Evidence map›Paper›PMID 33119751›Full record

ArticleNucleic acids research2021

The MemMoRF database for recognizing disordered protein regions interacting with cellular membranes.

Georgina Csizmadia, Gábor Erdős, Hedvig Tordai, Rita Padányi, Silvio Tosatto, Zsuzsanna Dosztányi, Tamás Hegedűs

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.7field-weighted citation impact, top 32% of its field
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

9 citing papers in PubMed, 17 citations in OpenAlex.

  1. Comparative assessment of binding residue predictions in intrinsically disordered regions.Protein science : a publication of the Protein Society · 2025
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  2. Article
  3. Article
  4. Article
  5. Article
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  7. MemDis: Predicting Disordered Regions in Transmembrane Proteins.International journal of molecular sciences · 2021
    Article
  8. What FXYDs fix.The Journal of general physiology · 2021
    Article
  9. 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

7 authors at 3 institutions in 2 countries.

Georgina CsizmadiaDepartment of Biophysics and Radiation Biology, Semmelweis University, Budapest 1094, Hungary.
Gábor ErdősMTA-ELTE Lendület Bioinformatics Research Group, Department of Biochemistry, Eötvös Loránd University, Budapest 1117, Hungary.
Hedvig TordaiDepartment of Biophysics and Radiation Biology, Semmelweis University, Budapest 1094, Hungary.
Rita PadányiDepartment of Biophysics and Radiation Biology, Semmelweis University, Budapest 1094, Hungary.
Silvio TosattoDepartment of Biomedical Sciences, University of Padua, Padua 35131, Italy.
Zsuzsanna DosztányiMTA-ELTE Lendület Bioinformatics Research Group, Department of Biochemistry, Eötvös Loránd University, Budapest 1117, Hungary.
Tamás HegedűsDepartment of Biophysics and Radiation Biology, Semmelweis University, Budapest 1094, Hungary.
Semmelweis University · HUEötvös Loránd University · HUUniversity of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein and lipid membrane interactions play fundamental roles in a large number of cellular processes (e.g. signalling, vesicle trafficking, or viral invasion). A growing number of examples indicate that such interactions can also rely on intrinsically disordered protein regions (IDRs), which can form specific reversible interactions not only with proteins but also with lipids. We named IDRs involved in such membrane lipid-induced disorder-to-order transition as MemMoRFs, in an analogy to IDRs exhibiting disorder-to-order transition upon interaction with protein partners termed Molecular Recognition Features (MoRFs). Currently, both the experimental detection and computational characterization of MemMoRFs are challenging, and information about these regions are scattered in the literature. To facilitate the related investigations we generated a comprehensive database of experimentally validated MemMoRFs based on manual curation of literature and structural data. To characterize the dynamics of MemMoRFs, secondary structure propensity and flexibility calculated from nuclear magnetic resonance chemical shifts were incorporated into the database. These data were supplemented by inclusion of sentences from papers, functional data and disease-related information. The MemMoRF database can be accessed via a user-friendly interface at https://memmorf.hegelab.org, potentially providing a central resource for the characterization of disordered regions in transmembrane and membrane-associated proteins.

Indexed as

Databases, ProteinCell MembraneInternetIntrinsically Disordered ProteinsMagnetic Resonance SpectroscopyOpen Reading FramesProtein BindingIntrinsically Disordered Proteins

Identifiers

PMID33119751
PMCPMC7778998
OpenAlexW3096427258

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.