Evidence map›Paper›PMID 27131789›Full record

ArticleNucleic acids research2016

PepComposer: computational design of peptides binding to a given protein surface.

Agnieszka Obarska-Kosinska, Alfredo Iacoangeli, Rosalba Lepore, Anna Tramontano

Abstract read
In one paragraph

Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Tertiary motifs as building blocks for the design of protein-binding peptides.Protein science : a publication of the Protein Society · 2022
    Article
  9. Article
  10. Article
  11. Article
  12. Computational Evolution Protocol for Peptide Design.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Frontiers in molecular biosciences · 2021
    Review
  19. Article
  20. 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

4 authors.

Agnieszka Obarska-KosinskaDepartment of Physics, Sapienza University, Piazzale Aldo Moro, 5-00184 Rome, Italy.
Alfredo IacoangeliDepartment of Physics, Sapienza University, Piazzale Aldo Moro, 5-00184 Rome, Italy.
Rosalba LeporeDepartment of Physics, Sapienza University, Piazzale Aldo Moro, 5-00184 Rome, Italy alba.lepore@uniroma1.it.
Anna TramontanoDepartment of Physics, Sapienza University, Piazzale Aldo Moro, 5-00184 Rome, Italy Istituto Pasteur-Fondazione Cenci Bolognetti, Viale Regina Elena 291, 00161 Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a wide interest in designing peptides able to bind to a specific region of a protein with the aim of interfering with a known interaction or as starting point for the design of inhibitors. Here we describe PepComposer, a new pipeline for the computational design of peptides binding to a given protein surface. PepComposer only requires the target protein structure and an approximate definition of the binding site as input. We first retrieve a set of peptide backbone scaffolds from monomeric proteins that harbor the same backbone arrangement as the binding site of the protein of interest. Next, we design optimal sequences for the identified peptide scaffolds. The method is fully automatic and available as a web server at http://biocomputing.it/pepcomposer/webserver.

Indexed as

Computer-Aided DesignSoftwareAutomationBinding SitesDEAD-box RNA HelicasesEscherichia coli ProteinsFimbriae ProteinsInternetModels, MolecularMonte Carlo MethodNucleoside-TriphosphatasePeptidesProtein BindingProteinsReproducibility of ResultsSerine EndopeptidasesDEAD-box RNA HelicasesEscherichia coli ProteinsFimbriae ProteinsFimG protein, E coliNS3 protein, hepatitis C virusNucleoside-TriphosphatasePeptidesProteinsSerine EndopeptidasesViral Nonstructural ProteinsViral Proteases

Identifiers

PMID27131789
PMCPMC4987918

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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 OpenQuestion graph.