Evidence map›Paper›PMID 38514040›Full record

ReviewDrug discovery today2024

Peptide-derived ligands for the discovery of safer opioid analgesics.

Abbe Eliasof, Lee-Yuan Liu-Chen, Yangmei Li

Open access · greenAbstract readReview
In one paragraph

Review in Drug discovery today, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

3 authors at 2 institutions in 1 country.

Abbe EliasofCollege of Pharmacy, University of South Carolina, Columbia, SC 29208, USA.
Lee-Yuan Liu-ChenLewis Katz School of Medicine, Temple University, Philadelphia, PA 19140, USA.
Yangmei LiCollege of Pharmacy, University of South Carolina, Columbia, SC 29208, USA. Electronic address: liyangme@cop.sc.edu.
University of South Carolina · USTemple University · US

Funding

Pilot Projects Core (PPC)P30DA013429 · NIDA · TEMPLE UNIV OF THE COMMONWEALTH · PI SCOTT M. RAWLS · 2000 to 2026
$34.6M
Pharmacology of Kappa Opioid ReceptorR01DA041359 · NIDA · TEMPLE UNIV OF THE COMMONWEALTH · PI LIU-CHEN, LEE-YUAN · 2017 to 2021
$2.9M
Kappa Opioid Receptor in Paraventricular Nucleus of ThalamusR01DA056581 · NIDA · TEMPLE UNIV OF THE COMMONWEALTH · PI LEE-YUAN LIU-CHEN · 2023 to 2026
$2.3M
NIDA NIH HHS P30 DA013429NIDA NIH HHS R01 DA041359NIDA NIH HHS R01 DA056581
6 · The paper itself

Abstract

Drugs targeting the μ-opioid receptor (MOR) remain the most efficacious analgesics for the treatment of pain, but activation of MOR with current opioid analgesics also produces harmful side effects, notably physical dependence, addiction, and respiratory depression. Opioid peptides have been accepted as promising candidates for the development of safer and more efficacious analgesics. To develop peptide-based opioid analgesics, strategies such as modification of endogenous opioid peptides, development of multifunctional opioid peptides, G protein-biased opioid peptides, and peripherally restricted opioid peptides have been reported. This review seeks to provide an overview of the opioid peptides that produce potent antinociception with much reduced side effects in animal models and highlight the potential advantages of peptides as safer opioid analgesics.

Indexed as

Analgesics, OpioidDrug DiscoveryOpioid PeptidesAnimalsHumansLigandsPainPeptidesReceptors, Opioid, muAnalgesics, OpioidLigandsOpioid PeptidesPeptidesReceptors, Opioid, mu

Identifiers

PMID38514040
PMCPMC11127667
OpenAlexW4392973803

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.