Evidence map›Paper›PMID 36834553›Full record

ReviewInternational journal of molecular sciences2023

Thinking on the Construction of Antimicrobial Peptide Databases: Powerful Tools for the Molecular Design and Screening.

Kun Zhang, Da Teng, Ruoyu Mao, Na Yang, Ya Hao, Jianhua Wang

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Repositioning Antimicrobial Peptides Against WHO-Priority Fungi.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  5. Peptide-Based Strategies AgainstPharmaceuticals (Basel, Switzerland) · 2025
    Review
  6. Designing of a novel chimeric antimicrobial peptide againstResearch in pharmaceutical sciences · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Effect of Camel Peptide on the Biofilm ofAntibiotics (Basel, Switzerland) · 2023
    Article
  11. Article
  12. 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

6 authors.

Kun ZhangGene Engineering Laboratory, Feed Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Da TengGene Engineering Laboratory, Feed Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Ruoyu MaoGene Engineering Laboratory, Feed Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Na YangGene Engineering Laboratory, Feed Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Ya HaoGene Engineering Laboratory, Feed Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Jianhua WangGene Engineering Laboratory, Feed Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China.ORCID 0000-0002-4048-6055

Funding

Innovation Program of Agricultural Science and Technology (ASTIP) in CAAS CAAS-ASTIP-2017-FRI-02key projects of Innovation Program of Agricultural Science and Technology (ASTIP) in CAAS CAAS-ZDRW202111 and Grant No.CAAS-ZDXT 201808National Natural Science Foundation of China 31872393
6 · The paper itself

Abstract

With the accelerating growth of antimicrobial resistance (AMR), there is an urgent need for new antimicrobial agents with low or no AMR. Antimicrobial peptides (AMPs) have been extensively studied as alternatives to antibiotics (ATAs). Coupled with the new generation of high-throughput technology for AMP mining, the number of derivatives has increased dramatically, but manual running is time-consuming and laborious. Therefore, it is necessary to establish databases that combine computer algorithms to summarize, analyze, and design new AMPs. A number of AMP databases have already been established, such as the Antimicrobial Peptides Database (APD), the Collection of Antimicrobial Peptides (CAMP), the Database of Antimicrobial Activity and Structure of Peptides (DBAASP), and the Database of Antimicrobial Peptides (dbAMPs). These four AMP databases are comprehensive and are widely used. This review aims to cover the construction, evolution, characteristic function, prediction, and design of these four AMP databases. It also offers ideas for the improvement and application of these databases based on merging the various advantages of these four peptide libraries. This review promotes research and development into new AMPs and lays their foundation in the fields of druggability and clinical precision treatment.

Indexed as

Anti-Infective AgentsAntimicrobial PeptidesAlgorithmsAnti-Bacterial AgentsPeptidesAnti-Bacterial AgentsAnti-Infective AgentsAntimicrobial PeptidesPeptidesantimicrobial peptidescharacteristic functiondatabasesscreening model

Identifiers

PMID36834553
PMCPMC9960615

What OpenQuestion holds

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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.