Evidence map›Paper›PMID 42921313›Full record

ReviewACS bio & med chem Au2026

Antimicrobial Peptides Beyond the Petri Dish: Translational Barriers to Therapeutic Development.

Marc Torrent

Abstract readReview
In one paragraph

Review in ACS bio & med chem Au, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Marc TorrentThe Systems Biology of Infection Laboratory, Department of Biochemistry and Molecular Biology, Biosciences Faculty, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona 08193, Spain.ORCID https://orcid.org/0000-0001-6567-3474

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial peptides (AMPs) are promising antibiotics with rapid bactericidal mechanisms, broad-spectrum activity, and efficacy against drug-resistant pathogens. Yet, despite decades of research and development of many active AMPs, translation to the clinic remains limited. Although AMPs kill bacteria efficiently under optimized conditions, the same properties that enable membrane disruption - cationic charge, amphipathicity, and hydrophobicity - also cause their sequestration, degradation, and inactivation in biological fluids and tissues. This review examines how the major administration routes shape AMP pharmacokinetics and identifies the barriers that must be overcome for effective clinical translation. Each route imposes different limitations: oral delivery is limited by proteolytic degradation, bile sequestration, and poor absorption; intravenous administration by plasma protein binding, proteolysis, restricted tissue penetration, and nephrotoxicity; inhaled delivery by sequestration and inactivation in mucus and pulmonary surfactant; and topical delivery by impaired diffusion, sequestration, and proteolysis within wound and biofilm matrices. These limitations should be addressed from the outset of AMP design, with clear strategies on how to control serum binding, protect against protease digestion, and optimize charge and hydrophobic moment, to off-target interactions and toxicity. A pharmacologically informed approach that incorporates these barriers as design constraints is essential to transform AMPs into clinically effective drugs.

Indexed as

antimicrobial peptidesbioavailabilitybiofilmclinical translationdrug deliverypeptide antibioticspharmacodynamicspharmacokineticsproteolysisserum protein binding

Identifiers

PMID42921313
PMCPMC13692726

What OpenQuestion holds

Textmetadata
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.