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Other literature type . 2026
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2026
License: CC BY
Data sources: Datacite
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Proteome hydrophobicity and effective codon usage (ENC) in major biological groups

Authors: Ivan Zucconelli;

Proteome hydrophobicity and effective codon usage (ENC) in major biological groups

Abstract

Codon usage bias is commonly studied in relation to DNA composition, while its association with the physicochemical properties of the encoded proteins has been explored to a much lesser extent. In this work, we analyze, at the taxonomic level, the relationship between the average proteome hydrophobicity, measured according to the Kyte–Doolittle scale, and the Effective Number of Codons (ENC). The analysis is based exclusively on median values derived from the aggregated statistics provided by the CompoDynamics database. The representation of the nine major biological groups in the hydrophobicity–ENC space reveals a structured and non-random distribution, with distinct regions occupied by Archaea, Bacteria, and eukaryotes. Viruses are located within the region associated with eukaryotic groups, consistently with their dependence on host translational systems. These results indicate that simple aggregated metrics are sufficient to relate the degree of codon usage degeneracy to the global physical and chemical properties of proteomes. This approach may offer a complementary perspective for the large-scale study of codon usage bias.

Keywords

codon usage, Effective Number of Codons, Proteome hydrophobicity, Codon Usage

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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