bioRxivBiochemistry
Design and optimization of novel succinate dehydrogenase inhibitors against agricultural fungi based on Transformer model
C. Pian, Y. Zhang, J. Chai, L. Li, W. Zhao, L. Zhang, Y. Chen, Z. Xu, C. Yang
Abstract
Succinate dehydrogenase inhibitors (SDHIs) are a promising class of fungicides targeting the energy production pathway of pathogenic fungi. However, overuse has led to resistance, necessitating the development of new and effective SDHIs. This study takes 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 testing, and structural optimization further refined these leads into potent SDHI candidates. This work marks the first application of a generative model to SDHI design, establishing a robust workflow for virtual library generation, screening, activity evaluation, and structure optimization. This provides one way for the rational design of future SDHIs, not only against fungi, but potentially other agricultural pathogens as well.
- research focus: drug response / drug discovery
- approach: deep learning
- approach: transformer / foundation model
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