Evidence map›Paper›PMID 33852346›Full record

ReviewAnnual review of biomedical engineering2021

Engineering Selectively Targeting Antimicrobial Peptides.

Ming Lei, Arul Jayaraman, James A Van Deventer, Kyongbum Lee

Open access · hybridAbstract readReview
In one paragraph

Review in Annual review of biomedical engineering, 2021. 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
6.0field-weighted citation impact, top 3% 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, 66 citations in OpenAlex.

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  10. Lactic Acid Bacteria Bacteriocins: Safe and Effective Antimicrobial Agents.International journal of molecular sciences · 2025
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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 at 2 institutions in 1 country.

Ming LeiDepartment of Chemical and Biological Engineering, Tufts University, Medford, Massachusetts 02155, USA; email: ming.lei@tufts.edu, James.Van_Deventer@tufts.edu, kyongbum.lee@tufts.edu.
Arul JayaramanArtie McFerrin Department of Chemical Engineering and Department of Biomedical Engineering, Texas A&M University, College Station, Texas 77843, USA; email: arulj@mail.che.tamu.edu.
James A Van DeventerDepartment of Chemical and Biological Engineering, Tufts University, Medford, Massachusetts 02155, USA; email: ming.lei@tufts.edu, James.Van_Deventer@tufts.edu, kyongbum.lee@tufts.edu.
Kyongbum LeeDepartment of Chemical and Biological Engineering, Tufts University, Medford, Massachusetts 02155, USA; email: ming.lei@tufts.edu, James.Van_Deventer@tufts.edu, kyongbum.lee@tufts.edu.
Tufts University · USTexas A&M Health Science Center · US

Funding

Microbial flavonoid metabolites as modulators of AD markers in a 3D human neural tissue modelR01AT010282 · NCCIH · TEXAS A&M AGRILIFE RESEARCH · PI CHAPKIN, ROBERT STEPHEN, JAYARAMAN, ARUL · 2018 to 2021
$1.9M
NCCIH NIH HHS R01 AT010282
6 · The paper itself

Abstract

The rise of antibiotic-resistant strains of bacterial pathogens has necessitated the development of new therapeutics. Antimicrobial peptides (AMPs) are a class of compounds with potentially attractive therapeutic properties, including the ability to target specific groups of bacteria. In nature, AMPs exhibit remarkable structural and functional diversity, which may be further enhanced through genetic engineering, high-throughput screening, and chemical modification strategies. In this review, we discuss the molecular mechanisms underlying AMP selectivity and highlight recent computational and experimental efforts to design selectively targeting AMPs. While there has been an extensive effort to find broadly active and highly potent AMPs, it remains challenging to design targeting peptides to discriminate between different bacteria on the basis of physicochemical properties. We also review approaches for measuring AMP activity, point out the challenges faced in assaying for selectivity, and discuss the potential for increasing AMP diversity through chemical modifications.

Indexed as

Antimicrobial PeptidesProtein EngineeringAnti-Bacterial AgentsBacteriaHumansAnti-Bacterial AgentsAntimicrobial Peptidesantimicrobial peptidescell selectivityhigh-throughput screeningmachine learningmicrobiotapeptide conjugates

Identifiers

PMID33852346
PMCPMC9017812
OpenAlexW3156544690

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.