Evidence map›Paper›PMID 32609328›Full record

ArticleBioinformatics (Oxford, England)2020

Network analysis of synonymous codon usage.

Khalique Newaz, Gabriel Wright, Jacob Piland, Jun Li, Patricia L Clark, Scott J Emrich, Tijana Milenković

Open access · greenAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.1field-weighted citation impact, top 58% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Khalique NewazDepartment of Computer Science and Engineering.
Gabriel WrightDepartment of Computer Science and Engineering.
Jacob PilandDepartment of Computer Science and Engineering.
Jun LiDepartment of Applied and Computational Mathematics and Statistics.
Patricia L ClarkDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA.
Scott J EmrichDepartment of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA.
Tijana MilenkovićDepartment of Computer Science and Engineering.
Center for Global Health · USUniversity of Notre Dame · USUniversity of Tennessee at Knoxville · US

Funding

Integrative computational framework for pattern mining in big -omics data: linking synonymous codon usage to protein biogenesisR01GM120733 · NIGMS · UNIVERSITY OF NOTRE DAME · PI CLARK, PATRICIA LOUISE, EMRICH, SCOTT · 2016 to 2019
$1.1M
NIGMS NIH HHS R01 GM120733
6 · The paper itself

Abstract

motivationMost amino acids are encoded by multiple synonymous codons, some of which are used more rarely than others. Analyses of positions of such rare codons in protein sequences revealed that rare codons can impact co-translational protein folding and that positions of some rare codons are evolutionarily conserved. Analyses of their positions in protein 3-dimensional structures, which are richer in biochemical information than sequences alone, might further explain the role of rare codons in protein folding.

resultsWe model protein structures as networks and use network centrality to measure the structural position of an amino acid. We first validate that amino acids buried within the structural core are network-central, and those on the surface are not. Then, we study potential differences between network centralities and thus structural positions of amino acids encoded by conserved rare, non-conserved rare and commonly used codons. We find that in 84% of proteins, the three codon categories occupy significantly different structural positions. We examine protein groups showing different codon centrality trends, i.e. different relationships between structural positions of the three codon categories. We see several cases of all proteins from our data with some structural or functional property being in the same group. Also, we see a case of all proteins in some group having the same property. Our work shows that codon usage is linked to the final protein structure and thus possibly to co-translational protein folding. AVAILABILITY AND IMPLEMENTATION: https://nd.edu/∼cone/CodonUsage/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Codon UsageProtein FoldingAmino Acid SequenceCodonProteinsCodonProteins

Identifiers

PMID32609328
PMCPMC7750956
OpenAlexW2953990100

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.