scholarly journals Using Weighted Entropy to Rank Chemicals in Quantitative High-Throughput Screening Experiments

2013 ◽  
Vol 19 (3) ◽  
pp. 344-353 ◽  
Author(s):  
Keith R. Shockley
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Nonlinear Models ◽  
Hill Equation ◽  
Parameter Estimates ◽  
Chemical Library ◽  
Data Set ◽  
Screening Experiments ◽  
The Hill ◽  
Weighted Entropy

Quantitative high-throughput screening (qHTS) experiments can simultaneously produce concentration-response profiles for thousands of chemicals. In a typical qHTS study, a large chemical library is subjected to a primary screen to identify candidate hits for secondary screening, validation studies, or prediction modeling. Different algorithms, usually based on the Hill equation logistic model, have been used to classify compounds as active or inactive (or inconclusive). However, observed concentration-response activity relationships may not adequately fit a sigmoidal curve. Furthermore, it is unclear how to prioritize chemicals for follow-up studies given the large uncertainties that often accompany parameter estimates from nonlinear models. Weighted Shannon entropy can address these concerns by ranking compounds according to profile-specific statistics derived from estimates of the probability mass distribution of response at the tested concentration levels. This strategy can be used to rank all tested chemicals in the absence of a prespecified model structure, or the approach can complement existing activity call algorithms by ranking the returned candidate hits. The weighted entropy approach was evaluated here using data simulated from the Hill equation model. The procedure was then applied to a chemical genomics profiling data set interrogating compounds for androgen receptor agonist activity.

scholarly journals Outlier Mining in High Throughput Screening Experiments

2002 ◽  
Vol 7 (4) ◽  
pp. 341-351 ◽  
Author(s):  
Michael F.M. Engels ◽  
Luc Wouters ◽  
Rudi Verbeeck ◽  
Greet Vanhoof
Keyword(s):  
Data Mining ◽  
Biological Activity ◽  
High Throughput ◽  
High Throughput Screening ◽  
False Negative ◽  
Data Sets ◽  
Data Set ◽  
Structure Information ◽  
Screening Experiments ◽  
Mining Procedure

A data mining procedure for the rapid scoring of high-throughput screening (HTS) compounds is presented. The method is particularly useful for monitoring the quality of HTS data and tracking outliers in automated pharmaceutical or agrochemical screening, thus providing more complete and thorough structure-activity relationship (SAR) information. The method is based on the utilization of the assumed relationship between the structure of the screened compounds and the biological activity on a given screen expressed on a binary scale. By means of a data mining method, a SAR description of the data is developed that assigns probabilities of being a hit to each compound of the screen. Then, an inconsistency score expressing the degree of deviation between the adequacy of the SAR description and the actual biological activity is computed. The inconsistency score enables the identification of potential outliers that can be primed for validation experiments. The approach is particularly useful for detecting false-negative outliers and for identifying SAR-compliant hit/nonhit borderline compounds, both of which are classes of compounds that can contribute substantially to the development and understanding of robust SARs. In a first implementation of the method, one- and two-dimensional descriptors are used for encoding molecular structure information and logistic regression for calculating hits/nonhits probability scores. The approach was validated on three data sets, the first one from a publicly available screening data set and the second and third from in-house HTS screening campaigns. Because of its simplicity, robustness, and accuracy, the procedure is suitable for automation.

scholarly journals Identification of a juvenile-hormone signaling inhibitor via high-throughput screening of a chemical library

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Takumi Kayukawa ◽  
Kenjiro Furuta ◽  
Keisuke Nagamine ◽  
Tetsuro Shinoda ◽  
Kiyoaki Yonesu ◽  
...  
Keyword(s):  
Juvenile Hormone ◽  
Cell Line ◽  
Signaling Pathway ◽  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Ex Vivo ◽  
Agricultural Field ◽  
Chemical Library ◽  
Field Development

Abstract Insecticide resistance has recently become a serious problem in the agricultural field. Development of insecticides with new mechanisms of action is essential to overcome this limitation. Juvenile hormone (JH) is an insect-specific hormone that plays key roles in maintaining the larval stage of insects. Hence, JH signaling pathway is considered a suitable target in the development of novel insecticides; however, only a few JH signaling inhibitors (JHSIs) have been reported, and no practical JHSIs have been developed. Here, we established a high-throughput screening (HTS) system for exploration of novel JHSIs using a Bombyx mori cell line (BmN_JF&AR cells) and carried out a large-scale screening in this cell line using a chemical library. The four-step HTS yielded 69 compounds as candidate JHSIs. Topical application of JHSI48 to B. mori larvae caused precocious metamorphosis. In ex vivo culture of the epidermis, JHSI48 suppressed the expression of the Krüppel homolog 1 gene, which is directly activated by JH-liganded receptor. Moreover, JHSI48 caused a parallel rightward shift in the JH response curve, suggesting that JHSI48 possesses a competitive antagonist-like activity. Thus, large-scale HTS using chemical libraries may have applications in development of future insecticides targeting the JH signaling pathway.

Retrospective Analysis of an Experimental High-Throughput Screening Data Set by Recursive Partitioning

2001 ◽  
Vol 3 (3) ◽  
pp. 267-277 ◽  
Author(s):  
A. Michiel van Rhee ◽  
Jon Stocker ◽  
David Printzenhoff ◽  
Chris Creech ◽  
P. Kay Wagoner ◽  
...  
Keyword(s):  
Retrospective Analysis ◽  
High Throughput ◽  
High Throughput Screening ◽  
Recursive Partitioning ◽  
Data Set

Data Analysis of High-Throughput Screening Results:  Application of Multidomain Clustering to the NCI Anti-HIV Data Set

2002 ◽  
Vol 45 (14) ◽  
pp. 3082-3093 ◽  
Author(s):  
Susan Y. Tamura ◽  
Patricia A. Bacha ◽  
Heather S. Gruver ◽  
Ruth F. Nutt
Keyword(s):  
Data Analysis ◽  
High Throughput ◽  
High Throughput Screening ◽  
Data Set ◽  
Anti Hiv

High-Throughput Screening with HyperCyt® Flow Cytometry to Detect Small Molecule Formylpeptide Receptor Ligands

2005 ◽  
Vol 10 (4) ◽  
pp. 374-382 ◽  
Author(s):  
Susan M. Young ◽  
Cristian Bologa ◽  
Eric R. Prossnitz ◽  
Tudor I. Oprea ◽  
Larry A. Sklar ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
High Throughput ◽  
High Throughput Screening ◽  
Receptor Ligands ◽  
Chemical Library ◽  
Assay Sensitivity ◽  
Compound Libraries ◽  
Analysis System ◽  
G Protein Coupled ◽  
Formylpeptide Receptor

High-throughput flow cytometry (HTFC), enabled by faster automated sample processing, represents a promising high- content approach for compound library screening. HyperCyt® is a recently developed automated HTFC analysis system by which cell samples are rapidly aspirated from microplate wells and delivered to the flow cytometer. The formylpeptide receptor (FPR) family of G protein–coupled receptors contributes to the localization and activation of tissue-damaging leukocytes at sites of chronic inflammation. Here, the authors describe development and application of an HTFC screening approach to detect potential anti-inflammatory compounds that block ligand binding to FPR. Using a homogeneous no-wash assay, samples were routinely processed at 1.5 s/well (~2500 cells analyzed/sample), allowing a 96-well plate to be processed in less than 2.5 min. Assay sensitivity and accuracy were validated by detection of a previously documented active compound with relatively low FPR affinity (sulfinpyrazone, inhibition constant [Ki]=14 μM) from among a collection of 880 compounds in the Prestwick Chemical Library. The HyperCyt® system was therefore demonstrated to be a robust, sensitive, and highly quantitative method with which to screen lead compound libraries in a 96-well format.

Hormesis in high-throughput screening of antibacterial compounds in E coli

2010 ◽  
Vol 29 (8) ◽  
pp. 667-677 ◽  
Author(s):  
Edward J Calabrese ◽  
George R Hoffmann ◽  
Edward J Stanek ◽  
Marc A Nascarella
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Antibacterial Agents ◽  
Threshold Model ◽  
Concentration Effects ◽  
Data Set ◽  
E Coli ◽  
Model Predictions ◽  
High Throughput Study ◽  
Repeat Measure

This article assesses the response below a toxicological threshold for 1888 antibacterial agents in Escherichia coli, using 11 concentrations with twofold concentration spacing in a high-throughput study. The data set had important strengths such as low variability in the control (2%—3% SD), a repeat measure of all wells, and a built-in replication. Bacterial growth at concentrations below the toxic threshold is significantly greater than that in the controls, consistent with a hormetic concentration response. These findings, along with analyses of published literature and complementary evaluations of concentration-response model predictions of low-concentration effects in yeast, indicate a lack of support for the broadly and historically accepted threshold model for responses to concentrations below the toxic threshold.

scholarly journals A High-Throughput Screening Triage Workflow to Authenticate a Novel Series of PFKFB3 Inhibitors

2017 ◽  
Vol 23 (1) ◽  
pp. 11-22
Author(s):  
Stephen A. St-Gallay ◽  
Neil Bennett ◽  
Susan E. Critchlow ◽  
Nicola Curtis ◽  
Gareth Davies ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Isothermal Calorimetry ◽  
Binding Mode ◽  
Carbonyl Oxygen ◽  
Enzyme Concentration ◽  
Titration Calorimetry ◽  
X Ray ◽  
X Ray Crystallography ◽  
The Hill

A high-throughput screen (HTS) of human 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) resulted in several series of compounds with the potential for further optimization. Informatics was used to identify active chemotypes with lead-like profiles and remove compounds that commonly occurred as actives in other HTS screens. The activities were confirmed with IC50 measurements from two orthogonal assay technologies, and further analysis of the Hill slopes and comparison of the ratio of IC50 values at 10 times the enzyme concentration were used to identify artifact compounds. Several series of compounds were rejected as they had both high slopes and poor ratios. A small number of compounds representing the different leading series were assessed using isothermal titration calorimetry, and the X-ray crystal structure of the complex with PFKFB3 was solved. The orthogonal assay technology and isothermal calorimetry were demonstrated to be unreliable in identifying false-positive compounds in this case. Presented here is the discovery of the dihydropyrrolopyrimidinone series of compounds as active and novel inhibitors of PFKFB3, shown by X-ray crystallography to bind to the adenosine triphosphate site. The crystal structures of this series also reveal it is possible to flip the binding mode of the compounds, and the alternative orientation can be driven by a sigma-hole interaction between an aromatic chlorine atom and a backbone carbonyl oxygen. These novel inhibitors will enable studies to explore the role of PFKFB3 in driving the glycolytic phenotype of tumors.

Selection and Tuning of a Fast and Simple Phase-Contrast Microscopy Image Segmentation Algorithm for Measuring Myoblast Growth Kinetics in an Automated Manner

2013 ◽  
Vol 19 (4) ◽  
pp. 855-866 ◽  
Author(s):  
Pierre-Marc Juneau ◽  
Alain Garnier ◽  
Carl Duchesne
Keyword(s):  
Cell Cultures ◽  
High Throughput ◽  
Growth Kinetics ◽  
High Throughput Screening ◽  
Phase Contrast ◽  
Segmentation Algorithm ◽  
Phase Contrast Microscopy ◽  
Screening Experiments ◽  
Contrast Microscopy ◽  
Microscopy Images

AbstractAcquiring and processing phase-contrast microscopy images in wide-field long-term live-cell imaging and high-throughput screening applications is still a challenge as the methodology and algorithms used must be fast, simple to use and tune, and as minimally intrusive as possible. In this paper, we developed a simple and fast algorithm to compute the cell-covered surface (degree of confluence) in phase-contrast microscopy images. This segmentation algorithm is based on a range filter of a specified size, a minimum range threshold, and a minimum object size threshold. These parameters were adjusted in order to maximize the F-measure function on a calibration set of 200 hand-segmented images, and its performance was compared with other algorithms proposed in the literature. A set of one million images from 37 myoblast cell cultures under different conditions were processed to obtain their cell-covered surface against time. The data were used to fit exponential and logistic models, and the analysis showed a linear relationship between the kinetic parameters and passage number and highlighted the effect of culture medium quality on cell growth kinetics. This algorithm could be used for real-time monitoring of cell cultures and for high-throughput screening experiments upon adequate tuning.

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