RAPID: IIBR Informatics: Predicting All-atom Structure of SARS-CoV-2 Related Protein Complex from 3D Cryo-Electron Microscopy Data

RAPID：IIBR 信息学：根据 3D 冷冻电子显微镜数据预测 SARS-CoV-2 相关蛋白复合物的全原子结构

• 批准号: 2030381
• 负责人: Dong Si
• 金额: $ 20万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-15 至 2022-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2030381&HistoricalAwards=false
• 关键词: RAPID; IIBR; Informatics; Predicting; atom

The outbreak of novel coronavirus disease (COVID-19) has caused a global pandemic. Knowledge on the molecular basis of novel coronavirus (SARS-CoV-2) related protein complexes is essential to providing insight of the virus and how it infects human cells, a first step in developing novel drugs and vaccines to combat SARS-CoV-2. This study will enable development of all-atom structure prediction of CoV-related protein complexes, including complex surfaces of human cells the virus infects. Prediction results will be broadly and quickly disseminated through interactive web applications to maximize the impact of the research. The results will lead to a broad range of biomedical applications, such as a better understanding of important biological functions, disease processes, development of novel drugs and vaccines, and improved preventive therapies leading to reduced health care costs. The project seeks to study ab initio all-atom structure prediction of CoV-related protein complexes based on electron cryo-microscopy (cryo-EM). Methods based on the state-of-the-art technologies of image processing for pre-processing the data, deep learning for complex structure prediction, and dynamic optimization for final refinement to reveal fundamental mechanisms of CoV-related macromolecules will be developed. The project will also provide an open-source and interactive web portal for public access of the developed tools. The work could have immediate impact on steps taken to halt the spread of SARS-CoV-2 and the current pandemic. Training opportunities for students at all levels, particularly women and underrepresented minorities will also be carried out. The results of the project can be found at: http://faculty.washington.edu/dongsi.This RAPID award is made by the Infrastructure Innovation for Biological Research (IIBR Informatics) Program in the Division of Biological Infrastructure, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

新型冠状病毒病（COVID-19）爆发已导致全球大流行。了解新型冠状病毒（SARS-CoV-2）相关蛋白复合物的分子基础对于了解病毒及其如何感染人类细胞至关重要，这是开发新型药物和疫苗以对抗SARS-CoV-2的第一步。这项研究将有助于开发CoV相关蛋白质复合物的全原子结构预测，包括病毒感染的人类细胞的复杂表面。预测结果将通过交互式网络应用程序广泛而迅速地传播，以最大限度地扩大研究的影响。这些结果将导致广泛的生物医学应用，例如更好地了解重要的生物功能，疾病过程，开发新药和疫苗，以及改善预防性治疗，从而降低医疗保健成本。该项目旨在研究基于电子冷冻显微镜（cryo-EM）的CoV相关蛋白质复合物的从头算全原子结构预测。将开发基于最先进的图像处理技术的方法来预处理数据，深度学习用于复杂结构预测，动态优化用于最终细化，以揭示CoV相关大分子的基本机制。该项目还将提供一个开放源码和互动式门户网站，供公众使用所开发的工具。这项工作可能会对阻止SARS-CoV-2和当前流行病传播的措施产生直接影响。还将为各级学生，特别是妇女和代表性不足的少数民族提供培训机会。该项目的结果可以在以下网站找到：http://faculty.washington.edu/dongsi.This RAPID奖由生物基础设施部的生物研究基础设施创新（IIBR信息学）计划颁发，使用冠状病毒援助，救济和经济安全（CARES）法案的资金。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。