Investigating the Herbicidal Potential of Substituted Urea Derivatives as HPPD Inhibitors: A Comparative Computational Study with Standard Mesotrione

Abstract

ABSTRACT The cumulative pervasiveness of herbicide-resistant weeds demands the improvement of novel herbicides with superior efficiency, selectivity and environmental protection. In this study, a series of substituted urea derivatives were computationally assessed as potential inhibitors of 4-hydroxyphenylpyruvate dioxygenase (HPPD) using a combined workflow comprising molecular docking, MM-GBSA binding free energy calculations, physicochemical and herbicide-likeness assessment, ADMET and toxicity prediction, molecular dynamics (MD) simulations and density functional theory (DFT) analysis. Molecular docking result recognized Compound 2 as the most promising candidate, displaying a superior binding affinity (MolDock score: -166.256kcal/mol) compared with the reference herbicide Mesotrione ( - 118.689kcal/mol) through favorable hydrogen bonding, hydrophobic, π- π interactions and van der Waals interactions. MM-GBSA calculations additionally confirmed the thermodynamic stability of the protein-ligand complex, with Compound 2 demonstrating the most favorable binding free energy among all the evaluated compounds. ADMET, toxicity and herbicide-likeness analyses demonstrated desirable agrochemical characteristics and a favorable predicted safety profile. Furthermore, 100ns MD simulations revealed that the Compound 2-HPPD complex exhibited greater structural stability, persistent intermolecular interactions and improved conformational integrity relative to Mesotrione. DFT analysis indicated enhanced electronic stability and appropriate chemical reactivity, supporting efficient molecular recognition within the HPPD active site. Cooperatively, the strong agreement among docking, MM-GBSA, MD, DFT and ADMET analyses identifies Compound 2 as the most promising lead in this series. These findings highlight substituted urea derivatives as valuable scaffolds for the rational design of next-generation HPPD inhibitors and provide a robust computational basis for future experimental validation and herbicide development.