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Record W3010820094 · doi:10.1002/chem.202001193

Mechanochemical Synthesis of Short DNA Fragments

2020· article· en· W3010820094 on OpenAlexafffund
James D. Thorpe, Daniel O’Reilly, Tomislav Friščić, Masad J. Damha

Bibliographic record

VenueChemistry - A European Journal · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhosphoramiditePhosphonateChemistryMechanochemistrySulfurDNAYield (engineering)ReagentMonomerProtecting groupCombinatorial chemistryOne-pot synthesisNucleic acidSolventOligonucleotideOrganic chemistryCatalysisMaterials scienceBiochemistry

Abstract

fetched live from OpenAlex

We demonstrate the first mechanochemical synthesis of DNA fragments by ball milling, enabling the synthesis of oligomers of controllable sequence and length using multi-step, one-pot reactions, without bulk solvent or the need to isolate intermediates. Mechanochemistry allowed for coupling of phosphoramidite monomers to the 5'-hydroxyl group of nucleosides, iodine/water oxidation of the resulting phosphite triester linkage, and removal of the 5'-dimethoxytrityl (DMTr) protecting group in situ in good yields (up to 60 % over three steps) to produce DNA dimers in a one-pot manner. H-Phosphonate chemistry under milling conditions enabled coupling and protection of the H-phosphonate linkage, as well as removal of the 5'-DMTr protecting group in situ, enabling a one-pot process with good yields (up to 65 % over three steps, or ca. 87 % per step). Sulfurization of the internucleotide linkage was possible using elemental sulfur (S8) or sulfur transfer reagents, yielding the target DNA phosphorothioate dimers in good yield (up to 80 % over two steps). This work opens the door to creation of solvent-free synthesis methodologies for DNA and RNA therapeutics.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.001

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 head0.014
GPT teacher head0.208
Teacher spread0.194 · 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

Citations28
Published2020
Admission routes2
Has abstractyes

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Same venueChemistry - A European JournalSame topicBacteriophages and microbial interactionsFrench-language works237,207