Shielding Metabolic Hotspots in the Triketone-Quinoline Scaffold Yields Potent 4-Hydroxyphenylpyruvate Dioxygenase Inhibitors

  • J Agric Food Chem. 2026 Jul 29;74(29):22507-22518. doi: 10.1021/acs.jafc.5c15585.
Min Li  1 Han Xiao  1 Si-Mei Zhou  1 Zi-Xuan Li Li-Jun Chen  1 Lei Wu  1 Jun-Jie Huang  1 Wishwajith Kandegama  2 Ismail Ismail  3 Qiong Chen  1 Da-Wei Wang  1
Affiliations
  • 1. International Joint Research Center for Intelligent Biosensor Technology and Health, Central China Normal University, Wuhan430079, P. R. China.
  • 2. Department of Horticulture and Landscape Gardening, Faculty of Agriculture and Plantation Management, Wayamba University of Sri Lanka, Makandura, Gonawila (NWP)60170, Sri Lanka.
  • 3. Department of Chemistry and Biochemistry, Materials Science Institute, Knight Campus for Accelerating Scientific Impact, and Institute of Molecular Biology, University of Oregon, Eugene, Oregon97403-1253, United States.
Abstract

4-Hydroxyphenylpyruvate dioxygenase (HPPD; EC 1.13.11.27) is an important target for modern Herbicide discovery. To translate HPPD inhibitors into effective Herbicide candidates, we developed a metabolism-oriented design strategy to improve the in vivo efficacy of triketone-quinoline HPPD inhibitors. By shielding the metabolic hotspots within the scaffold, we discovered a series of new analogues with broadly improved postemergence herbicidal activity and substantially enhanced inhibition of Arabidopsis thaliana HPPD (AtHPPD). Notably, 9i showed a Ki value of 0.0012 μM toward AtHPPD, outperforming mesotrione by an order of magnitude. 11b not only exhibited excellent weed control at 15.625-250 g ai/ha, but also showed high crop safety to wheat at 250 g ai/ha. Molecular simulations showed that quinoline substitutions could enhance π-π interactions with Phe360 and Phe403, improving bioactivity. Our work establishes a metabolism-guided optimization framework for Herbicide discovery and provides a promising wheat-selective Herbicide candidate.

Keywords
HPPD; herbicide; metabolic hotspots; metabolism-guided optimization; molecular design.
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