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A Computational Platform for In-Situ Structure Determination at Near-Atomic Resolution using Cryo-Electron Tomography

A Computational Platform for In-Situ Structure Determination at Near-Atomic Resolution using Cryo-Electron Tomography
使用冷冻电子断层扫描以近原子分辨率原位结构测定的计算平台
批准号:
10581369
负责人:
Alberto Bartesaghi
金额:
$21.0万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-09-01 至 2025-05-31

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英文摘要
PROJECT SUMMARY Understanding how proteins interact within the cell to perform specific functions is a major goal of modern biology and vital for understanding the diverse roles these molecules play in biomedicine. Cryo-electron tomography (cryo-ET) combined with sub-volume averaging (SVA) is currently the only imaging technology that allows visualizing macromolecules within their unperturbed native environment at nanometer resolutions. Most successful studies, however, have been of large complexes or ordered assemblies and at resolutions that are too low to reveal molecular level interactions. The overall objective of this Technology Development project is to design computational tools to improve the resolution of cryo-ET/SVA and extend its applicability to a wider class of biomedically relevant targets. The specific aims are: (1) we will develop strategies to improve the accuracy of the tilted contrast transfer function (CTF) determination from low-dose tomographic tilt-series, (2) we will design algorithms to improve the accuracy of image alignment, reconstruction and classification aimed at reducing the computational B-factors associated with data processing, and (3) we will extend the applicability of cryo-ET/SVA to a broader class of targets including low molecular weight proteins that are currently considered below the technological capabilities of the technique. As proof of principle, we will demonstrate that our methods improve the state-of-the-art in terms of achievable resolution and can be used to determine the structure of a small 300kDa enzyme at near-atomic resolution, representing a significant milestone for the field. Our research is innovative because it seeks to overcome fundamental technical challenges in cryo-ET needed to realize the full potential of this emerging imaging technology. The proposal is significant because it demonstrates that challenging targets can be visualized al high-resolution using cryo-ET, indicating that this technique is the most promising route for studying important biomolecules in-situ. Ultimately, by closing the resolution gap between strategies for studying samples in-vitro and techniques to study proteins in their native cellular environment, our methods will allow the visualization of proteins in their functional state at an unprecedented level of detail.
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A Computational Platform for In-Situ Structure Determination at Near-Atomic Resolution using Cryo-Electron Tomography
  • 批准号:
    10466802
  • 项目类别:
  • 资助金额:
    $31.82万
  • 财政年份:
    2021
  • 负责人:
    Alberto Bartesaghi
  • 依托单位:
A Computational Platform for In-Situ Structure Determination at Near-Atomic Resolution using Cryo-Electron Tomography
  • 批准号:
    10624852
  • 项目类别:
  • 资助金额:
    $31.74万
  • 财政年份:
    2021
  • 负责人:
    Alberto Bartesaghi
  • 依托单位:
A Computational Platform for In-Situ Structure Determination at Near-Atomic Resolution using Cryo-Electron Tomography
  • 批准号:
    10183362
  • 项目类别:
  • 资助金额:
    $31.89万
  • 财政年份:
    2021
  • 负责人:
    Alberto Bartesaghi
  • 依托单位:
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