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Record W3169873395 · doi:10.1002/cphc.202100333

Influence of the Number, Nature and Position of Methyl Posttranscriptional Modifications on Nucleobase Stacking in RNA

2021· article· en· W3169873395 on OpenAlexaff
Deepika Kagra, Amanpreet Singh Mahmi, N. V. Suresh Kumar, Preethi Seelam Prabhakar, Purshotam Sharma

Bibliographic record

VenueChemPhysChem · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsNucleobaseStackingChemistryRNAStereochemistryDNABiochemistryGeneOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract DFT calculations are employed to quantify the influence of the presence, number, nature, and position of posttranscriptional methylation on stacking strength of RNA bases. We carry out detailed potential energy scans of the variation in stacking energies with characteristic geometrical parameters in three categories of forty stacked dimers – canonical base homodimers (N||N), methylated base homodimers (mN||mN) and heterodimers of canonical bases and methylated counterparts (N||mN). Our analysis reveals that neutral methylation invariably enhances the stacking of bases. Further, N||mN stacking is stronger than mN||mN stacking and charged N||mN exhibit strongest stacking among all dimers. This indicates that methylations greatly enhance stacking when dispersed in RNA sequences containing identical bases. Comparison of stacks involving singly‐ and doubly‐methylated purines reveal that incremental methylation enhances the stacking in neutral dimers. Although methylation at the carbon position of neutral pyrimidine dimers greatly enhances the stacking, methylation on the 5‐membered ring imparts better stacking compared to methylation on the 6‐membered ring in adenine dimers. However, methylation at the ring nitrogen (N 1 ) provides better stacking than the amino group (N 2 ) in guanine dimers. Our results thus highlight subtle structural effects of methylation on RNA base stacking and will enhance our understanding of the physicochemical principles of RNA structure and dynamics.

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 score0.079
Threshold uncertainty score0.208

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.265
Teacher spread0.255 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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