Evidence map›Paper›PMID 39623291›Full record

ArticleProteins2025

α/β Hydrolases: Toward Unraveling Entangled Classification.

Fatih Ozhelvaci, Kamil Steczkiewicz

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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. microPublication biology · 2026
    Article
  8. Article
  9. Article
  10. Review
  11. 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

2 authors.

Fatih OzhelvaciInstitute of Biochemistry and Biophysics, Polish Academy of Sciences, Warszawa, Poland.
Kamil SteczkiewiczInstitute of Biochemistry and Biophysics, Polish Academy of Sciences, Warszawa, Poland.ORCID 0000-0002-6223-1694

Funding

Narodowe Centrum NaukiNCN 2019/35/D/NZ2/03411
6 · The paper itself

Abstract

α/β Hydrolase-like enzymes form a large and functionally diverse superfamily of proteins. Despite retaining a conserved structural core consisting of an eight-stranded, central β-sheet flanked with six α-helices, they display a modular architecture allowing them to perform a variety of functions, like esterases, lipases, peptidases, epoxidases, lyases, and others. At the same time, many α/β hydrolase-like families, even enzymatically distinct, share a high degree of sequence similarity. This imposes several problems for their annotation and classification, because available definitions of particular α/β hydrolase-like families overlap significantly, so the unambiguous functional assignment of these superfamily members remains a challenging task. For instance, two large and important peptidase families, namely S9 and S33, blend with lipases, epoxidases, esterases, and other enzymes unrelated to proteolysis, which hinders automatic annotations in high-throughput projects. With the use of thorough sequence and structure analyses, we newly annotate three protein families as α/β hydrolase-like and revise current classifications of the realm of α/β hydrolase-like superfamily. Based on manually curated structural superimpositions and multiple sequence and structure alignments, we comprehensively demonstrate structural conservation and diversity across the whole superfamily. Eventually, after detailed pairwise sequence similarity assessments, we develop a new clustering of the α/β hydrolases and provide a set of family profiles allowing for detailed, reliable, and automatic functional annotations of the superfamily members.

Indexed as

HydrolasesAmino Acid SequenceDatabases, ProteinModels, MolecularHydrolasesenzyme structurehomology modelingMEROPSpeptidaseproteaseprotein familyS09S33serine proteaseα/β hydrolases

Identifiers

PMID39623291
PMCPMC11878206

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.