ArticleMolecular diversity2026
Design and optimization of novel succinate dehydrogenase inhibitors against agricultural fungi based on transformer model.
Article in Molecular diversity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Fluopyram in agricultural ecosystems: environmental fate, microbial transformation, ecotoxicity, and resistance risks of an SDHI fungicide.Frontiers in microbiology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Succinate dehydrogenase (SDH), also termed complex II or succinate-ubiquinone oxidoreductase, is a crucial biological enzyme in the process of mitochondrial oxidative phosphorylation. Succinate dehydrogenase inhibitors (SDHIs) are a promising class of fungicides targeting the energy production pathway of pathogenic fungi. However, overuse has resulted in the emergence of resistance, underscoring the need for novel and effective SDHIs. This study utilized the Transformer model to generate a customized virtual library of potential SDHIs. These candidates were then meticulously screened based on expert knowledge and synthetic feasibility, ultimately yielding several pyrazole carboxamide derivatives as the promising leads. Subsequent synthesis, antifungal activity assessment, and structural optimization further refined these leads into potent SDHI candidates. This work represents the first application of a generative model to SDHI design, establishing a robust workflow encompassing virtual library generation, screening, activity evaluation, and structure optimization. This study paves the way for the rational design of future SDHIs, not only against fungi, but potentially other agricultural pathogens as well.
Indexed as
Identifiers
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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.