Xiaoming Zhang

According to the Food and Agriculture Organization of the United Nations (FAO), pests reduce global crop production by 14% annually. The growing challenge of pest resistance, coupled with the relatively low success rates of pesticides, has prompted researchers to shift their attention towards the accurate evaluation of insecticide lead. In contrast to in vitro methods of structural similarity or target affinity, the ‘insecticide‐likeness’ approach emphasises the in vivo biological effects of compounds, thereby constructing precise and comprehensive evaluation rules. In the present study, a multi‐scale qualitative‐quantitative insecticide‐likeness evaluation platform, Agrochem Predictive Platform for Insecticide‐likeness (APPi), was developed. An APPi rule was proposed for qualitative evaluation (ClogP ≤ 7, ARB ≤ 18, HBA ≤ 7, HBD ≤ 2, PFI ≤ 8 and ROB ≤ 10). A quantitative insecticide‐likeness evaluation model, the APPi model, was developed based on a multi‐classifier integrated machine learning framework (PUMV). The APPi model demonstrated excellent performance on the train and external test sets. Crucially, on the independent external test set, it achieved an accuracy of 85%, which represents a significant improvement over existing models. Furthermore, we developed the FragScore Visualiser tool to identify critical insecticidal fragments of compounds. The APPi platform provides precise guidance for virtual screening and structure optimisation of lead compounds in the early stage of insecticides discovery. The platform is available free of charge at http://pesticides.cau.edu.cn/APPi .

Fungal chitin deacetylase (CDA) plays a crucial role in pathogen-plant interactions, which is regarded as an innovative and promising target for fungicides. In this study, a pharmacophore-based virtual screening strategy was employed to identify compounds VS-24 and VS-25 as potent inhibitors against Puccinia striiformis f. sp. tritici CDA (PstCDA). Further bioassays demonstrated that VS-24 exhibited a protective effect of 61.2% against rice blast at 100 μg/mL, while VS-25 showed a superior protective effect of 45.5% against corn rust at 5 μg/mL, both superior to the reported CDA inhibitor benzohydroxamic acid (BHA). Molecular dynamics simulations revealed that multiple key interactions involving the Zn²⁺ ion and residues His207 and Tyr152 of PstCDA are critical for the binding of VS-24 or VS-25, with electrostatic interactions contributing most significantly to the binding free energy. Finally, toxicity predictions confirmed the potential biosafety of VS-24 and VS-25. Overall, this study identified two promising lead compounds targeting fungal CDA to control plant diseases.

The metabolism of environmental organic chemicals often relies on the catalytic action of specific enzymes at the nanoscale, which is critical for assessing their environmental impact, safety, and efficacy. Hydrolysis is one of the primary metabolic and degradation reaction pathways. Traditionally, hydrolysis product identification has relied on experimental methods that are both time-consuming and costly. In this study, machine-learning-based atomic-driven models were constructed to predict the hydrolysis reactions for environmental organic chemicals, including four main hydrolysis sites: N-Hydrolysis, O-Hydrolysis, C-Hydrolysis, and Global-Hydrolysis. These machine learning models were further integrated with a knowledge-based expert system to create a global hydrolysis model, which utilizes predicted hydrolysis site probabilities to prioritize potential hydrolysis products. For an external test set of 75 chemicals, the global hydrolysis site prediction model achieved an accuracy of 93%. Additionally, among 99 experimental hydrolysis products, our model successfully predicted 90, with a hit rate of 90%. This model offers significant potential for identifying hydrolysis metabolites in environmental organic chemicals.

Bees, one of the most vital pollinators in the ecosystem and agriculture, are currently threatened by neonicotinoids. To explore the molecular mechanisms of neonicotinoid toxicity to bees, the different binding modes of imidacloprid, thiacloprid, and flupyradifurone with nicotinic acetylcholine receptor (nAChR) α1β1 and cytochrome P450 9Q3 (CYP9Q3) were studied using homology modeling and molecular dynamics simulations. These mechanisms provided a basis for the design of compounds with a potential low bee toxicity. Consequently, we designed and synthesized a series of triazinone derivatives and assessed their bioassays. Among them, compound 5a not only displayed substantially insecticidal activities against Aphis glycines (LC₅₀ = 4.40 mg/L) and Myzus persicae (LC₅₀ = 6.44 mg/L) but also had low toxicity to Apis mellifera. Two-electrode voltage clamp recordings further confirmed that compound 5a interacted with the M. persicae nAChR α1 subunit but not with the A. mellifera nAChR α1 subunit. This work provides a paradigm for applying molecular toxic mechanisms to the design of compounds with low bee toxicity, thereby aiding the future rational design of eco-friendly nicotinic insecticides.

Insect growth regulators (IGRs) are important green insecticides that disrupt normal growth and development in insects to reduce the harm caused by pests to crops. The ecdysone receptor (EcR) and three chitinases OfChtI, OfChtII, and OfChi-h are closely associated with the molting stage of insects. Thus, they are considered promising targets for the development of novel insecticides such as IGRs. Our previous work identified a dual-target compound 6j, which could act simultaneously on both EcR and OfChtI. In the present study, 6j was first found to have inhibitory activities against OfChtII and OfChi-h, too. Subsequently, taking 6j as a lead compound, 19 novel acetamido derivatives were rationally designed and synthesized by introducing an acetamido moiety into the amide bridge based on the flexibility of the binding cavities of 6j with EcR and three chitinases. Then, their insecticidal activities against Plutella xylostella (P. xylostella), Ostrinia furnacalis (O. furnacalis), and Spodoptera frugiperda (S. frugiperda) were carried out. The bioassay results revealed that most of these acetamido derivatives possessed moderate to good larvicidal activities against three lepidopteran pests. Especially, compound I-17 displayed excellent insecticidal activities against P. xylostella (LC₅₀, 93.32 mg/L), O. furnacalis (LC₅₀, 114.79 mg/L), and S. frugiperda (86.1% mortality at 500 mg/L), significantly better than that of 6j. In addition, further protein validation and molecular docking demonstrated that I-17 could act simultaneously on EcR (17.7% binding activity at 8 mg/L), OfChtI (69.2% inhibitory rate at 50 μM), OfChtII (71.5% inhibitory rate at 50 μM), and OfChi-h (73.9% inhibitory rate at 50 μM), indicating that I-17 is a potential lead candidate for novel multitarget IGRs. This work provides a promising starting point for the development of novel types of IGRs as pest management agents.

Novel agrochemicals have been successfully developed using target-based drug design (TBDD). To discover a novel, efficient, and highly selective nicotinic insecticide candidate, we developed a unified pharmacological model using TBDD by studying the binding modes of 11 nicotinic acetylcholine receptor (nAChR) modulators with acetylcholine binding protein (AChBP) targets for the first time. This model was used to design and develop a series of 1,2,4-triazolone derivatives. Bioassays demonstrated excellent insecticidal activities against Aphis glycines of compounds 4k (LC₅₀ = 4.95 mg/L) and 4q (LC₅₀ = 3.17 mg/L), and low toxicities to Apis mellifera. Additionally, compound 4q was stably bound to Aplysia californica AChBP, which was consistent with the pharmacological model obtained via molecular docking and molecular dynamics simulations. Therefore, compound 4q could be a potential lead candidate targeting nAChR. The explicit pharmacological model of nAChR modulators with Ac-AChBP in this study may facilitate the future rational design of eco-friendly nicotinic insecticides.

To discover fungicides with novel targets, a series of N-acyl-1,2,3,4-tetrahydroquinoline (NATHQ) derivatives were designed and synthesized by linking the active substructure NATHQ moiety in aspernigerin with the O-benzyl oxime-ether scaffold in commercial agrochemicals. Target compound structures were identified using proton and carbon-13 nuclear magnetic resonance spectroscopies and high-resolution mass spectrometry. Preliminary bioassays indicated that at 40 mg/L, some target compounds exhibited moderate to considerable in vitro fungicidal activities against Rhizoctonia solani and Botrytis cinerea. In particular, compound 3j exhibited higher fungicidal activities both in vitro (EC₅₀ = 0.733 mg/L) and in vivo (EC₅₀ = 15.2 mg/L) against R. solani than the commercial fungicide prochloraz; therefore, it should be a promising fungicide candidate against rice sheath blight. Additionally, compound 3j exhibited good laccase inhibitory activity (73.2% at 200 mg/L). Molecular docking revealed that the bis-cyano-oxime-ether moiety of compound 3j exhibited an excellent binding mode with the laccase target protein and could be used as a lead compound for developing laccase inhibitors. The structural features of these NATHQ derivatives will provide inspiration for developing laccase inhibitors and discovering more effective fungicides to control agricultural diseases.

Both insect ecdysone receptors and ultraspiracle belong to the nuclear receptor family. They form a nanoscale self-assembling complex with ecdysteroids in cells, transit into the nucleus, bind with genes to initiate transcription, and perform specific biological functions to regulate the molting, metamorphosis, and growth processes of insects. Therefore, this complex is an important target for the development of eco-friendly insecticides. The diamondback moth (Plutella xylostella) is a devastating pest of cruciferous vegetable crops, wreaking havoc worldwide and causing severe economic losses, and this pest has developed resistance to most chemical insecticides. In this study, highly pure EcR and USP functional domains were obtained by constructing a prokaryotic expression system for the diamondback moth EcR and USP functional domain genes, and the differences between EcR and USP binding domain monomers and dimers were analyzed using transmission electron microscopy and zeta potential. Radioisotope experiments further confirmed that the binding affinity of PonA to the EcR/USP dimer was enhanced approximately 20-fold compared with the binding affinity to the PxGST−EcR monomer. The differences between PonA and tebufenozide in binding with EcR/USP were examined. Molecular simulations showed that the hydrogen bonding network formed by Glu307 and Arg382 on the EcR/USP dimer was a key factor in the affinity enhancement. This study provides a rapid and sensitive method for screening ecdysone agonists for ecdysone receptor studies in vitro.