Evidence map›Paper›PMID 37399326›Full record

ArticleGenome biology and evolution2023

Highly Abundant Proteins Are Highly Thermostable.

Agusto R Luzuriaga-Neira, Andrew M Ritchie, Bryan L Payne, Oliver Carrillo-Parramon, David A Liberles, David Alvarez-Ponce

Abstract read
In one paragraph

Article in Genome biology and evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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

6 authors.

Agusto R Luzuriaga-NeiraBiology Department, University of Nevada, Reno, USA.
Andrew M RitchieDepartment of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, Pennsylvania, USA.
Bryan L PayneBiology Department, University of Nevada, Reno, USA.
Oliver Carrillo-ParramonDepartment of Physics, Universitat Politècnica de Catalunya, Barcelona, Spain.
David A LiberlesDepartment of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, Pennsylvania, USA.ORCID 0000-0003-3487-8826
David Alvarez-PonceBiology Department, University of Nevada, Reno, USA.ORCID 0000-0002-8729-1036

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Highly abundant proteins tend to evolve slowly (a trend called E-R anticorrelation), and a number of hypotheses have been proposed to explain this phenomenon. The misfolding avoidance hypothesis attributes the E-R anticorrelation to the abundance-dependent toxic effects of protein misfolding. To avoid these toxic effects, protein sequences (particularly those of highly expressed proteins) would be under selection to fold properly. One prediction of the misfolding avoidance hypothesis is that highly abundant proteins should exhibit high thermostability (i.e., a highly negative free energy of folding, ΔG). Thus far, only a handful of analyses have tested for a relationship between protein abundance and thermostability, producing contradictory results. These analyses have been limited by 1) the scarcity of ΔG data, 2) the fact that these data have been obtained by different laboratories and under different experimental conditions, 3) the problems associated with using proteins' melting energy (Tm) as a proxy for ΔG, and 4) the difficulty of controlling for potentially confounding variables. Here, we use computational methods to compare the free energy of folding of pairs of human-mouse orthologous proteins with different expression levels. Even though the effect size is limited, the most highly expressed ortholog is often the one with a more negative ΔG of folding, indicating that highly expressed proteins are often more thermostable.

Indexed as

Protein FoldingProteinsAnimalsHumansMiceProteinsexpression levelsmisfolding avoidance hypothesisprotein thermostabilityrates of evolutiontranslational robustness hypothesis

Identifiers

PMID37399326
PMCPMC10317291

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