New methods to capture protein dynamics of the TSC-mTOR signalling axis.

捕获 TSC-mTOR 信号轴蛋白质动态的新方法。

• 批准号: DE240100992
• 负责人: Dr Charles Bayly-Jones
• 金额: $ 31.06万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2024
• 资助国家: 澳大利亚
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE240100992
• 关键词: New; methods; capture; protein; dynamics

Protein flexibility, the way proteins move, has a major role in how they function. However, we still do not have the tools to analyse this flexibility. Our cells have evolved many complex and flexible systems to sense and respond to their environment. For example, the TSC-mTOR system is found across life, from baker’s yeast to humans, however it remains poorly understood. This proposal will study TSC as an exemplar to develop novel machine-learning approaches to capture protein flexibility and shape. This proposal will advance fundamental understanding of the TSC-mTOR pathway and build transformative methodologies to study flexible proteins more broadly.

蛋白质的灵活性，即蛋白质运动的方式，在它们的功能中起着重要作用。然而，我们仍然没有工具来分析这种灵活性。我们的细胞已经进化出许多复杂而灵活的系统来感知和响应环境。例如，TSC-mTOR系统存在于从面包酵母到人类的所有生命中，但对它的了解仍然很少。该提案将研究TSC作为开发新的机器学习方法来捕获蛋白质灵活性和形状的范例。该建议将促进对TSC-mTOR途径的基本理解，并建立更广泛地研究柔性蛋白的变革性方法。