Evidence map›Paper›PMID 32355003›Full record

ReviewScience (New York, N.Y.)2020

Antimicrobial peptides: Application informed by evolution.

Brian P Lazzaro, Michael Zasloff, Jens Rolff

Open access · greenAbstract readReview
In one paragraph

Review in Science (New York, N.Y.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 481 papers.

0numbers the graph read from it
0cells of the map it votes in
481citing papers in PubMed
76.3field-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

481 citing papers in PubMed, 1,035 citations in OpenAlex.

  1. Trial
  2. Artificial intelligence catalyzes antimicrobial peptide design.Synthetic and systems biotechnology · 2027
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421 more citing papers are in PubMed but not listed here.

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

3 authors at 3 institutions in 2 countries.

Brian P LazzaroDepartment of Entomology, Cornell Institute of Host-Microbe Interactions and Disease, Cornell University, Ithaca, NY, USA.ORCID 0000-0002-3881-0995
Michael ZasloffMedStar Georgetown Transplant Institute, Georgetown University School of Medicine, Washington, DC, USA.
Jens RolffFreie Universität Berlin, Evolutionary Biology, Institut für Biologie, Königin-Luise-Strasse 1-3, 14195 Berlin, Germany. jens.rolff@fu-berlin.de.ORCID 0000-0002-1529-5409
Berlin Brandenburg Institute of Advanced Biodiversity Research · DECornell University · USGeorgetown University · US

Funding

Mechanisms and Evolutionary Consequences of a Reproduction-Immunity TradeoffR01AI141385 · NIAID · CORNELL UNIVERSITY · PI LAZZARO, BRIAN · 2019 to 2024
$2.6M
European Research CouncilNIAID NIH HHS R01 AI141385
6 · The paper itself

Abstract

Antimicrobial peptides (AMPs) are essential components of immune defenses of multicellular organisms and are currently in development as anti-infective drugs. AMPs have been classically assumed to have broad-spectrum activity and simple kinetics, but recent evidence suggests an unexpected degree of specificity and a high capacity for synergies. Deeper evaluation of the molecular evolution and population genetics of AMP genes reveals more evidence for adaptive maintenance of polymorphism in AMP genes than has previously been appreciated, as well as adaptive loss of AMP activity. AMPs exhibit pharmacodynamic properties that reduce the evolution of resistance in target microbes, and AMPs may synergize with one another and with conventional antibiotics. Both of these properties make AMPs attractive for translational applications. However, if AMPs are to be used clinically, it is crucial to understand their natural biology in order to lessen the risk of collateral harm and avoid the crisis of resistance now facing conventional antibiotics.

Indexed as

Drug Resistance, BacterialEvolution, MolecularAnimalsAnti-Bacterial AgentsAntimicrobial Cationic PeptidesDrosophila ProteinsDrug SynergismHumansPolymorphism, GeneticTranslational Research, BiomedicalAnti-Bacterial AgentsAntimicrobial Cationic PeptidesDptA protein, DrosophilaDrosophila Proteins

Identifiers

PMID32355003
PMCPMC8097767
OpenAlexW3023413280

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.