Identification and Rational Design of Novel Antimicrobial Peptides for Plant Protection
Abstract
Peptides and small proteins exhibiting antimicrobial activity have been isolated from many organisms ranging from insects to humans, including plants. Their role in defense is established, and their use in agriculture was already being proposed shortly after their discovery. However, some natural peptides have undesirable properties that complicate their application. Advances in peptide synthesis and high-throughput activity screening have made possible the de novo and rational design of novel peptides with improved properties. This review summarizes findings in the identification and design of short antimicrobial peptides with activity against plant pathogens, and will discuss alternatives for their heterologous production suited to plant disease control. Recent studies suggest that peptide antimicrobial action is not due solely to microbe permeation as previously described, but that more subtle factors might account for the specificity and absence of toxicity of some peptides. The elucidation of the mode of action and interaction with microbes will assist the improvement of peptide design with a view to targeting specific problems in agriculture and providing new tools for plant protection.
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Natural peptides have limitations including nonspecific toxicity, low stability, and poor bioavailability, which led researchers to attempts to artificially synthesize new AMPs with superior properties.
“However, limitations of natural peptides such as nonspecific toxicity, low stability, and poor bioavailability led researchers to attempts to artificially synthetize new AMPs with superior properties (Marcos et al., 2008).”
From GRAS, plant- and animal-derived compounds as alternatives to conventional fungicides for the control of postharvest diseases of fresh horticultural produce (2016) · cites this paper as Marcos et al., 2008
Antimicrobial peptides can be specifically designed and screened for a specific crop protection function.
“Moreover, they can also be specifically designed and screened for a specific crop protection function [78].”
From Biofuels from algae: Challenges and potential (2010) · cites this paper as [78]
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- Authors
- Marcos, J. F., Muñoz, A., Pérez-Payá, E., Misra, S., & López-García, B.
- Affiliations
- Departamento de Ciencia de los Alimentos, Instituto de Agroquímica y Tecnología de Alimentos (IATA)-CSIC, 46100 Burjassot, Spain;
- Consejo Superior de Investigaciones Científicas (ES)
- Centro de Investigación Príncipe Felipe (CIPF), 46013 Valencia, Spain; and Instituto de Biomedicina de Valencia (IBV)–CSIC;
- University of Victoria (CA)
- Venue
- Annual Review of Phytopathology
- Publisher
- Annual Reviews
- Published
- 2008-09-01
- Volume
- 46
- Issue
- 1
- Pages
- 273-301
- ISSN
- 0066-4286 (ISSN-L)
- 1545-2107
- OpenAlex
- W2114496961
- Cited by
- 205
- References
- 201
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 7 · 2023: 13 · 2022: 4 · 2021: 11 · 2020: 11 · 2019: 20 · 2018: 13 · 2017: 9 · 2016: 11 · 2015: 11 · 2014: 11 · 2013: 19 · 2012: 17
- FWCI
- 1.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Phytopathology (publishedVersion)
- PubMed (publishedVersion)
- Research Explorer (The University of Manchester) (publishedVersion)
- Topics
- Life Sciences › Immunology and Microbiology › Microbiology › Antimicrobial Peptides and Activities
- Physical Sciences › Chemistry › Organic Chemistry › Antimicrobial agents and applications
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant-Microbe Interactions and Immunity
- Keywords
- antimicrobial peptides, crop protection, plant pathogens, rational peptide design, mechanism of action, peptide specificity, toxicity, plant defense peptides, peptide synthesis, high-throughput screening, plant disease control
- MeSH terms
- Models, Biological, Plant Diseases, Plants, Drug Design, Peptide Library, Antimicrobial Cationic Peptides
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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