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Record W3153114342 · doi:10.24908/iqurcp.10551

Investigating Binding Mechanisms of Small Molecules to Quadruplex DNA

2018· article· en· W3153114342 on OpenAlexvenueno aff
Alana M. M. Rangaswamy

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsG-quadruplexBinding constantFluorescenceChemistryDNAIntercalation (chemistry)Fluorescence anisotropyMoleculeGuanineTitrationBinding siteStereochemistryNucleotideMembraneOrganic chemistryBiochemistryGene

Abstract

fetched live from OpenAlex

Guanine quadruplexes (G4) are dynamic structures found naturally in guanine-rich DNA. When folded, they have been found to block the expression of genes related to diseases including cancer1 and are therefore of significant interest in the field of biomedical research. Our research group has developed a family of chemical binders which strongly stabilize folded G4. This project focuses on quantifying the interaction of these binders with various quadruplexes, through their binding constant (a measure of relative preference for the bound vs unbound state). This constants can be determined through the use of a Fluorescence Intercalation Displacement (FID) biophysical assay,2 a method which measures the competitive binding of the binder molecule and a fluorescent probe to the quadruplex (see figure 1). As a preliminary step, we perform direct titrations of the fluorescent probe, Thiazole Orange (TO), with quadruplex DNA, to determine its binding constant and TO:DNA stoichiometry. TO fluoresces only when bound to a substrate,3 allowing us to track the formation of the TO*DNA complex through an increase in fluorescence. In the FID titration, however, the binder displaces the fluorescent probe, and a decrease in fluorescence intensity is observed. We also discuss mathematical methods used to fit the experimental data in order to determine binding constants for both the fluorescent probe and our binders. A robust model should give evidence in support of the expected binding phenomena. References 1. Hurley, L. et. al. The Febs Journal, 2010, 277, 3459-3469 2. Monchaud, D. et. al. Biochimie, 2008, 90: 1209-1223 3. Yaron, D. et. al. The Journal of Physical Chemistry A. 2008, 112, 9692-9701

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.079
GPT teacher head0.348
Teacher spread0.269 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2018
Admission routes1
Has abstractyes

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