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Record W2976858486 · doi:10.1021/acschembio.9b00237

Selection of 2'-Deoxy-2'-Fluoroarabino Nucleic Acid (FANA) Aptamers that Bind HIV-1 Integrase with Picomolar Affinity

2019· article· en· W2976858486 on OpenAlexfundno aff
Kevin Rose, Irani Alves Ferreira‐Bravo, Min Li, Robert Craigie, Mark A. Ditzler, Philipp Holliger, Jeffrey J. DeStefano

Bibliographic record

VenueACS Chemical Biology · 2019
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesMedical Research Council CanadaDivision of Intramural Research, National Institute of Allergy and Infectious Diseases
KeywordsIntegraseAptamerNucleic acidHuman immunodeficiency virus (HIV)Selection (genetic algorithm)Computational biologyVirologyChemistryBiologyBiochemistryMolecular biologyComputer science

Abstract

fetched live from OpenAlex

. Comparisons to published HIV-1 IN RNA and DNA aptamers as well as IN genomic binding partners indicated that FANA aptamers bound more than 2 orders of magnitude more tightly to IN. Using a combination of RNA folding algorithms and covariation analysis, all strong binding aptamers demonstrated a common four-way junction structure, despite significant sequence variation. IN aptamers were selected from the same starting library as FA1, a FANA aptamer that binds with pM affinity to HIV-1 Reverse Transcriptase (RT). It contains a 20-nucleotide 5' DNA sequence followed by 59 FANA nucleotides. IN-1.1 (one of the selected aptamers) potently inhibited IN activity and intasome formation in vitro. Replacing the FANA nucleotides of IN-1.1 with 2'-fluororibonucleic acid (F-RNA), which has the same chemical formula but with a ribose rather than arabinose sugar conformation, dramatically reduced binding, suggesting that FANA adopts unique structural conformations that promote binding to HIV-1 IN.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.373
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.234
Teacher spread0.223 · 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 teacher head, 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

Citations46
Published2019
Admission routes1
Has abstractyes

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