Evidence map›Paper›PMID 40927993›Full record

ArticleNucleic acids research2026

APD6: the antimicrobial peptide database is expanded to promote research and development by deploying an unprecedented information pipeline.

Guangshun Wang, Cindy Schmidt, Xia Li, Zhe Wang

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
–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

33 citing papers in PubMed.

  1. Exploring the antifungal activity of the wheat microbiome.Biochemical Society transactions · 2026
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  6. A MarineMarine drugs · 2026
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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

4 authors.

Guangshun WangDepartment of Pathology, Microbiology and Immunology, College of Medicine, University of Nebraska Medical Center, 985900 Nebraska Medical Center, Omaha, NE 68198-5900, United States.ORCID 0000-0002-4841-7927
Cindy SchmidtDepartment of Pathology, Microbiology and Immunology, College of Medicine, University of Nebraska Medical Center, 985900 Nebraska Medical Center, Omaha, NE 68198-5900, United States.
Xia LiDepartment of Pathology, Microbiology and Immunology, College of Medicine, University of Nebraska Medical Center, 985900 Nebraska Medical Center, Omaha, NE 68198-5900, United States.
Zhe WangDepartment of Pathology, Microbiology and Immunology, College of Medicine, University of Nebraska Medical Center, 985900 Nebraska Medical Center, Omaha, NE 68198-5900, United States.

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
Novel antimicrobials to combat Gram-negative bacteriaR56AI175209 · NIAID · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI MURRY, DARYL, WANG, GUANGSHUN · 2023 to 2023
$384k
National Institute of Allergy and Infectious DiseasesNIAID NIH HHS R56 AI175209NIGMS NIH HHS AI175209NIGMS NIH HHS R01 GM138552NIH HHS GM138552
6 · The paper itself

Abstract

The global antibiotic resistance issue constitutes a driving force for developing host defense antimicrobial peptides (AMPs) into a new generation of antibiotics. To facilitate this development, we report the antimicrobial peptide database version 6 (APD6) with (i) the consolidated database platform, (ii) the most comprehensive AMP information pipeline (AMPIP), and (iii) the expanded wheel of function. As of 18 March 2025, the APD6 platform housed records for 5188 peptides, including 3306 natural, 1380 synthetic, and 239 predicted AMPs with systematic classification schemes for each group. Based on the refined dataset, we present an updated view and findings on natural AMPs. Natural AMPs provide a fundamental dataset for peptide design and predicting potential AMPs. While current artificial intelligence prediction of AMPs is limited to activity and hemolysis, the APD6 provides new positive and negative datasets (e.g. pH, salt, serum effects, and resistance) for building advanced AI prediction models to identify more robust antibiotics. The AMPIP covers information ranging from peptide discovery, in vitro/in vivo activity and toxicity data, to clinical trials. In addition, the APD6 (available at https://aps.unmc.edu) contains an expanded wheel of peptide functions (e.g. anticancer and antidiabetic), allowing for developing peptide therapeutics outside the antibiotic arena.

Indexed as

Antimicrobial PeptidesDatabases, ProteinAnimalsAnti-Bacterial AgentsHumansAnti-Bacterial AgentsAntimicrobial Peptides

Identifiers

PMID40927993
PMCPMC12807733

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.