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Record W2800554653 · doi:10.3934/biophy.2018.2.125

The effect of different divalent cations on the kinetics and fidelity of <em>Bacillus stearothermophilus</em> DNA polymerase

2018· article· en· W2800554653 on OpenAlexaff
Ashwani Kumar Vashishtha, William H. Konigsberg

Bibliographic record

VenueAIMS Biophysics · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsConcordia University
FundersNational Institute of General Medical Sciences
KeywordsDivalentDNAChemistryDNA polymeraseCrystallographyStereochemistryBiochemistry

Abstract

fetched live from OpenAlex

Although Mg2+ is the metal ion that functions as the cofactor for DNA polymerases (DNA pols) in vivo, Mn2+ can also serve in this capacity but it reduces base discrimination. Metal ions aside from Mg2+ or Mn2+ can act as cofactors for some DNA pols but not for others. Here we report on the ability of several divalent metal ions to substitute for Mg2+ or Mn2+ with BST DNA polymerase (BST pol), an A family DNA pol. We selected the metal ions based on whether they had previously been shown to be effective with other DNA pols. We found that Co2+ and Cd2+ were the only cations tested that could replace Mg2+ or Mn2+. When Co2+ was substituted for Mg2+, the incorporation efficiency for correct dNTPs increased 6-fold but for incorrect dNTPs there was a decrease which depended on the incoming dNTP. With Mn2+, base selectivity was impaired compared to Co2+ and Cd2+. In addition, Co2+ and Mn2+ helped BST pol to catalyze primer-extension past a mismatch. Finally both Co2+ and Mn2+ enhanced ground-state binding of both correct and incorrect dNTPs to BST pol: Dideoxy terminated primer-template complexes.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.221
Teacher spread0.215 · 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

Citations17
Published2018
Admission routes1
Has abstractyes

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