Evidence map›Paper›PMID 42579495›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

The history of enzyme evolution embedded in metabolism.

Tatsuya Corlett, Harrison B Smith, Eric Smith, Joshua E Goldford, Liam M Longo

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Contrastive learning unites sequence and structure in a global representation of protein space.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. 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

5 authors.

Tatsuya CorlettEarth-Life Science Institute, Institute of Science Tokyo, Tokyo 152-8550, Japan.
Harrison B SmithEarth-Life Science Institute, Institute of Science Tokyo, Tokyo 152-8550, Japan.ORCID 0000-0001-8806-9659
Eric SmithEarth-Life Science Institute, Institute of Science Tokyo, Tokyo 152-8550, Japan.ORCID 0000-0003-0013-3447
Joshua E GoldfordBlue Marble Space Institute of Science, Seattle, WA 98104.ORCID 0000-0001-7315-8018
Liam M LongoEarth-Life Science Institute, Institute of Science Tokyo, Tokyo 152-8550, Japan.ORCID 0000-0002-1773-0611

Funding

Human Frontier Science Program (HFSP) RGEC29/2025NASA (NASA) 80NSSC23K1357NASA (NASA) 80NSSC25K7873
6 · The paper itself

Abstract

Whereas phylogenetic reconstructions are a primary record of protein evolution, it is unknown whether the deep history of enzymes is encoded at higher levels of biological organization. Here, we demonstrate that the emergence and reuse history of enzymatic folds is embedded within the web of metabolite-cofactor-enzyme interdependencies that comprise biosphere-scale metabolic reaction networks. Using a simple network analysis approach, we reconstruct the relative ordering of enzymatic fold emergence and, where possible, the first reaction(s) that each enzymatic fold catalyzed. We find that a large majority of enzymatic folds were sufficient as independent additions to open new avenues for metabolic growth. The resulting network-based histories are broadly concordant with enzyme phyletic distribution in prokaryotes, a proxy for enzyme age. Our results suggest that the earliest enzyme-mediated metabolisms were enriched for α/β proteins, likely due to their strong association with cofactor utilization, and that α-proteins preferentially emerge at later stages. The cradle-loop barrel, a member of the small β-barrel metafold, is predicted to be the founding β-fold, in agreement with analyses of ribosome structure. An examination of how the protein universe responded to the biological production of molecular oxygen reveals that the adaptation of existing enzymatic folds, not novel fold emergence, was the primary driver of metabolic evolution. This work presents a self-consistent model of metabolic and enzyme evolution, key progress toward integrating diverse perspectives into a unified history of protein evolution.

Indexed as

EnzymesEvolution, MolecularMetabolic Networks and PathwaysPhylogenyProtein FoldingEnzymesECODKEGGmetabolismnetwork expansionprotein evolution

Identifiers

PMID42579495
PMCPMC13486565

What OpenQuestion holds

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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.