Evidence map›Paper›PMID 33230664›Full record

ArticleJournal of molecular evolution2020

Site-Specific Amino Acid Distributions Follow a Universal Shape.

Mackenzie M Johnson, Claus O Wilke

Abstract read
In one paragraph

Article in Journal of molecular evolution, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. A fitness distribution law for amino-acid replacements.bioRxiv : the preprint server for biology · 2024
    Article
  3. Article
  4. 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

2 authors.

Mackenzie M JohnsonDepartment of Integrative Biology, The University of Texas at Austin, Austin, TX, 78712, USA.ORCID 0000-0002-3915-2023
Claus O WilkeDepartment of Integrative Biology, The University of Texas at Austin, Austin, TX, 78712, USA. wilke@austin.utexas.edu.ORCID 0000-0002-7470-9261

Funding

The biophysical basis of translational selectionR01GM088344 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI BARRICK, JEFFREY EVAN, WILKE, CLAUS O · 2009 to 2023
$3.5M
PREDOCTORAL TRAINING IN BIOMEDICAL BIG DATA SCIENCET32LM012414 · NLM · UNIVERSITY OF TEXAS AT AUSTIN · PI DHILLON, INDERJIT, MEYERS, LAUREN ANCEL · 2016 to 2020
$974k
NIGMS NIH HHS R01 GM088344NLM NIH HHS T32 LM012414
6 · The paper itself

Abstract

In many applications of evolutionary inference, a model of protein evolution needs to be fitted to the amino acid variation at individual sites in a multiple sequence alignment. Most existing models fall into one of two extremes: Either they provide a coarse-grained description that lacks biophysical realism (e.g., dN/dS models), or they require a large number of parameters to be fitted (e.g., mutation-selection models). Here, we ask whether a middle ground is possible: Can we obtain a realistic description of site-specific amino acid frequencies while severely restricting the number of free parameters in the model? We show that a distribution with a single free parameter can accurately capture the variation in amino acid frequency at most sites in an alignment, as long as we are willing to restrict our analysis to predicting amino acid frequencies by rank rather than by amino acid identity. This result holds equally well both in alignments of empirical protein sequences and of sequences evolved under a biophysically realistic all-atom force field. Our analysis reveals a near universal shape of the frequency distributions of amino acids. This insight has the potential to lead to new models of evolution that have both increased realism and a limited number of free parameters.

Indexed as

Amino AcidsEvolution, MolecularAmino Acid SequenceAmino Acid SubstitutionModels, GeneticSequence AlignmentAmino AcidsAmino-acid distributionsEvolutionary modelingProtein site variability

Identifiers

PMID33230664
PMCPMC7717668

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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.