Evidence map›Paper›PMID 40418090›Full record

ArticleProteins2025

Case Studies of Orphan Domain Reclassification in ECOD by Expert Curation.

Jimin Pei, R Dustin Schaeffer, Qian Cong, Nick V Grishin

Abstract read
In one paragraph

Article in Proteins, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Exploring the Terra incognita of AI-based domain classifications.Protein science : a publication of the Protein Society · 2025
    Article
  2. 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

4 authors.

Jimin PeiEugene McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID 0000-0002-3505-9665
R Dustin SchaefferDepartment of Biophysics, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Qian CongEugene McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID 0000-0002-8909-0414
Nick V GrishinDepartment of Biophysics, University of Texas Southwestern Medical Center, Dallas, Texas, USA.

Funding

Computational analysis of proteinsR35GM127390 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI GRISHIN, NICK V. · 2018 to 2022
$1.5M
ECOD: Large scale classification of predicted and experimental protein structuresR01GM147367 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI Richard Dustin Schaeffer · 2023 to 2026
$1.4M
National Science Foundation DBI 2224128NIGMS NIH HHS R01 GM147367NIGMS NIH HHS R35 GM127390NIH HHS GM127390NIH HHS GM147367Welch Foundation I-1505Welch Foundation I-2095-20220331
6 · The paper itself

Abstract

Homology-based protein domain classification is a powerful tool for gaining biological insights into protein function. This classification process has been significantly enhanced by the availability of experimental structures and high-accuracy structural models generated by advanced tools such as AlphaFold. Our Evolutionary Classification of protein Domains (ECOD) database provides a continuously updated and refined domain classification system. Isolated ("orphan") protein domain families, which have a limited distribution in the protein universe, present a unique challenge in this classification process. These families lack clear or identifiable evolutionary relationships with other sequence families. While some isolated domain families may have emerged through de novo evolution, others potentially share common evolutionary origins with existing domain families but represent difficult cases for traditional classification methods. In this study, we conducted a manual analysis of a set of isolated families of small domains in ECOD. By exploring sequence, structural, and functional evidence, we uncovered distant members and likely homologous relationships between different isolated domain families that were previously unrecognized. Our analysis provides valuable insights into the evolution of isolated domain families and has led to improved classification within ECOD. This work enhances our understanding of protein evolution and underscores the importance of continuous refinement in domain classification systems as new data and analytical methods become available.

Indexed as

Databases, ProteinProtein DomainsProteinsComputational BiologyEvolution, MolecularHumansModels, MolecularProteinsECODisolated domain familiesprotein classificationprotein evolutionremote homology

Identifiers

PMID40418090
PMCPMC12353581

What OpenQuestion holds

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Registered trials

None linked

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.