Evidence map›Paper›PMID 28063303›Full record

ReviewCurrent opinion in structural biology2017

Peptides and peptidomimetics as regulators of protein-protein interactions.

Anna D Cunningham, Nir Qvit, Daria Mochly-Rosen

Abstract readReview
In one paragraph

Review in Current opinion in structural biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers.

0numbers the graph read from it
0cells of the map it votes in
87citing papers in PubMed
5.8field-weighted citation impact, top 3% 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

87 citing papers in PubMed, 171 citations in OpenAlex.

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  16. Peptide Multifunctionalization via Modular Construction of Trans-ABAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  17. Review
  18. Article
  19. Article
  20. Review

27 more citing papers are in PubMed but not listed here.

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

3 authors at 1 institution in 1 country.

Anna D CunninghamDepartment of Chemical and Systems Biology, Stanford University, School of Medicine, Stanford, CA 94305-5174, USA.
Nir QvitDepartment of Chemical and Systems Biology, Stanford University, School of Medicine, Stanford, CA 94305-5174, USA. Electronic address: nirqvit@stanford.edu.
Daria Mochly-RosenDepartment of Chemical and Systems Biology, Stanford University, School of Medicine, Stanford, CA 94305-5174, USA. Electronic address: mochly@stanford.edu.
Stanford University · US

Funding

Protein Kinase C Isozymes in Ischemic HeartR01HL052141 · NHLBI · STANFORD UNIVERSITY · PI MOCHLY-ROSEN, DARIA · 1996 to 2021
$8.5M
NHLBI NIH HHS R01 HL052141
6 · The paper itself

Abstract

Protein-protein interactions are essential for almost all intracellular and extracellular biological processes. Regulation of protein-protein interactions is one strategy to regulate cell fate in a highly selective manner. Specifically, peptides are ideal candidates for inhibition of protein-protein interactions because they can mimic a protein surface to effectively compete for binding. Additionally, peptides are synthetically accessible and can be stabilized by chemical modifications. In this review, we survey screening and rational design methods for identifying peptides to inhibit protein-protein interactions, as well as methods for stabilizing peptides to effectively mimic protein surfaces. In addition, we discuss recent applications of peptides to regulate protein-protein interactions for both basic research and therapeutic purposes.

Indexed as

Amino Acid SequenceAnimalsDrug DiscoveryHumansMolecular Targeted TherapyPeptidesPeptidomimeticsProtein BindingProtein Structure, SecondaryPeptidesPeptidomimetics

Identifiers

PMID28063303
PMCPMC5496809
OpenAlexW2569303361

What OpenQuestion holds

Textmetadata
LicenceTDM
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.