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Record W3128774536 · doi:10.1101/2021.01.31.429023

Mn <sup>2+</sup> coordinates Cap-0-RNA to align substrates for efficient 2′- <i>O</i> -methyl transfer by SARS-CoV-2 nsp16

2021· preprint· en· W3128774536 on OpenAlexfundno aff
G. Minasov, Mónica Rosas‐Lemus, L. Shuvalova, Nicole L. Inniss, J.S. Brunzelle, Courtney M. Daczkowski, Paul Hoover, Andrew D. Mesecar, K.J.F. Satchell

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institutes of HealthUniversity of TorontoNational Institute of Allergy and Infectious DiseasesChicago Biomedical Consortium
KeywordsMethyltransferaseRNAChemistryMethylationNucleotideFive-prime capCoronavirusStereochemistryBiologyCrystallographyBiochemistryDNARNA-dependent RNA polymeraseCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

Abstract Capping viral messenger RNAs is essential for efficient translation and prevents their detection by host innate immune responses. For SARS-CoV-2, RNA capping includes 2′- O -methylation of the first ribonucleotide by methyltransferase nsp16 in complex with activator nsp10. The reaction requires substrates, a short RNA and SAM, and is catalyzed by divalent cations, with preference for Mn 2+ . Crystal structures of nsp16-nsp10 with capped RNAs revealed a critical role of metal ions in stabilizing interactions between ribonucleotides and nsp16, resulting in precise alignment of the substrates for methyl transfer. An aspartate residue that is highly conserved among coronaviruses alters the backbone conformation of the capped RNA in the binding groove. This aspartate is absent in mammalian methyltransferases and is a promising site for designing coronavirus-specific inhibitors.

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 score0.003
Threshold uncertainty score0.010

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)0.0030.001

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 head0.241
Teacher spread0.227 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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