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Record W2051766214 · doi:10.2174/1875397300801010002

The Use of AlphaScreen Technology in HTS: Current Status

2008· article· en· W2051766214 on OpenAlexaff
Richard M. Eglen, Terry Reisine, Philippe Roby, Nathalie Rouleau, Chantal Illy, Roger Bossé, Martina Bielefeld

Bibliographic record

VenueCurrent Chemical Genomics · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicbioluminescence and chemiluminescence research
Canadian institutionsPerkinElmer Biosignal
Fundersnot available
KeywordsChemistryPeptideSmall moleculeAnalyteProtein kinase APhosphorylationHigh-throughput screeningG protein-coupled receptorBiophysicsCombinatorial chemistryBiochemistrySignal transductionBiologyChromatography

Abstract

fetched live from OpenAlex

AlphaScreen (Amplified Luminescent Proximity Homogeneous Assay Screen) is versatile assay technology developed to measuring analytes using a homogenous protocol. This technology is an example of a bead-based proximity assay and was developed from a diagnostic assay technology known as LOCI (Luminescent Oxygen Channeling Assay). Here, singlet oxygen molecules, generated by high energy irradiation of Donor beads, travel over a constrained distance (approx. 200 nm) to Acceptor beads. This results in excitation of a cascading series of chemical reactions, ultimately causing generation of a chemiluminescent signal.In the past decade, a wide variety of applications has been reported, ranging from detection of analytes involved in cell signaling, including protein:protein, protein:peptide, protein:small molecule or peptide:peptide interactions. Numerous homogeneous HTS-optimized assays have been reported using the approach, including generation of second messengers (such as accumulation of cyclic AMP, cyclic GMP, inositol [1, 4, 5] trisphosphate or phosphorylated ERK) from liganded GPCRs or tyrosine kinase receptors, post-translational modification of proteins (such as proteolytic cleavage, phosphorylation, ubiquination and sumoylation) as well as protein-protein and protein-nucleic acid interactions.Recently, the basic AlphaScreen technology was extended in that the chemistry of the Acceptor bead was modified such that emitted light is more intense and spectrally defined, thereby markedly reducing interference from biological fluid matrices (such as trace hemolysis in serum and plasma). In this format, referred to as AlphaLISA, it provides an alternative technology to classical ELISA assays and is suitable for high throughput automated fluid dispensing and detection systems.Collectively, AlphaScreen and AlphaLISA technologies provide a facile assay platform with which one can quantitate complex cellular processes using simple no-wash microtiter plate based assays. They provide the means by which large compound libraries can be screened in a high throughput fashion at a diverse range of therapeutically important targets, often not readily undertaken using other homogeneous assay technologies. This review assesses the current status of the technology in drug discovery, in general, and high throughput screening (HTS), in particular.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.004
Scholarly communication0.0050.004
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.068
GPT teacher head0.308
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations257
Published2008
Admission routes1
Has abstractyes

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