Abstract

Mesotrione is a triketone widely used as an inhibitor of the hydroxyphenylpyruvate deoxygenase (HPPD) enzyme. However, new agrochemicals should be continuously developed to tackle the problem of herbicide resistance. Two sets of mesotrione analogs have been recently synthesized and demonstrated successful phytotoxicity against weeds. Herein, these compounds were joined as to form a single data set and the HPPD inhibition of this enlarged library of triketones was modeled using multivariate image analysis applied to quantitative structure-activity relationships (MIA-QSAR). Further, docking studies were carried out to validate the MIA-QSAR findings and aid the interpretation of ligand-enzyme interactions responsible for the bioactivities (pIC50 ). The MIA-QSAR models based on van der Waals radii (rvdW ), electronegativity (ε), and rvdW /ε ratio as molecular descriptors were similarly and satisfactorily predictive (r2 ≥ 0.80, q2 ≥ 0.68, and r2 pred ≥ 0.68). Subsequently, the PLS regression parameters were applied to predict the pIC50 values of newly proposed derivatives, yielding a few promising agrochemical candidates. In addition, the calculated log P for most of these derivatives was found to be higher than that of mesotrione and the library compounds, indicating that they should be less prone to leach out and contaminate groundwater. MIA descriptors corroborated by docking studies were capable of reliably modeling the herbicidal activities of 68 triketones. Due to the substituent effects at the triketone framework, particularly of a nitro group in R3 , promising analogs could be designed. The P9 proposal demonstrated higher calculated activity and log P than the commercial mesotrione.

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