scholarly journals BioAssay Ontology Annotations Facilitate Cross-Analysis of Diverse High-Throughput Screening Data Sets

2011 ◽  
Vol 16 (4) ◽  
pp. 415-426 ◽  
Author(s):  
Stephan C. Schürer ◽  
Uma Vempati ◽  
Robin Smith ◽  
Mark Southern ◽  
Vance Lemmon
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
High Throughput Screening ◽  
Data Sets ◽  
Large Set ◽  
Chemical Probes ◽  
Great Flexibility ◽  
Data Repositories ◽  
Data Format ◽  
Entry Points

High-throughput screening data repositories, such as PubChem, represent valuable resources for the development of small-molecule chemical probes and can serve as entry points for drug discovery programs. Although the loose data format offered by PubChem allows for great flexibility, important annotations, such as the assay format and technologies employed, are not explicitly indexed. The authors have previously developed a BioAssay Ontology (BAO) and curated more than 350 assays with standardized BAO terms. Here they describe the use of BAO annotations to analyze a large set of assays that employ luciferase- and β-lactamase–based technologies. They identified promiscuous chemotypes pertaining to different subcategories of assays and specific mechanisms by which these chemotypes interfere in reporter gene assays. Results show that the data in PubChem can be used to identify promiscuous compounds that interfere nonspecifically with particular technologies. Furthermore, they show that BAO is a valuable toolset for the identification of related assays and for the systematic generation of insights that are beyond the scope of individual assays or screening campaigns.

scholarly journals Statistical models for identifying frequent hitters in high throughput screening

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Samuel Goodwin ◽  
Golnaz Shahtahmassebi ◽  
Quentin S. Hanley
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
High Throughput Screening ◽  
Negative Binomial ◽  
Data Sets ◽  
Individual Compound ◽  
Data Set ◽  
Binomial Distributions ◽  
Compound Libraries ◽  
Large Numbers

Abstract High throughput screening (HTS) interrogates compound libraries to find those that are “active” in an assay. To better understand compound behavior in HTS, we assessed an existing binomial survivor function (BSF) model of “frequent hitters” using 872 publicly available HTS data sets. We found large numbers of “infrequent hitters” using this model leading us to reject the BSF for identifying “frequent hitters.” As alternatives, we investigated generalized logistic, gamma, and negative binomial distributions as models for compound behavior. The gamma model reduced the proportion of both frequent and infrequent hitters relative to the BSF. Within this data set, conclusions about individual compound behavior were limited by the number of times individual compounds were tested (1–1613 times) and disproportionate testing of some compounds. Specifically, most tests (78%) were on a 309,847-compound subset (17.6% of compounds) each tested ≥ 300 times. We concluded that the disproportionate retesting of some compounds represents compound repurposing at scale rather than drug discovery. The approach to drug discovery represented by these 872 data sets characterizes the assays well by challenging them with many compounds while each compound is characterized poorly with a single assay. Aggregating the testing information from each compound across the multiple screens yielded a continuum with no clear boundary between normal and frequent hitting compounds.

Upscaling and Automation of Electrophysiology: Toward High Throughput Screening in Ion Channel Drug Discovery

2003 ◽  
Vol 9 (1) ◽  
pp. 49-58
Author(s):  
Margit Asmild ◽  
Nicholas Oswald ◽  
Karen M. Krzywkowski ◽  
Søren Friis ◽  
Rasmus B. Jacobsen ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Ion Channel ◽  
High Throughput ◽  
High Throughput Screening

High-Throughput Affinity Selection Mass Spectrometry Using SAMDI-MS to Identify Small-Molecule Binders of the Human Rhinovirus 3C Protease

2021 ◽  
pp. 247255522110232
Author(s):  
Michael D. Scholle ◽  
Doug McLaughlin ◽  
Zachary A. Gurard-Levin
Keyword(s):  
Mass Spectrometry ◽  
Drug Discovery ◽  
High Throughput ◽  
High Throughput Screening ◽  
Human Rhinovirus ◽  
Binding Potential ◽  
Affinity Selection ◽  
Response Curves ◽  
Desorption Ionization ◽  
Self Assembled

Affinity selection mass spectrometry (ASMS) has emerged as a powerful high-throughput screening tool used in drug discovery to identify novel ligands against therapeutic targets. This report describes the first high-throughput screen using a novel self-assembled monolayer desorption ionization (SAMDI)–ASMS methodology to reveal ligands for the human rhinovirus 3C (HRV3C) protease. The approach combines self-assembled monolayers of alkanethiolates on gold with matrix-assisted laser desorption ionization time-of-flight (MALDI TOF) mass spectrometry (MS), a technique termed SAMDI-ASMS. The primary screen of more than 100,000 compounds in pools of 8 compounds per well was completed in less than 8 h, and informs on the binding potential and selectivity of each compound. Initial hits were confirmed in follow-up SAMDI-ASMS experiments in single-concentration and dose–response curves. The ligands identified by SAMDI-ASMS were further validated using differential scanning fluorimetry (DSF) and in functional protease assays against HRV3C and the related SARS-CoV-2 3CLpro enzyme. SAMDI-ASMS offers key benefits for drug discovery over traditional ASMS approaches, including the high-throughput workflow and readout, minimizing compound misbehavior by using smaller compound pools, and up to a 50-fold reduction in reagent consumption. The flexibility of this novel technology opens avenues for high-throughput ASMS assays of any target, thereby accelerating drug discovery for diverse diseases.

scholarly journals Development of a Robust High-Throughput Screening Platform for Inhibitors of the Striatal-Enriched Tyrosine Phosphatase (STEP)

2021 ◽  
Vol 22 (9) ◽  
pp. 4417
Author(s):  
Lester J Lambert ◽  
Stefan Grotegut ◽  
Maria Celeridad ◽  
Palak Gosalia ◽  
Laurent JS De Backer ◽  
...  
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
Tyrosine Kinases ◽  
High Throughput Screening ◽  
Kinase Inhibitors ◽  
Tyrosine Phosphatase ◽  
Protein Tyrosine Phosphatases ◽  
Synaptic Function ◽  
Label Free ◽  
Protein Tyrosine

Many human diseases are the result of abnormal expression or activation of protein tyrosine kinases (PTKs) and protein tyrosine phosphatases (PTPs). Not surprisingly, more than 30 tyrosine kinase inhibitors (TKIs) are currently in clinical use and provide unique treatment options for many patients. PTPs on the other hand have long been regarded as “undruggable” and only recently have gained increased attention in drug discovery. Striatal-enriched tyrosine phosphatase (STEP) is a neuron-specific PTP that is overactive in Alzheimer’s disease (AD) and other neurodegenerative and neuropsychiatric disorders, including Parkinson’s disease, schizophrenia, and fragile X syndrome. An emergent model suggests that the increase in STEP activity interferes with synaptic function and contributes to the characteristic cognitive and behavioral deficits present in these diseases. Prior efforts to generate STEP inhibitors with properties that warrant clinical development have largely failed. To identify novel STEP inhibitor scaffolds, we developed a biophysical, label-free high-throughput screening (HTS) platform based on the protein thermal shift (PTS) technology. In contrast to conventional HTS using STEP enzymatic assays, we found the PTS platform highly robust and capable of identifying true hits with confirmed STEP inhibitory activity and selectivity. This new platform promises to greatly advance STEP drug discovery and should be applicable to other PTP targets.

The Discovery Channel: microfluidics and microengineered systems in drug screening

2015 ◽  
Vol 7 (3) ◽  
pp. 285-288 ◽  
Author(s):  
Christopher Moraes
Keyword(s):  
Drug Discovery ◽  
Engineering Design ◽  
High Throughput ◽  
Drug Screening ◽  
High Throughput Screening ◽  
Recent Literature ◽  
Analytical Strategies ◽  
Discovery Pipeline

We highlight exciting findings and promising approaches in the recent literature in which researchers integrate advanced micro-engineering, design, and analytical strategies to improve the relevance and utility of high-throughput screening in the drug discovery pipeline.

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