ArticleMolecular biology and evolution2025
Reduced Amino Acid Substitution Matrices Find Traces of Ancient Coding Alphabets in Modern Day Proteins.
Article in Molecular biology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Avoiding Catastrophic Mutations Accurately Predicts Amino Acid to Codon Pairing.Journal of molecular evolution · 2026Article
- Structural Enzymology, Phylogenetics, Differentiation, and Symbolic Reflexivity at the Dawn of Biology.Genome biology and evolution · 2025Article
- Aminoacyl-tRNA synthetase urzymes optimized by deep learning behave as a quasispecies.Structural dynamics (Melville, N.Y.) · 2025Article
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4 authors.
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Abstract
All known living systems make proteins from the same 20 canonically coded amino acids, but this was not always the case. Early genetic coding systems likely operated with a restricted pool of amino acid types and limited means to distinguish between them. Despite this, amino acid substitution models like LG and WAG all assume a constant coding alphabet over time. That makes them especially inappropriate for the aminoacyl-tRNA synthetases (aaRS)-the enzymes that govern translation. To address this limitation, we created a class of substitution models that account for evolutionary changes in the coding alphabet size by defining the transition from 19 states in a past epoch to 20 now. We use a Bayesian phylogenetic framework to improve phylogeny estimation and testing of this two-alphabet hypothesis. The hypothesis was strongly rejected by datasets composed exclusively of "young" eukaryotic proteins. It was generally supported by "old" (aaRS and non-aaRS) proteins whose origins date from before the last universal common ancestor. Standard methods overestimate the divergence ages of proteins that originated under reduced coding alphabets in both simulated and aaRS alignments. The new model provides a timeline slightly more consistent with the Earth's history. Our findings suggest that aaRS functional bifurcation events can explain much of the genetic code's evolution, but there remain other unknown forces at play too. This work provides a robust, seamless framework for reconstructing phylogenies from ancient protein datasets and offers further insights into the dawn of molecular biology.
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