EAGER: Modeling Protein Degradation - Evaluation of Strategies and Targets

EAGER：蛋白质降解建模 - 策略和目标评估

• 批准号: 1355462
• 负责人: Christine Vogel
• 金额: $ 30万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-11-15 至 2016-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1355462&HistoricalAwards=false
• 关键词: EAGER; Modeling; Protein; Degradation; Evaluation

The ability to manipulate the concentration of individual proteins in a cell is limited, for example, by the lack of knowledge of the factors that regulate protein stability. In this project the response of yeast cells to oxidative stress will be used to develop predictive models of protein degradation based on protein sequence and structure. The approach will employ mass spectrometry and bioinformatics to combine proteomic data (including protein ubiquitination status and degradation) with information on protein sequence and structure to learn features that impact protein stability. Predictions will be validated in targeted experiments. Broader Impacts: Interdisciplinary training will be provided to graduate students and postdoctoral fellows, and engagement with high-school students will be achieved through participation in the American Museum of Natural History's LANG program.

例如，由于缺乏对调节蛋白质稳定性的因素的了解，操纵细胞中单个蛋白质浓度的能力受到限制。在这个项目中，酵母细胞对氧化应激的反应将被用于开发基于蛋白质序列和结构的蛋白质降解预测模型。该方法将利用质谱和生物信息学将联合收割机蛋白质组数据（包括蛋白质泛素化状态和降解）与蛋白质序列和结构信息结合起来，以了解影响蛋白质稳定性的特征。预测将在有针对性的实验中得到验证。更广泛的影响：将为研究生和博士后研究员提供跨学科培训，并通过参与美国自然历史博物馆的LANG计划实现与高中生的接触。