Quantitative structure-transformation relationships of phenylurea herbicides

Design, Synthesis, and Herbicidal Activity of Substituted 3-(Pyridin-2-yl)Phenylamino Derivatives

To discover protoporphyrinogen oxidase (PPO) inhibitors with robust herbicidal activity and crop safety, three types of substituted 3-(pyridin-2-yl)phenylamino derivatives bearing amide, urea, or thiourea as side chain were designed via structure splicing strategy. Postemergence herbicidal activity assessment of 33 newly prepared compounds revealed that many of our compounds such as 6a, 7b, and 8d exhibited superior herbicidal activities against broadleaf and monocotyledon weeds to commercial acifluorfen. In particular, compound 8d exhibited excellent herbicidal activities and high crop safety at a dosage range of 37.5-150 g ai/ha. PPO inhibitory studies supported our compounds as typical PPO inhibitors. Molecular docking studies revealed that compound 8d provided effective interactions with Nicotiana tabacum PPO (NtPPO) via diverse interaction models, such as π-π stacking and hydrogen bonds. Molecular dynamics (MD) simulation studies and degradation studies were also conducted to gain insight into the inhibitory mechanism. Our study indicates that compound 8d may be a candidate molecule for the development of novel herbicides.

Prediction of the Fate of Organic Compounds in the Environment From Their Molecular Properties: A Review

A comprehensive review of quantitative structure-activity relationships (QSAR) allowing the prediction of the fate of organic compounds in the environment from their molecular properties was done. The considered processes were water dissolution, dissociation, volatilization, retention on soils and sediments (mainly adsorption and desorption), degradation (biotic and abiotic), and absorption by plants. A total of 790 equations involving 686 structural molecular descriptors are reported to estimate 90 environmental parameters related to these processes. A significant number of equations was found for dissociation process (pKa), water dissolution or hydrophobic behavior (especially through the KOW parameter), adsorption to soils and biodegradation. A lack of QSAR was observed to estimate desorption or potential of transfer to water. Among the 686 molecular descriptors, five were found to be dominant in the 790 collected equations and the most generic ones: four quantum-chemical descriptors, the energy of the highest occupied molecular orbital (EHOMO) and the energy of the lowest unoccupied molecular orbital (ELUMO), polarizability (α) and dipole moment (μ), and one constitutional descriptor, the molecular weight. Keeping in mind that the combination of descriptors belonging to different categories (constitutional, topological, quantum-chemical) led to improve QSAR performances, these descriptors should be considered for the development of new QSAR, for further predictions of environmental parameters. This review also allows finding of the relevant QSAR equations to predict the fate of a wide diversity of compounds in the environment.

Quantitative structure-transformation relationships of sulfonylurea herbicides

Model development to predict transformation of sulfonylureas in different matrices was carried out using multiple linear regression. Descriptors for lipophilicity and molecular topology, as well as quantum chemical descriptors for energy, geometry, polarity, charges and reactivity using MOPAC with three different Hamiltonians, AM1, PM3 and MNDO, were calculated. In addition, experimental descriptors were measured and taken from the literature. End-points were transformation rates of twelve sulfonylurea herbicides in buffers at different pH (4, 7 and 10), in sterile and native sediments, and in sterile and native soil. Inter-correlation of reaction rates indicated four different groups of transformation types, for which sum parameters were calculated. (1) Hydrolysis at pH 4 could be estimated with pKa and charges at a specific atom of the heterocycle. (2) Hydrolysis at pH 7 and 10, as well as transformation in sterile sediments and soil, could be described with descriptors for reactivity (polarisability and superdelocalisability) at specific atoms of the molecules. (3) For transformation in native sediments different models could be found, all based on descriptors for polarisability, superdelocalisability and charges at specific atoms. (4) Modelling of biotransformation in native soil led to diverse models with a variety of descriptors reflecting electronic properties and lipophilicity. Models confirmed previous findings on reaction mechanisms and thereby prove valuable not only for quantitative prediction of reaction rates, but also for studies on transformation pathways.