Analysis tools for quantifying protein conformational landscapes using DEER spectroscopy

使用 DEER 光谱定量蛋白质构象景观的分析工具

• 批准号: 10360468
• 负责人: Stefan Stoll
• 金额: $ 31.32万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-01 至 2023-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10360468
• 关键词: Address; Bayesian Analysis; Behavior; Biomedical Research; Computer Analysis; Computer Models; Cryoelectron Microscopy; Crystallography; Data; Data Analyses; Data Set; Deer; Disease; Electrons; Environment; Goals; Human; Human body; Kinetics; Label; Life; Ligands; Markov Chains; Measures; Membrane Proteins; Methodology; Methods; Modeling; Molecular; Molecular Conformation; Motion; Noise; Outcome; Process; Protein Conformation; Proteins; Reproducibility; Research Personnel; Resolution; Science; Series; Side; Site; Software Tools; Spectrum Analysis; Spin Labels; Statistical Data Interpretation; Structural Models; Structure; System; Techniques; Temperature; Tertiary Protein Structure; Testing; Time; Titrations; Uncertainty; Visualization; Work; X-Ray Crystallography; base; conformational conversion; drug development; experimental analysis; flexibility; improved; innovation; insight; knowledge base; nanoscale; novel; novel therapeutics; open source; prevent; protein complex; protein distribution; protein structure; protein structure function; technology research and development; tool

PROJECT SUMMARY/ABSTRACT This project develops new computational analysis and modeling methods for DEER (double electron- electron resonance) spectroscopy. DEER is a biostructural technique for the quantification of protein conformational landscapes and protein motions on the nanometer scale. Protein motions are crucial for many key molecular processes at the basis of human life and disease. Therefore, DEER provides important insights that contribute to the knowledge base necessary for drug development. In combination with X-ray crystallography, NMR and cryo-EM, DEER is part of a complementary set of integrative experimental biostructural tools. It is especially important for the study of membrane proteins. A major barrier in the field is the lack of integrated analysis tools for biomedical researchers. This project addresses this issue by (a) developing methods and tools based on Bayesian statistics for the rigorous and reproducible analysis of experimental DEER data, providing comprehensive methods for uncertainty quantification (error bars) in DEER data, and (b) creating advanced computational approaches that utilize DEER data in the refinement of protein structures based on atomic-resolution ensemble models. Overall, the goal of the project is to significantly accelerate the workflow of DEER data analysis, interpretation, and modeling and to increase its rigor, reproducibility and accessibility. This will enable the study of the structure and dynamics of larger and more complex proteins and protein assemblies, which are increasingly important in biomedical research.

项目总结/摘要 该项目开发了DEER（双电子- 电子共振）光谱学。DEER是一种用于蛋白质定量的生物结构技术 纳米尺度上的构象景观和蛋白质运动。蛋白质运动对于 许多关键的分子过程是人类生命和疾病的基础。因此，DEER提供 重要的见解，有助于药物开发所需的知识基础。组合 与X射线晶体学，NMR和cryo-EM，DEER是一个互补的一套综合的一部分， 实验生物结构工具。这对膜蛋白的研究尤为重要。一个主要 该领域的一个障碍是缺乏生物医学研究人员的综合分析工具。这个项目 解决这一问题的办法是：（a）开发基于贝叶斯统计的方法和工具， 实验DEER数据的可重复性分析，为不确定性提供全面的方法 DEER数据中的量化（误差条），以及（B）创建利用 DEER数据在基于原子分辨率系综模型的蛋白质结构精化中的应用。总的来说， 该项目的目标是大大加快DEER数据分析，解释， 和建模，并增加其严谨性，可重复性和可访问性。这将有助于研究 更大更复杂的蛋白质和蛋白质组装体的结构和动力学， 在生物医学研究中越来越重要。