Evidence map›Paper›PMID 40828433›Full record

ArticleMolecular diversity2026

Design and optimization of novel succinate dehydrogenase inhibitors against agricultural fungi based on transformer model.

Yuan Zhang, Jianqi Chai, Ling Li, Wenqian Zhao, Jinwen Ji, Yanru Li, Ziyu Wang, Yuanyuan Chen, Liangyun Zhang, Zhihui Xu and 2 more

Abstract read
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In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

12 authors.

Yuan Zhang *College of Agriculture, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
Jianqi Chai *College of Science, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
Ling LiZhejiang Laboratory, Hangzhou, 311100, Zhejiang, China.
Wenqian ZhaoCollege of Science, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
Jinwen JiCollege of Agriculture, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
Yanru LiCollege of Agriculture, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
Ziyu WangCollege of Food Science and Technology, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
Yuanyuan ChenCollege of Science, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
Liangyun ZhangCollege of Science, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
Zhihui XuSchool of Pharmacy, China Pharmaceutical University, Nanjing, 211198, Jiangsu, China. xuzhihui234@sina.com.
Chunlong YangCollege of Science, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China. ycl@njau.edu.cn.
Cong PianCollege of Science, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China. piancong@njau.edu.cn.

Funding

National Natural Science Foundation of China ZX2200521
6 · The paper itself

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

Antifungal AgentsDrug DesignEnzyme InhibitorsFungiSuccinate DehydrogenaseMicrobial Sensitivity TestsModels, MolecularStructure-Activity RelationshipAntifungal AgentsEnzyme InhibitorsSuccinate DehydrogenaseAntifungal activity evaluationDeep generation modelDrug designMolecular dockingSuccinate dehydrogenaseSuccinate dehydrogenase inhibitors

Identifiers

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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.