ReviewPlanta2025
Integrative multi-omics and computer-aided biofungicide design approach to combat fusarium wilt of chickpea.
Review in Planta, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
MAIN
conclusionIntegrating multi-omics and computer-aided drug discovery approaches can overcome the limitations of traditional methods and help develop highly effective, specific, and environmentally safe biofungicides to control crop diseases. Chickpea is a valuable legume crop in terms of nutrition, food security, economic sustainability, and environmental benefits. Fusarium wilt caused by the soil-borne fungus Fusarium oxysporum f.sp. ciceri is one of the most important diseases affecting chickpea. Several disease management methods, including crop rotation, soil fumigation with chemical fungicides, soil solarization, etc., are practiced to manage the disease. However, these methods have various limitations and cannot completely control the disease. Moreover, chemical fungicides indiscriminately kill even the beneficial soil microbes, pollute groundwater, and enter the food chain. Hence, modern approaches emphasizing innovative strategies and technologies need to be explored to manage the disease effectively. In this review, we propose integrating multi-omics (genomics, proteomics, metabolomics, etc.) and computer-aided drug discovery (CADD) approaches to develop biofungicides targeting vital pathogen proteins. Multi-omics approaches can delve deeper into the plant-pathogen interaction and reveal essential pathogen genes or proteins. These proteins could be targeted using CADD to identify phytochemical-based potential biofungicides, either using structure- or ligand-based drug design approaches. The potential biofungicides can be subjected to the prediction of carcinogenicity, hepatotoxicity, mutagenicity, etc., to identify biofungicides that are safe to use and are highly specific to the target pathogen. In vivo and in vitro validation studies can be followed to establish the efficacy and safety of the identified biofungicides for their practical application. This integrated approach can reduce the time and cost compared to the traditional methods and accelerate the discovery of highly effective biofungicides to protect crops from various diseases.
Indexed as
Identifiers
41003817What OpenQuestion holds
Registered trials
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.