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DESCRIPTION (provided by applicant): Macromolecular assemblies are involved in nearly every process in the cell, from motility to signaling. Typically, such assemblies are composed of a variety of protein and organized into intricate machines that undergo dynamic and transient shifts in their organization and composition. As such, understanding macromolecular assemblies is paramount for increasing our knowledge about basic cellular events and discovering targets for disease prevention. While electron cryo-microscopy (cryo-EM) is capable of imaging these large and often difficult to study assemblies, limitations currently hinder the ability to atomic resolutions, at which point these structures can reveal the intricate sets of interactions and cordination of complex chemistry. State-of-the-art cryo-EM imaging has recently achieved near-atomic resolutions (3.5-5¿), such that basic models for all or parts of an entire macromolecular assembly could be constructed. These "first- approach" models describe the organization and basic fold of the protein constituents, but fall short of describing the necessary atomic-level detail features of macromolecular assemblies that is critical for designing effective measures for disease prevention and improving human health. Motivated by the need for new tools to push towards atomic resolution structures in cryo-EM, we propose developing a comprehensive macromolecular refinement and modeling protocol. Our ultimate goal is to provide the community with a new technique to push near-atomic resolution structures to atomic resolutions such that full atomic models can be built directly from a density map. To accomplish this goal, we will develop a novel automated method for generating simple structural models that, in turn can be used to refine and improve resolution in a cryo-EM density map. From this, it will not only be possible to construct fill atomic models, but also to model the structural dynamics captured by cryo-EM imaging. We believe this work will revolutionize the field of cryo-EM, as well as lead to significant leaps in our understanding of all biological processes.
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Atomic Resolution Cryo-EM using Model-Based Constraints
  • 批准号:
    8443939
  • 项目类别:
  • 资助金额:
    $23.48万
  • 财政年份:
    2013
  • 负责人:
    Matthew Lowell Baker
  • 依托单位:
海外基金