Evidence map›Paper›PMID 33183148›Full record

ReviewAutophagy2021

Protein complexes and neighborhoods driving autophagy.

Devanarayanan Siva Sankar, Jörn Dengjel

Open access · hybridAbstract readReview
In one paragraph

Review in Autophagy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

31 citing papers in PubMed, 52 citations in OpenAlex.

  1. Article
  2. Autophagy · 2026
    Review
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Investigating Protein-Protein Interactions of Autophagy-Involved TNIP1.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  14. Article
  15. Article
  16. Autophagy3D: a comprehensive autophagy structure database.Database : the journal of biological databases and curation · 2024
    Article
  17. Article
  18. Article
  19. Article
  20. Review
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 at 1 institution in 1 country.

Devanarayanan Siva SankarDepartment of Biology, University of Fribourg, Fribourg, Switzerland.
Jörn DengjelDepartment of Biology, University of Fribourg, Fribourg, Switzerland.ORCID 0000-0002-9453-4614
University of Fribourg · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autophagy summarizes evolutionarily conserved, intracellular degradation processes targeting cytoplasmic material for lysosomal degradation. These encompass constitutive processes as well as stress responses, which are often found dysregulated in diseases. Autophagy pathways help in the clearance of damaged organelles, protein aggregates and macromolecules, mediating their recycling and maintaining cellular homeostasis. Protein-protein interaction networks contribute to autophagosome biogenesis, substrate loading, vesicular trafficking and fusion, protein translocations across membranes and degradation in lysosomes. Hypothesis-free proteomic approaches tremendously helped in the functional characterization of protein-protein interactions to uncover molecular mechanisms regulating autophagy. In this review, we elaborate on the importance of understanding protein-protein-interactions of varying affinities and on the strengths of mass spectrometry-based proteomic approaches to study these, generating new mechanistic insights into autophagy regulation. We discuss in detail affinity purification approaches and recent developments in proximity labeling coupled to mass spectrometry, which uncovered molecular principles of autophagy mechanisms.

Indexed as

AutophagyProteomicsLysosomesMass SpectrometryProtein Interaction Mapsaffinity purificationAutophagymass spectrometryprotein-protein interactionsproximity labelingquantitative proteomics

Identifiers

PMID33183148
PMCPMC8526019
OpenAlexW3100326425

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.