Novel Artificial Intelligence platform leads to the discovery of new protoporphyrinogen oxidase inhibitors

Abstract

Weed control is essential in modern agriculture, though it has become more difficult with the emergence of resistance to most current herbicides and a slow registration process of new compounds. A new approach to identify possible herbicide candidates using an artificial intelligence algorithm that takes into effect biological parameters with the goal of reducing R&D time on new herbicides. Herein we describe the discovery of 4-chloro-2-pentenamides as novel inhibitors of protoporphyrinogen oxidase, a known herbicide target site, by the Agrematch AI. The herbicidal activity is confirmed in greenhouse assays, with the highest performing AGR001 showing good activity pre-emergent at 150 g/ha and post emergent as low as 50 g/ha on the troublesome weed palmer amaranth (Amaranthus palmeri). A lack of activity is reported on PPO resistant palmer amaranth carrying the glycine 210 deletion (ΔG210) mutation. The mechanism of action is confirmed by the herbicide-dependent accumulation of protoporphyrin IX, subsequent light-dependent loss of membrane integrity, and direct in vitro inhibition of protoporphyrinogen oxidase. Modeling of the docking of these inhibitors in the active site of protoporphyrinogen oxidase illustrates that their flexible side chains can accommodate a number of poses in the catalytic domain.