Evidence map›Paper›PMID 19219049›Full record

ArticleNature chemical biology2009

Analysis of the eukaryotic prenylome by isoprenoid affinity tagging.

Uyen T T Nguyen, Zhong Guo, Christine Delon, Yaowen Wu, Celine Deraeve, Benjamin Fränzel, Robin S Bon, Wulf Blankenfeldt, Roger S Goody, Herbert Waldmann and 2 more

Abstract read
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In one paragraph

Article in Nature chemical biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.

0numbers the graph read from it
0cells of the map it votes in
71citing papers in PubMed
8.5field-weighted citation impact, top 2% 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

71 citing papers in PubMed, 171 citations in OpenAlex.

  1. Review
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  6. Article
  7. Chemoproteomic Profiling of Geranyl Pyrophosphate-Binding Proteins.Methods in molecular biology (Clifton, N.J.) · 2023
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11 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 2 countries.

Uyen T T NguyenMax Planck Institute of Molecular Physiology, Dortmund, Germany.
Zhong Guo
Christine Delon
Yaowen Wu
Celine Deraeve
Benjamin Fränzel
Robin S Bon
Wulf Blankenfeldt
Roger S Goody
Herbert Waldmann
Dirk Wolters
Kirill Alexandrov
Max Planck Society · DEMax Planck Institute of Molecular Physiology · DERuhr University Bochum · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein prenylation is a widespread phenomenon in eukaryotic cells that affects many important signaling molecules. We describe the structure-guided design of engineered protein prenyltransferases and their universal synthetic substrate, biotin-geranylpyrophosphate. These new tools allowed us to detect femtomolar amounts of prenylatable proteins in cells and organs and to identify their cognate protein prenyltransferases. Using this approach, we analyzed the in vivo effects of protein prenyltransferase inhibitors. Whereas some of the inhibitors displayed the expected activities, others lacked in vivo activity or targeted a broader spectrum of prenyltransferases than previously believed. To quantitate the in vivo effect of the prenylation inhibitors, we profiled biotin-geranyl-tagged RabGTPases across the proteome by mass spectrometry. We also demonstrate that sites of active vesicular transport carry most of the RabGTPases. This approach enables a quantitative proteome-wide analysis of the regulation of protein prenylation and its modulation by therapeutic agents.

Indexed as

Isotope LabelingAnimalsBiotinCatalytic DomainChlorocebus aethiopsCOS CellsModels, MolecularMolecular StructurePolyisoprenyl PhosphatesProtein BindingProtein ConformationProtein EngineeringProtein PrenylationSignal TransductionTerpenesBiotinbiotin-geranylpyrophosphatePolyisoprenyl PhosphatesTerpenes

Identifiers

PMID19219049
OpenAlexW2067153023

What OpenQuestion holds

Textmetadata
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.