Reliable model building for cryo-EM

可靠的冷冻电镜模型构建

• 批准号: 10612108
• 负责人: Raquel Bromberg
• 金额: $ 85.43万
• 依托单位: LIGO ANALYTICS, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10612108
• 关键词: 3-Dimensional; Address; Architecture; Articular Range of Motion; Cell physiology; Classification; Complex; Computer software; Coupling; Cryoelectron Microscopy; Data Analyses; Data Set; Development; Disease; Drug Design; Excision; Experimental Models; Feedback; Freedom; Grouping; Health; Ice; Image; Individual; Maps; Methods; Modeling; Molecular; Motion; Noise; Phase; Procedures; Process; Proteins; Resolution; Running; Sampling; Signal Transduction; Small Business Innovation Research Grant; Structural Models; Structure; Thinness; Translations; Validation; Weight; Work; design; flexibility; guided inquiry; improved; insight; macromolecule; model building; molecular modeling; novel; novel strategies; particle; predictive modeling; rational design; reconstruction; restraint; structural biology

Project Abstract Atomic models generated by experimental structural biology are used to understand cellular processes at the molecular level, and also for rational design of drugs and treatments. Cryogenic electron microscopy single particle reconstruction (cryo-EM SPR) generates such atomic models based on interpretation of maps of Coulomb potential that are obtained by averaging many thousands of weak images, with each image containing projection snapshots of individual macromolecules suspended in a thin layer of ice. Consequently, cryo-EM maps represent averages of structural states and frequently have limited and uneven quality resulting from both flexibility of particles used in cryo-EM SPR as well as their non-random distributions in ice called preferred orientation. Building and rebuilding structural models in maps that are low quality due to lack of detail (resolution) or having sampling and reconstruction problems is a challenge. In this proposal, we will address these challenges by developing and implementing methods for automatic and comprehensive model building and validation with carefully designed feedback loops to experimental data analysis. The initial and intermediate models generated by our model building methods will aid cryo-EM SPR projects by stabilizing convergence of computations at all steps of reconstruction, but without introducing bias, with bias removal and quantification being addressed explicitly. Aim 1 will focus on methods that will use ab initio predicted models or experimental models to improve cryo-EM SPR so that they can be used without introducing bias. In Aim 2, a new weighting of information for refinement and validation of the structural models will be developed and implemented to account for uneven quality of information in cryo-EM SPR. Aim 3 will focus on developing and implementing methods for directly coupling 2D classification to model building. Finally, Aim 4 will target analysis and modeling of internal motions to guide the structural interpretation and to improve the resolution of reconstructions. The results will be incorporated into the commercially distributed suite cryoEMMA. The competitive advantage of these approaches arises from their ability to provide highly informative 3D reconstructions in the presence of severe preferred orientation and for single particle signal-to-noise lower than in the current approaches.

项目摘要

项目成果

CryoEM single particle reconstruction with a complex-valued particle stack.

• DOI: 10.1016/j.jsb.2023.107945
• 发表时间: 2023-06
• 期刊: JOURNAL OF STRUCTURAL BIOLOGY
• 影响因子: 3
• 作者: Bromberg, Raquel;Guo, Yirui;Borek, Dominika;Otwinowski, Zbyszek
• 通讯作者: Otwinowski, Zbyszek