Evidence map›Paper›PMID 24906382›Full record

ReviewBiology direct2014

Profiling the orphan enzymes.

Maria Sorokina, Mark Stam, Claudine Médigue, Olivier Lespinet, David Vallenet

Abstract readReview
In one paragraph

Review in Biology direct, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Article
  2. The history of enzyme evolution embedded in metabolism.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Review
  4. Dual-encoder contrastive learning accelerates enzyme discovery.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Prokaryotic Genome Annotation.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Enzyme annotation for orphan and novel reactions using knowledge of substrate reactive sites.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
  18. Article
  19. Article
  20. 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.

Maria SorokinaDirection des Sciences du Vivant, Commissariat à l'Energie Atomique (CEA), Institut de Génomique, Genoscope, Laboratoire d'Analyses Bioinformatiques pour la Génomique et le Métabolisme, 2 rue Gaston Crémieux, 91057 Evry, France. msorokina@genoscope.cns.fr.
Mark Stam
Claudine Médigue
Olivier Lespinet
David Vallenet

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of Next Generation Sequencing generates an incredible amount of sequence and great potential for new enzyme discovery. Despite this huge amount of data and the profusion of bioinformatic methods for function prediction, a large part of known enzyme activities is still lacking an associated protein sequence. These particular activities are called "orphan enzymes". The present review proposes an update of previous surveys on orphan enzymes by mining the current content of public databases. While the percentage of orphan enzyme activities has decreased from 38% to 22% in ten years, there are still more than 1,000 orphans among the 5,000 entries of the Enzyme Commission (EC) classification. Taking into account all the reactions present in metabolic databases, this proportion dramatically increases to reach nearly 50% of orphans and many of them are not associated to a known pathway. We extended our survey to "local orphan enzymes" that are activities which have no representative sequence in a given clade, but have at least one in organisms belonging to other clades. We observe an important bias in Archaea and find that in general more than 30% of the EC activities have incomplete sequence information in at least one superkingdom. To estimate if candidate proteins for local orphans could be retrieved by homology search, we applied a simple strategy based on the PRIAM software and noticed that candidates may be proposed for an important fraction of local orphan enzymes. Finally, by studying relation between protein domains and catalyzed activities, it appears that newly discovered enzymes are mostly associated with already known enzyme domains. Thus, the exploration of the promiscuity and the multifunctional aspect of known enzyme families may solve part of the orphan enzyme issue. We conclude this review with a presentation of recent initiatives in finding proteins for orphan enzymes and in extending the enzyme world by the discovery of new activities.

Indexed as

ArchaeaBacteriaDatabases, ProteinEnzymesEukaryotaGenomicsHigh-Throughput Nucleotide SequencingPhylogenyProteinsProteomicsSequence Analysis, ProteinEnzymesProteins

Identifiers

PMID24906382
PMCPMC4084501

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.