Evidence map›Paper›PMID 31091705›Full record

ReviewInternational journal of molecular sciences2019

A Comprehensive Review on Current Advances in Peptide Drug Development and Design.

Andy Chi-Lung Lee, Janelle Louise Harris, Kum Kum Khanna, Ji-Hong Hong

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 283 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
283citing papers in PubMed, 1 pooled it
–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

283 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Exploring RiPP-derivedRSC chemical biology · 2026
    Article
  4. Peptide-based allosteric modulators of AMPA receptors: design, docking and ligand-receptor interactions.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026
    Article
  5. Article
  6. Phage Display as a Promising Platform for Peptide Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2026
    Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Proteome-wide prediction of interactions between structured domains and peptide motifs reveals functionally coherent subnetworks.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  17. A 62-aa core of the cochlin LCCL domain induces macrophage M1 polarization in vitro.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026
    Article
  18. Article
  19. Article
  20. Article

223 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

4 authors.

Andy Chi-Lung LeeQIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia. andy.lee@qimrberghofer.edu.au.
Janelle Louise HarrisQIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia. Janelle.Hancock@qimrberghofer.edu.au.
Kum Kum KhannaQIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia. KumKum.Khanna@qimrberghofer.edu.au.
Ji-Hong HongRadiation Biology Research Center, Institute for Radiological Research, Chang Gung Memorial Hospital, Chang Gung University, Taoyuan 333, Taiwan. jihong@cgmh.org.tw.ORCID 0000-0002-1601-6555

Funding

Chang Gung Memorial Hospital CMRPG3F2232, CMRP3G1491, CMRPG3H1241National Health and Medical Research Council ID1017028
6 · The paper itself

Abstract

Protein-protein interactions (PPIs) execute many fundamental cellular functions and have served as prime drug targets over the last two decades. Interfering intracellular PPIs with small molecules has been extremely difficult for larger or flat binding sites, as antibodies cannot cross the cell membrane to reach such target sites. In recent years, peptides smaller size and balance of conformational rigidity and flexibility have made them promising candidates for targeting challenging binding interfaces with satisfactory binding affinity and specificity. Deciphering and characterizing peptide-protein recognition mechanisms is thus central for the invention of peptide-based strategies to interfere with endogenous protein interactions, or improvement of the binding affinity and specificity of existing approaches. Importantly, a variety of computation-aided rational designs for peptide therapeutics have been developed, which aim to deliver comprehensive docking for peptide-protein interaction interfaces. Over 60 peptides have been approved and administrated globally in clinics. Despite this, advances in various docking models are only on the merge of making their contribution to peptide drug development. In this review, we provide (i) a holistic overview of peptide drug development and the fundamental technologies utilized to date, and (ii) an updated review on key developments of computational modeling of peptide-protein interactions (PepPIs) with an aim to assist experimental biologists exploit suitable docking methods to advance peptide interfering strategies against PPIs.

Indexed as

AnimalsDrug DevelopmentHumansMachine LearningMolecular Docking SimulationPeptidesProtein BindingPeptidesbinding sitedockingInterfacemodelingpeptidepeptide–protein interactionprotein–protein interactionscoring

Identifiers

PMID31091705
PMCPMC6566176

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.