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Record W3186023394 · doi:10.1016/j.csbj.2021.07.012

Quantitative elucidation of associations between nucleotide identity and physicochemical properties of amino acids and the functional insight

2021· article· en· W3186023394 on OpenAlexfundno aff
Yan-Ting Jin, Tian-Yue Jin, Zhi-Li Zhang, Yuan‐Nong Ye, Zixin Deng, Ju Wang, Feng‐Biao Guo

Bibliographic record

VenueComputational and Structural Biotechnology Journal · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaMinistry of Science and Technology of the People's Republic of ChinaInstitute of GeneticsNational Natural Science Foundation of China
KeywordsAmino acidNucleotideCodon usage biasGenomeFunction (biology)GeneBiologyNucleobaseGeneticsAmino acid residueComputational biologyPeptide sequenceBiochemistryChemistryDNA

Abstract

fetched live from OpenAlex

Studies on codon property would deepen our understanding of the origin of primitive life and enlighten biotechnical application. Here, we proposed a quantitative measurement of codon-amino acid association and found that seven out of 13 physicochemical properties have stronger associations with the nucleotide identity at the second codon position, indicating that protein structure and function may associate more closely with it than the other two sites. When extending the effect of codon-amino acid association to protein level, it was found that the correlation between the second codon position (measured by the relative frequencies of nucleobase T and A at this codon site) and hydrophobicity (by the form of GRAVY value) became stronger with 96% genomes having R > 0.90 and p < 1e-60. Furthermore, we revealed that informational genes encoding proteins have lower GRAVY values than operational proteins (p < 3e-37) in both prokaryotic and eukaryotic genomes. The above results reveal a complete link from codon identity (A2 versus T2) to amino acid property (hydrophilic versus hydrophobic) and then to protein functions (informational versus operational). Hence, our work may help to understand how the nucleotide sequence determines protein function.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.022
GPT teacher head0.250
Teacher spread0.228 · 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 designSimulation or modeling
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

Citations9
Published2021
Admission routes1
Has abstractyes

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