Evidence map›Paper›PMID 28134276›Full record

ArticleScientific reports2017

Exploring the dark foldable proteome by considering hydrophobic amino acids topology.

Tristan Bitard-Feildel, Isabelle Callebaut

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Shining light on the dark proteome with unstructural biology.Current research in structural biology · 2026
    Article
  2. Impact of GC content on de novo gene birth.Nature communications · 2026
    Article
  3. The Analysis ofCurrent issues in molecular biology · 2025
    Article
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  16. Unique function words characterize genomic proteins.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  17. 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.

Tristan Bitard-FeildelCNRS UMR7590, Sorbonne Universités, Université Pierre et Marie Curie - Paris 6 - MNHN - IRD - IUC, Paris, France.
Isabelle CallebautCNRS UMR7590, Sorbonne Universités, Université Pierre et Marie Curie - Paris 6 - MNHN - IRD - IUC, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The protein universe corresponds to the set of all proteins found in all organisms. A way to explore it is by taking into account the domain content of the proteins. However, some part of sequences and many entire sequences remain un-annotated despite a converging number of domain families. The un-annotated part of the protein universe is referred to as the dark proteome and remains poorly characterized. In this study, we quantify the amount of foldable domains within the dark proteome by using the hydrophobic cluster analysis methodology. These un-annotated foldable domains were grouped using a combination of remote homology searches and domain annotations, leading to define different levels of darkness. The dark foldable domains were analyzed to understand what make them different from domains stored in databases and thus difficult to annotate. The un-annotated domains of the dark proteome universe display specific features relative to database domains: shorter length, non-canonical content and particular topology in hydrophobic residues, higher propensity for disorder, and a higher energy. These features make them hard to relate to known families. Based on these observations, we emphasize that domain annotation methodologies can still be improved to fully apprehend and decipher the molecular evolution of the protein universe.

Indexed as

Hydrophobic and Hydrophilic InteractionsAmino AcidsAmino Acid SequenceCluster AnalysisMolecular Sequence AnnotationProteomeThermodynamicsAmino AcidsProteome

Identifiers

PMID28134276
PMCPMC5278394

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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.