Evidence map›Paper›PMID 35606604›Full record

ReviewMolecular biology reports2022

Antimicrobial peptides: features, applications and the potential use against covid-19.

Dalia Mamdouh Mabrouk

Open access · hybridAbstract readReview
In one paragraph

Review in Molecular biology reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
5.0field-weighted citation impact, top 4% 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

22 citing papers in PubMed, 37 citations in OpenAlex.

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  14. medRxiv : the preprint server for health sciences · 2024
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  19. Strategic Approaches to Improvise Peptide Drugs as Next Generation Therapeutics.International journal of peptide research and therapeutics · 2023
    Review
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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

1 author at 1 institution in 1 country.

Dalia Mamdouh MabroukCell Biology Department, National Research Centre, 33 El Bohouth, St., P.O.12622, Dokki, Giza, Egypt. dalia.mamdouh@ymail.com.ORCID http://orcid.org/0000-0002-8535-9359
National Research Centre · EG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAntimicrobial peptides (AMPs) are a diverse class of molecules that represent a vital part of innate immunity. AMPs are evolutionarily conserved molecules that exhibit structural and functional diversity. They provide a possible solution to the antibiotic-resistance crisis. MAIN TEXT: These small cationic peptides can target bacteria, fungi, and viruses, as well as cancer cells. Their unique action mechanisms, rare antibiotic-resistant variants, broad-spectrum activity, low toxicity, and high specificity encourage pharmaceutical industries to conduct clinical trials to develop them as therapeutic drugs. The rapid development of computer-assisted strategies accelerated the identification of AMPs. The Antimicrobial Peptide Database (APD) so far contains 3324 AMPs from different sources. In addition to their applications in different fields, some AMPs demonstrated the potential to combat COVID-19, and hinder viral infectivity in diverse ways.

conclusionsThis review provides a brief history of AMPs and their features, including classification, evolution, sources and mechanisms of action, biosynthesis pathway, and identification techniques. Furthermore, their different applications, challenges to clinical applications, and their potential use against COVID-19 are presented.

Indexed as

Antimicrobial Cationic PeptidesCOVID-19 Drug TreatmentAnti-Bacterial AgentsAntimicrobial PeptidesBacteriaHumansAnti-Bacterial AgentsAntimicrobial Cationic PeptidesAntimicrobial PeptidesAntibioticsAntimicrobial peptidesCovid-19Therapeutic agents

Identifiers

PMID35606604
PMCPMC9126628
OpenAlexW4281382833

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.