Evidence map›Paper›PMID 27025565›Full record

ArticleBioorganic & medicinal chemistry2016

Prediction and verification of novel peptide targets of protein tyrosine phosphatase 1B.

Xun Li, Maja Köhn

Open access · hybridAbstract read
In one paragraph

Article in Bioorganic & medicinal chemistry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 37% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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 at 1 institution in 3 countries.

Xun LiEuropean Molecular Biology Laboratory, Genome Biology Unit, Meyerhofstrasse 1, 69117 Heidelberg, Germany; European Molecular Biology Laboratory-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom.
Maja KöhnEuropean Molecular Biology Laboratory, Genome Biology Unit, Meyerhofstrasse 1, 69117 Heidelberg, Germany. Electronic address: koehn@embl.de.
European Bioinformatics Institute · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phosphotyrosine peptides are useful starting points for inhibitor design and for the search for protein tyrosine phosphatase (PTP) phosphoprotein substrates. To identify novel phosphopeptide substrates of PTP1B, we developed a computational prediction protocol based on a virtual library of protein sequences with known phosphotyrosine sites. To these we applied sequence-based methods, biologically meaningful filters and molecular docking. Five peptides were selected for biochemical testing of their potential as PTP1B substrates. All five peptides were equally good substrates for PTP1B compared to a known peptide substrate whereas appropriate control peptides were not recognized, showing that our protocol can be used to identify novel peptide substrates of PTP1B.

Indexed as

Amino Acid SequenceHumansModels, ChemicalModels, MolecularPhosphopeptidesProtein Tyrosine Phosphatase, Non-Receptor Type 1Substrate SpecificityPhosphopeptidesProtein Tyrosine Phosphatase, Non-Receptor Type 1PTPN1 protein, humanComputational predictionPeptide substratesProtein tyrosine phosphatasesPTP1B

Identifiers

PMID27025565
PMCPMC4957924
OpenAlexW2298121671

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.