Evidence map›Paper›PMID 41904309›Full record

ArticleScientific reports2026

An information-theoretic argument for the restriction of the current biological alphabets to 4 nucleotides and 20 amino acids.

Ezequiel Alejandro Galpern, Diego Ulises Ferreiro, Ignacio Enrique Sánchez

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Ezequiel Alejandro GalpernFacultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Laboratorio de Fisiología de Proteínas, Universidad de Buenos Aires, Buenos Aires, Argentina.ORCID http://orcid.org/0000-0001-9516-3985
Diego Ulises FerreiroFacultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Laboratorio de Fisiología de Proteínas, Universidad de Buenos Aires, Buenos Aires, Argentina. ferreiro@qb.fcen.uba.ar.ORCID http://orcid.org/0000-0002-7869-4247
Ignacio Enrique SánchezFacultad de Ciencias Exactas y Naturales, Departamento de Química Biológica, Laboratorio de Fisiología de Proteínas, Universidad de Buenos Aires, Buenos Aires, Argentina. isanchez@qb.fcen.uba.ar.ORCID http://orcid.org/0000-0003-4284-9013

Funding

Consejo Nacional de Investigaciones Científicas y Técnicas PIP2022-2024-11220210100704COUniversidad de Buenos Aires UBACyT 20020220200106BA
6 · The paper itself

Abstract

Life as we know it is based on foldable biopolymers encoded with just 4 nucleotides or 20 amino acids. Evolution of these biopolymers requires effective and fast search of both the conformational space for folding and the sequence space for evolution. Energy landscape theory links the free energy of the possible polymer sequences and conformations with its ability to fold, while molecular information theory provides connections between conformational entropy and sequence entropy. Combining these two theories provides constraints to the alphabet size of an evolving biopolymer, given its physico-chemical properties. Empirical estimations of the size of the effective sequence and conformational spaces of foldable proteins and RNA show that the observed alphabet sizes agree with the theoretical predictions and are just large enough to allow for biopolymer evolution. In this scenario, one effective digital alphabet letter in the sequence landscape maps to one effective analog monomer configuration in the conformational landscape. We also use the current views on genetic code evolution to explore scenarios for biopolymers in the early stages of life. We find that primitive genetic systems coding for smaller amino acid alphabets may have led to a prominent presence of intrinsically disordered proteins.

Indexed as

Amino AcidsInformation TheoryNucleotidesBiopolymersEntropyEvolution, MolecularGenetic CodeProtein FoldingProteinsRNAAmino AcidsBiopolymersNucleotidesProteinsRNABiopolymerGenetic codeRandom energy model

Identifiers

PMID41904309
PMCPMC13039375

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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.