Chem. Lett.

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We combine two graphical SAR analysis methods, Network-like Similarity Graphs (NSGs) and Similarity-Potency Trees (SPTs), to search for SAR information in a large and heterogeneous compound data set containing more than 13,000 antimalarial screening hits that was recently released by GlaxoSmithKline (GSK). The NSG-SPT approach first identifies subsets of compounds inducing local SAR discontinuity in data sets and then extracts available SAR information from these subsets in a graphically intuitive manner. Applying the NSG-SPT analysis scheme, we have identified in the GSK collection compound subsets of high local SAR information content including both known and previously unknown antimalarial chemotypes, which yielded interpretable SAR patterns. This information should be helpful to prioritize and select antimalarial candidate compounds for further chemical exploration. Furthermore, the NSG-SPT tools are publicly available, and our study also shows how to practically apply these SAR analysis methods to study large compound data sets.

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Evaluating Real-Life High-Throughput Screening Data

Cited by 64 publications

References 7 publications

Successful Identification of Glycine Transporter Inhibitors Using an Adaptation of a Functional Cell-Based Assay

Successful Identification of Glycine Transporter Inhibitors Using an Adaptation of a Functional Cell-Based Assay

Application of the BD ACTOne™ Technology for the High-Throughput Screening of Gs-Coupled Receptor Antagonists

Extracting SAR Information from a Large Collection of Anti-Malarial Screening Hits by NSG-SPT Analysis

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