Computer-Assisted Proposition of Promising Aryloxyacetic Acid Derivatives as HPPD Inhibitors

Computer-Aided Design and Pharmacophore-Based Screening of a Diverse Combinatorial Library of Phytoselective Aryloxyacetic Acid Derivatives as HPPD Inhibitors

We investigated the inhibitory potency of aryloxyacetic acid derivatives (AADs) on 4-hydroxyphenylpyruvate dioxygenase (HPPD), a crucial enzyme target for HPPD herbicide development. Developing a wide-ranging approach combining reported structure-activity relationships (SARs with the observed inhibitory potencies of the enzyme Kiexp), our simulations for molecular mechanics Poisson-Boltzmann (MM-PB) complexation quantitative SAR (QSAR) (computed relative Gibbs free energies of the HPPD-AADx complex formation ΔΔGcom), and three-dimensional (3D)-QSAR pharmacophore (PH4) models for screening the chemical subspace of aryloxyacetic acid derivatives (a virtual library of AADs, VL), we come out with a handful of novel AADs with promising predictive HPPD inhibitory potency and confirmed molecular dynamics (MD) conformational stability. The 3D-QSAR model revealed a correlation (pKiexp = a × ΔΔGcom + b) between computed data and observed inhibition ones: pKiexp = -0.0544 × ΔΔGcom + 6.93, R2 = 0.87 for a training set (TS) of 30 AAD (AAD1-30). The subsequent 3D-QSAR pharmacophore (PH4) of HPPD inhibition by AADs confirmed the correlation (pKiexp = 0.863 × pKipre + 7.92, R2 = 0.86) between PH4-predicted pKipre and the observed ones pKiexp. The structural information derived from these models suggested suitable substituents for building a virtual library (VL) of AAD analogues representing a chemical subspace of 79,500 compounds to be PH4-screened in search of more potent inhibitors; the best predicted Kipre of them reached 40 pM. Finally, the good stability of the AtHPPD-AADx complex and the flexibility of the active conformation of the inhibitor for selected top-ranked AAD analogues were checked with the help of molecular dynamics (MD, 200 ns runs). This computational study proposed a set of new predicted potent inhibitors with herbicidal effects.

Basing target enzyme study the enantioselective bioactivity action mechanism of flusulfinam, a novel HPPD inhibitor herbicide

Flusulfinam is a novel chiral amide herbicide widely used for controlling annual weeds in rice paddies. However, the mechanism underlying their enantioselective herbicidal activity remain unclear. Herein, it was found that flusulfinam enantiomers, similar to typical HPPD inhibitor mesotrione, reduced chlorophyll and carotenoid levels, decreased HPPD enzyme activity, and upregulated gene expression. Additionally, homogentisate supplementation alleviated the bleaching symptoms caused by flusulfinam and all these results validate that flusulfinam is indeed an HPPD inhibitor. To further investigate the mechanism of enantioselectivity, molecular docking was used and showed that R-flusulfinam (-6.55 kcal/mol) had higher binding energy than S-flusulfinam (-5.60 kcal/mol), due to more stable hydrogen bonds with Gln293. After mutating Gln293 to His, the IC50 values for R-flusulfinam and S-flusulfinam on MutQ293H were 0.73 mg/L and 0.11 mg/L, respectively, indicating swapped enantioselective inhibition compared to AtHPPD, with IC50 values of 0.52 mg/L and 1.93 mg/L, respectively. The Microscale Thermophoresis assay further revealed that the dissociation constant (Kd) for MutQ293H with R-flusulfinam was 20.40 ± 4.19 μM, similar to the Kd value of 15.63 ± 4.51 μM for S-flusulfinam. The findings reveal that mutation of the Gln293 residue in the AtHPPD enzyme significantly altered its enantioselective inhibition by flusulfinam. This study is the first to verify the mode of action of flusulfinam and identifies that Gln293 may play a key role in flusulfinam enantioselectivity in the AtHPPD, laying the foundation for future HPPD inhibitor development based on flusulfinam.

The database makes the poison: How the selection of datasets in QSAR models impacts toxicant prediction of higher tier endpoints

As the United States and the European Union continue their steady march towards the acceptance of new approach methodologies (NAMs), we need to ensure that the available tools are fit for purpose. Critics will be well-positioned to caution against NAMs acceptance and adoption if the tools turn out to be inadequate. In this paper, we focus on Quantitative Structure Activity-Relationship (QSAR) models and highlight how the training database affects quality and performance of these models. Our analysis goes to the point of asking, "are the endpoints extracted from the experimental studies in the database trustworthy, or are they false negatives/positives themselves?" We also discuss the impacts of chemistry on QSAR models, including issues with 2-D structure analyses when dealing with isomers, metabolism, and toxicokinetics. We close our analysis with a discussion of challenges associated with translational toxicology, specifically the lack of adverse outcome pathways/adverse outcome pathway networks (AOPs/AOPNs) for many higher tier endpoints. We recognize that it takes a collaborate effort to build better and higher quality QSAR models especially for higher tier toxicological endpoints. Hence, it is critical to bring toxicologists, statisticians, and machine learning specialists together to discuss and solve these challenges to get relevant predictions.

Fluorinated benzoxazinones designed via MIA-QSAR, docking and molecular dynamics as protoporphyrinogen IX oxidase inhibitors

BACKGROUND

Fluorine plays a significant role in agrochemical science because approximately 25% of herbicides licensed worldwide contain this element. In a pool of previously synthesized benzoxazinones, some compounds contained fluorine and demonstrated inhibitory activities against protoporphyrinogen IX oxidase (PPO). Therefore, three data sets of benzoxazinone derivatives with known inhibitory activity against PPO were employed to build a multivariate image analysis applied to a quantitative structure-activity relationships (MIA-QSAR) model to identify improved analogs with at least one fluorine substituent.

RESULTS

The QSAR model was vigorously validated and demonstrated to be highly predictive (r2 = 0.85, q2 = 0.71, and r2 pred = 0.88); thus, the model can provide reliable estimations for the PPO inhibitory activity of unknown derivatives. From these compounds, a couple of N-substituted benzoxazinones that contained the -CH2CHF2 group were found with predicted pKi values larger than 8 (Ki in mol L-1) and higher lipophilicity than the most active data set compounds. In addition, we carried out a systematic investigation of the binding mode of PPO by performing computational docking followed by molecular dynamics simulations. The proposed binding mode was consistent with experimental studies, and several potential key residues were identified.

CONCLUSION

Two new proposed benzoxazinones exhibited better performance than compounds of the data set, and fluorine substituents played pivotal roles in describing the biological activities. © 2024 Society of Chemical Industry.

Discovery of Bis-5-cyclopropylisoxazole-4-carboxamides as Novel Potential 4-Hydroxyphenylpyruvate Dioxygenase Inhibitors

4-Hydroxyphenylpyruvate dioxygenase (EC 1.13.11.27; HPPD) represents a potential target for novel herbicide development. To discover the more promising HPPD inhibitor, we designed and synthesized a series of bis-5-cyclopropylisoxazole-4-carboxamides with different linkers using a multitarget pesticide design strategy. Among them, compounds b9 and b10 displayed excellent herbicidal activities versus Digitaria sanguinalis (DS) and Amaranthus retroflexus (AR) with the inhibition of about 90% at the concentration of 100 mg/L in vitro, which was better than that of isoxaflutole (IFT). Furthermore, compounds b9 and b10 displayed the best inhibitory effect versus DS and AR with the inhibition of about 90 and 85% at 90 g (ai)/ha in the greenhouse, respectively. The structure-activity relationship study showed that the flexible linker (6 carbon atoms) is responsible for increasing their herbicidal activity. The molecular docking analyses showed that compounds b9 and b10 could more closely bind to the active site of HPPD and thus exhibited a better inhibitory effect. Altogether, these results indicated that compounds b9 and b10 could be used as potential herbicide candidates targeting HPPD.

Discovery of Novel Pyrazole Derivatives with Improved Crop Safety as 4-Hydroxyphenylpyruvate Dioxygenase-Targeted Herbicides

As one of the essential herbicide targets, 4-hydroxyphenylpyruvate dioxygenase (HPPD) has recently been typically used to produce potent new herbicides. In continuation with the previous work, several pyrazole derivatives comprising a benzoyl scaffold were designed and synthesized, and their inhibitory effects on Arabidopsis thaliana hydroxyphenylpyruvate dioxygenase (AtHPPD) and herbicidal activities were comprehensively evaluated in this study. Compound Z9 showed top-rank inhibitory activity to AtHPPD with an half-maximal inhibitory concentration (IC₅₀) value of 0.05 μM, which was superior to topramezone (1.33 μM) and mesotrione (1.76 μM). Compound Z21 exhibited superior preemergence inhibitory activity against Echinochloa crusgalli, with stem and root inhibition rates of 44.3 and 69.6%, respectively, compared to topramezone (16.0 and 53.0%) and mesotrione (12.8 and 41.7%). Compounds Z5, Z15, Z20, and Z21 showed excellent postemergence herbicidal activities at a dosage of 150 g ai/ha, along with distinct bleaching symptoms and higher crop safety than topramezone and mesotrione, and they all were safe for maize, cotton, and wheat with injury rates of 0 or 10%. In addition, the molecular docking analysis also revealed that these compounds formed hydrophobic π-π interactions with Phe360 and Phe403 to AtHPPD. This study suggests that pyrazole derivatives containing a benzoyl scaffold could be used as new HPPD inhibitors to develop pre- and postemergence herbicides and be applied to additional crop fields.

Study of two combined series of triketones with HPPD inhibitory activity by molecular modelling

Triketones are suitable compounds for 4-hydroxyphenylpyruvate dioxygenase (HPPD) inhibition and are important compounds for eliminating agricultural weeds. We report herein quantitative structure-activity relationship (QSAR) modelling and docking studies for a series of triketone-quinoline hybrids and 2-(aryloxyacetyl)cyclohexane-1,3-diones with the aim of proposing new chemical candidates that exhibit improved performance as herbicides. The QSAR models obtained were reliable and predictive (average r², q², and r²_pred of 0.72, 0.51, and 0.71, respectively). Guided by multivariate image analysis of the PLS regression coefficients and variable importance in projection scores, the substituent effects could be analysed, and a promising derivative with R¹ = H, R² = CN, and R³ = 5,7,8-triCl at the triketone-quinoline scaffold (P18) was proposed. Docking studies demonstrated that π-π stacking interactions and specific interactions between the substituents and amino acid residues in the binding site of the Arabidopsis thaliana HPPD (AtHPPD) enzyme support the desired bioactivity. In addition, compared to a benchmark commercial triketone (mesotrione), the proposed compounds are more lipophilic and less mobile in soil rich in organic matter and are less prone to contaminate groundwater.