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Updated: Sep 13, 2025

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整合氧化蛋白学和计算建模来解读植物应激生理学中的基于硫醇的氧化后翻译性修饰 (oxiPTMs)
Cengiz Kaya1, Francisco J Corpas2
1Soil Science and Plant Nutrition Department, Harran University, Sanliurfa 63200, Turkey.
International journal of molecular sciences
|July 29, 2025
概括
植物的氧化还原信号使用醇修饰来控制适应和应激反应. 将质谱与人工智能工具相结合,可以提高对这些过程的理解,从而提高作物弹性.
科学领域:
- 植物生物学 植物生物学
- 生物化学 生物化学
- 系统生物学 系统生物学
背景情况:
- 反氧信号调节植物的适应,新陈代谢和应激反应,通过基于醇的氧化后翻译性修饰 (oxiPTMs).
- 氨酸 (Cys) 残留物修饰作为分子开关,改变蛋白质功能和相互作用.
研究的目的:
- 综合氧化还原蛋白质学和研究植物氧化还原信号的计算工具的方法进步.
- 探索实验和人工智能驱动方法的整合,以了解氧化还原依赖网络.
主要方法:
- 基于质谱的氧化还原蛋白质组学用于识别和量化oxiPTMs.
- 计算建模,人工智能和机器学习用于预测氧化还原敏感残留物和网络.
- 对缩策略,量化技术和实时氧化还原传感的审查.
主要成果:
- 氧化还原蛋白质组学的进步使人们能够更好地理解氧化还原动力学.
- 计算工具可以预测各种oxiPTM,如S-化,硫化,S-甲化,化和二硫化键的形成.
- 主要的模型包括CysQuant,BiGRUD-SA,DLF-Sul和植物PTM查看器.
结论:
- 实验性蛋白质组学和人工智能平台的整合为氧化还原系统生物学提供了未来的潜力.
- 验证计算预测对于提高作物弹性,代谢效率和在气候变化条件下精准农业至关重要.
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