Evidence map›Paper›PMID 32060385›Full record

ArticleScientific reports2020

Protein design under competing conditions for the availability of amino acids.

Francesca Nerattini, Luca Tubiana, Chiara Cardelli, Valentino Bianco, Christoph Dellago, Ivan Coluzza

Abstract read
In one paragraph

Article in Scientific reports, 2020. 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

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

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.

Francesca NerattiniFaculty of Physics, University of Vienna, Boltzmanngasse 5, 1090, Vienna, Austria.
Luca TubianaFaculty of Physics, University of Vienna, Boltzmanngasse 5, 1090, Vienna, Austria.
Chiara CardelliFaculty of Physics, University of Vienna, Boltzmanngasse 5, 1090, Vienna, Austria.
Valentino BiancoFaculty of Physics, University of Vienna, Boltzmanngasse 5, 1090, Vienna, Austria.
Christoph DellagoFaculty of Physics, University of Vienna, Boltzmanngasse 5, 1090, Vienna, Austria.
Ivan ColuzzaCenter for Cooperative Research in Biomaterials (CIC biomaGUNE), Basque Research and Technology Alliance (BRTA), Paseo Miramon 182, 20014, San Sebastian, Spain. icoluzza@cicbiomagune.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Isolating the properties of proteins that allow them to convert sequence into the structure is a long-lasting biophysical problem. In particular, studies focused extensively on the effect of a reduced alphabet size on the folding properties. However, the natural alphabet is a compromise between versatility and optimisation of the available resources. Here, for the first time, we include the impact of the relative availability of the amino acids to extract from the 20 letters the core necessary for protein stability. We present a computational protein design scheme that involves the competition for resources between a protein and a potential interaction partner that, additionally, gives us the chance to investigate the effect of the reduced alphabet on protein-protein interactions. We devise a scheme that automatically identifies the optimal reduced set of letters for the design of the protein, and we observe that even alphabets reduced down to 4 letters allow for single protein folding. However, it is only with 6 letters that we achieve optimal folding, thus recovering experimental observations. Additionally, we notice that the binding between the protein and a potential interaction partner could not be avoided with the investigated reduced alphabets. Therefore, we suggest that aggregation could have been a driving force in the evolution of the large protein alphabet.

Indexed as

Computational BiologyProtein ConformationProtein FoldingAlgorithmsAminesAmino AcidsAmino Acid SequenceProteinsSequence Analysis, ProteinAminesAmino AcidsProteins

Identifiers

PMID32060385
PMCPMC7021711

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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.