Evidence map›Paper›PMID 37673948›Full record

ArticleScientific reports2023

Tracing the birth of structural domains from loops during protein evolution.

M Fayez Aziz, Fizza Mughal, Gustavo Caetano-Anollés

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Tracing the Origin and Evolution of the Secondary Structure of RNA.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  3. Review
  4. Tracing Molecular Chronologies Onto Growing Biological Networks.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  5. Article
  6. Review
  7. Review
  8. Review
  9. Review
  10. Evolution of Intrinsic Disorder in Protein Loops.Life (Basel, Switzerland) · 2023
    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

3 authors.

M Fayez AzizEvolutionary Bioinformatics Laboratory, Department of Crop Sciences, University of Illinois, Urbana, IL, 61801, USA.
Fizza MughalEvolutionary Bioinformatics Laboratory, Department of Crop Sciences, University of Illinois, Urbana, IL, 61801, USA.
Gustavo Caetano-AnollésEvolutionary Bioinformatics Laboratory, Department of Crop Sciences, University of Illinois, Urbana, IL, 61801, USA. gca@illinois.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The structures and functions of proteins are embedded into the loop scaffolds of structural domains. Their origin and evolution remain mysterious. Here, we use a novel graph-theoretical approach to describe how modular and non-modular loop prototypes combine to form folded structures in protein domain evolution. Phylogenomic data-driven chronologies reoriented a bipartite network of loops and domains (and its projections) into 'waterfalls' depicting an evolving 'elementary functionome' (EF). Two primordial waves of functional innovation involving founder 'p-loop' and 'winged-helix' domains were accompanied by an ongoing emergence and reuse of structural and functional novelty. Metabolic pathways expanded before translation functionalities. A dual hourglass recruitment pattern transferred scale-free properties from loop to domain components of the EF network in generative cycles of hierarchical modularity. Modeling the evolutionary emergence of the oldest P-loop and winged-helix domains with AlphFold2 uncovered rapid convergence towards folded structure, suggesting that a folding vocabulary exists in loops for protein fold repurposing and design.

Indexed as

DermatitisEmbryonic DevelopmentHumansPhylogenyProtein DomainsTranslations

Identifiers

PMID37673948
PMCPMC10482863

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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.