Design, Synthesis, and Bioactivity of Novel 2-(Arylformyl)cyclohexane-1,3-dione Derivatives as HPPD Inhibitors.

4-Hydroxyphenylpyruvate dioxygenase inhibitors (Echinochloa crus-galli 1.13.11.27, HPPD) have gained significant popularity as one of the best-selling herbicides worldwide. To identify highly effective HPPD inhibitors, a rational design approach utilizing bioisosterism was employed to create a series of 2-(arylformyl)cyclohexane-1,3-dione derivatives. A total of 29 novel compounds were synthesized and characterized through various techniques, including IR, 1H NMR, 13C NMR, and HRMS. Evaluation of their inhibitory activity against Arabidopsis thaliana HPPD (AtHPPD) revealed that certain derivatives exhibited superior potency compared to mesotrione (IC50 = 0.204 µM). Initial herbicidal activity tests demonstrated that compounds 27 and 28 were comparable to mesotrione in terms of weed control and crop safety, with compound 28 exhibiting enhanced safety in canola crops. Molecular docking analyses indicated that the quinoline rings of compounds 27 and 28 formed more stable π-π interactions with the amino acid residues Phe-360 and Phe-403 in the active cavity of AtHPPD, surpassing the benzene ring of mesotrione. Molecular dynamics simulations and molecular structure comparisons confirmed the robust binding capabilities of compounds 27 and 28 to AtHPPD. This study provides a valuable reference for the development of novel triketone herbicide structures, serving as a blueprint for future advancements in this field.

Design, synthesis and biological activity of novel triketone herbicides containing natural product fragments.

4-Hydroxyphenylpyruvate dioxygenase (EC 1.13.11.27, HPPD) belongs to the non-heme Fe2+ - containing enzyme family and is an important enzyme in tyrosine decomposition. HPPD is crucial to the discovery of novel bleaching herbicides. To develop novel HPPD inhibitor herbicides containing the ß-triketone motif, a series of 4-hydroxyl-3-(substituted aryl)-pyran-2-one derivatives were designed using the active fragment splicing method. The title compounds were synthesized and characterized through infrared spectroscopy (IR), 1H nuclear magnetic resonance (1H NMR), 13C nuclear magnetic resonance (13C NMR), and high-resolution mass spectrometry (HRMS). The X-ray diffraction method determined the single crystal structure of I-17. Preliminary bioassay data revealed that several novel compounds, especially I-12 and II-3, showed excellent herbicidal activity against broadleaf and monocotyledonous weeds at a dose of 150 g ai/ha. The results of crop selectivity and carotenoids determination indicated that compound I-12 is more suitable for wheat and cotton fields than mesotrione. Additionally, compound II-3 is safer for soybeans and peanuts than mesotrione. The inhibitory activity of Arabidopsis thaliana HPPD (AtHPPD) verified that compound II-3 showed the most activity with an IC50 value of 0.248 µM, which was superior to that of mesotrione (0.283 µM) in vitro. The binding mode of compound II-3 and AtHPPD was confirmed through molecular docking and molecular dynamics simulations. This study provides insights into the future development of natural and efficient herbicides.

A Discrete Fruit Fly Optimization Algorithm for the Traveling Salesman Problem.

The fruit fly optimization algorithm (FOA) is a newly developed bio-inspired algorithm. The continuous variant version of FOA has been proven to be a powerful evolutionary approach to determining the optima of a numerical function on a continuous definition domain. In this study, a discrete FOA (DFOA) is developed and applied to the traveling salesman problem (TSP), a common combinatorial problem. In the DFOA, the TSP tour is represented by an ordering of city indices, and the bio-inspired meta-heuristic search processes are executed with two elaborately designed main procedures: the smelling and tasting processes. In the smelling process, an effective crossover operator is used by the fruit fly group to search for the neighbors of the best-known swarm location. During the tasting process, an edge intersection elimination (EXE) operator is designed to improve the neighbors of the non-optimum food location in order to enhance the exploration performance of the DFOA. In addition, benchmark instances from the TSPLIB are classified in order to test the searching ability of the proposed algorithm. Furthermore, the effectiveness of the proposed DFOA is compared to that of other meta-heuristic algorithms. The results indicate that the proposed DFOA can be effectively used to solve TSPs, especially large-scale problems.