Evidence map›Paper›PMID 35168785›Full record

ArticleMethods in enzymology2022

Unifying the classification of antimicrobial peptides in the antimicrobial peptide database.

Guangshun Wang

Open access · greenAbstract read
In one paragraph

Article in Methods in enzymology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
34.3field-weighted citation impact, top 1% 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

33 citing papers in PubMed, 1 synthesis or guideline pooled it, 55 citations in OpenAlex.

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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.

Guangshun WangDepartment of Pathology and Microbiology, College of Medicine, University of Nebraska Medical Center, 985900 Nebraska Medical Center, Omaha, NE, United States. Electronic address: gwang@unmc.edu.
Nebraska Medical Center · US

Funding

Novel Janus-type Antimicrobial Dressings for the Treatment of Biofilms in Chronic WoundsR01GM138552 · NIGMS · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI WANG, GUANGSHUN, XIE, JINGWEI · 2020 to 2023
$2.2M
T-cell-Alveolar Macrophage Crosstalk during Influenza and Streptococcus Pneumoniae Co-infectionR56AI137161 · NIAID · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI WANG, GUANGSHUN · 2019 to 2019
$419k
Novel antimicrobials to combat Gram-negative bacteriaR56AI175209 · NIAID · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI MURRY, DARYL, WANG, GUANGSHUN · 2023 to 2023
$384k
NIAID NIH HHS R56 AI137161NIAID NIH HHS R56 AI175209NIGMS NIH HHS R01 GM138552
6 · The paper itself

Abstract

Natural products offer an important avenue to novel therapeutics against drug-resistant bacteria, viruses, fungi, parasites, and cancer. However, there are numerous hurdles and challenges in discovering such molecules, including antimicrobial peptides (AMPs). While a thorough characterization of AMPs is limited by the amount of material, existing technology, and researcher's expertise, peptide classification is complicated by incomplete information as well as different methods proposed for AMPs from bacteria, plants, and animals. This article describes unified classification schemes for natural AMPs on a common platform: the Antimicrobial Peptide Database (APD; https://aps.unmc.edu). The various criteria for these unified classifications include peptide biological source, biosynthesis machinery, biological activity, amino acid sequence, mechanism of action, and three-dimensional structure. To overcome the problem with a limited number of known 3D structures, a universal peptide classification has also been refined and executed in the APD database. This universal method, based on the spatial connection patterns of polypeptide chains, is independent of peptide source, size, activity, 3D structure, or mechanism of action. It facilitates information registration, naming, exchange, decoding, prediction, and design of novel antimicrobial peptides.

Indexed as

Antimicrobial Cationic PeptidesAntimicrobial PeptidesAmino Acid SequenceAnimalsBacteriaFungiAntimicrobial Cationic PeptidesAntimicrobial PeptidesAntibioticsAntimicrobial peptidesClassificationDatabaseHydrophobic contentNet chargePeptide discoveryPeptide lengthStructure

Identifiers

PMID35168785
PMCPMC9082820
OpenAlexW3212602175

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.