Scholarlink

<p>Herbicide-based weed management is vital for modern agriculture, enhancing crop productivity while reducing labor costs. Among herbicides, 4-hydroxyphenylpyruvate dioxygenase (HPPD) inhibitors have emerged as a key class due to their broad-spectrum efficacy, high selectivity, and low toxicity. However, increasing resistance to HPPD inhibitors underscores the need for new herbicide candidates, with crop safety being a critical consideration in these development efforts. In this study, homology modeling was employed to predict the three-dimensional structures of HPPD enzymes from sorghum (<i>Sorghum bicolor</i>), soybean (<i>Glycine soja</i>), and cotton (<i>Gossypium barbadense</i>), using maize and <i>Arabidopsis thaliana</i> as reference species. The models were evaluated for structural integrity using root mean square deviation (RMSD) analysis, energy parameters, Ramachandran plots, and additional statistical validations. Molecular docking of mesotrione, a widely used HPPD inhibitor, was conducted to analyze its interaction with the modeled enzyme structures. Docking results identified key conserved residues, such as histidine and phenylalanine, which are critical for Fe(II) coordination and π-π interactions. Among the models, sorghum and soybean demonstrated high structural stability and minimal violations, whereas the cotton model showed the lowest binding energy. These findings enhance our understanding of crop safety and herbicide efficacy, providing valuable insights for the design of next-generation herbicides and the management of herbicide resistance.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Three-Dimensional Structure Prediction of HPPD Enzyme in Agricultural Crops Using Homology Modeling

  • 期刊论文

  • 发表日期：

    2025年5月7日

查看全文
  • Luiz dos Reis Capucho,
  • Elaine F. F. da Cunha,
  • Matheus P. Freitas

摘要

Herbicide-based weed management is vital for modern agriculture, enhancing crop productivity while reducing labor costs. Among herbicides, 4-hydroxyphenylpyruvate dioxygenase (HPPD) inhibitors have emerged as a key class due to their broad-spectrum efficacy, high selectivity, and low toxicity. However, increasing resistance to HPPD inhibitors underscores the need for new herbicide candidates, with crop safety being a critical consideration in these development efforts. In this study, homology modeling was employed to predict the three-dimensional structures of HPPD enzymes from sorghum (Sorghum bicolor), soybean (Glycine soja), and cotton (Gossypium barbadense), using maize and Arabidopsis thaliana as reference species. The models were evaluated for structural integrity using root mean square deviation (RMSD) analysis, energy parameters, Ramachandran plots, and additional statistical validations. Molecular docking of mesotrione, a widely used HPPD inhibitor, was conducted to analyze its interaction with the modeled enzyme structures. Docking results identified key conserved residues, such as histidine and phenylalanine, which are critical for Fe(II) coordination and π-π interactions. Among the models, sorghum and soybean demonstrated high structural stability and minimal violations, whereas the cotton model showed the lowest binding energy. These findings enhance our understanding of crop safety and herbicide efficacy, providing valuable insights for the design of next-generation herbicides and the management of herbicide resistance.