Identification of 4‐hydroxyphenylpyruvate dioxygenase inhibitors by virtual screening, molecular docking, molecular dynamic simulation

Abstract

BACKGROUND 4‐Hydroxyphenylpyruvate dioxygenase (HPPD) herbicides control broadleaf and gramineous weeds with better crop safety for corn, sorghum and wheat. Multiple screening models in silico have been established to obtain novel lead compounds as HPPD inhibition herbicides. RESULTS Topomer comparative molecular field analysis (CoMFA) combined with topomer search technology and Bayesian, genetic approximation functions (GFA) and multiple linear regression (MLR) models generated by calculating different descriptors were constructed for the quinazolindione derivatives of HPPD inhibitors. The coefficient of determination (r2) of topomer CoMFA, MLR and GFA were 0.975, 0.970 and 0.968, respectively; all the models established displayed excellent accuracy and high predictive capacity. Five compounds with potential HPPD inhibition were obtained via screening fragment library combined with the validation of the above models and molecular docking studies. After molecular dynamics (MD) validation and absorption, distribution, metabolism, excretion and toxicity (ADMET) prediction, the compound 2‐(2‐amino‐4‐(4H‐1,2,4‐triazol‐4‐yl) benzoyl)‐3‐hydroxycyclohex‐2‐en‐1‐one not only exhibited stable interactions with the protein but also high solubility and low toxicity, and has potential as a novel HPPD inhibition herbicide. CONCLUSION In this study, five compounds were obtained through multiple quantitative structure–activity relationship screening. Molecular docking and MD experiments showed that the constructed approach had good screening ability for HPPD inhibitors. This work provided molecular structural information for developing novel, highly efficient and low‐toxicity HPPD inhibitors. © 2023 Society of Chemical Industry.

4-Hydroxyphenylpyruvate Dioxygenase Inhibitors: From Molecular Design to Synthesis

“…47 Shi et al established topomer CoMFA models, along with Bayesian, GFA, and MLR models utilizing a consistent set of 36 HPPD inhibitors. 48 The application of a cross-validated approach involving multiple QSAR models significantly enhanced predictive precision, in contrast to singular models. Eventually, five compounds with favorable predictive values were recognized as potential new HPPD inhibitors (SI, Scheme S6).…”

Identification Novel Salty-Enhancing Peptides from Sea Cucumber Collagen: AlphaFold2 Modeling and Molecular Simulation

“…Subsequently, the 3D structure of the synthesized TMC4 receptor protein was imported into DS 2017 following small molecule ligand structure processing. The residual sequence of the protein crystal and ligand group was excluded during the "Prepare Protein" processing, and the selection of the docking site for the processed receptor protein was performed using the CHARMm force eld (Shi et al, 2023). CDOCKER was used to dock the small molecule peptides to the identi ed active pockets on the TMC4 receptor protein, respectively.…”

Integrated Virtual Screening and Validation toward Potential HPPD Inhibition Herbicide

“…Computer-aided drug design/discovery (CADD) has become a crucial part of drug development, and the combination of pharmacophore model screening and molecular docking has been widely adopted. − Pharmacophore models are commonly generated based on a series of ligand characteristics, receptor structure, and CBP, which have been extensively applied alone or in combination in the discovery of HPPD inhibitors. − Subsequently, molecular docking was carried out to validate the specific binding patterns between the ligands and HPPD, as well as ensure a relatively high binding energy. ,− However, a drawback in the molecular docking process still exists, in which it is hard to distinguish the optimal conformation. − A novel consensus docking approach has been reported recently in the discovery of HPPD inhibitors, which compensated for this shortcoming and improved the accuracy and reliability of the docking process …”