Automated de novo building of protein models into electron microscopy maps

自动将蛋白质模型从头构建到电子显微镜图谱中

基本信息

批准号：
BB/P000517/1
负责人：
Kevin Cowtan
金额：
$ 33.11万
依托单位：
University of York
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FP000517%2F1
关键词：
Automated de novo building protein

项目摘要

Scientists are interested in the atomic structure of biological molecules, in other words what the molecules look like. Knowing in detail what a molecule looks like provides important clues to how it might work. If we can go further and capture molecules in the process of interacting with other biological molecules, or artificial compounds such as drugs, we get a clearer picture of how they work.Most of our knowledge of the structure of biological molecules comes from X-ray crystallography. However over the past decade a new technique, electron microscopy (EM) has become popular. Individual molecules held in a thin film of liquid solvent are frozen and placed in an electron microscope, which captures images of the molecules. Many individual views can be combined to construct a model of the structure of the molecule in 3 dimensions.Until recently these images were of limited resolution - they were 'fuzzy' - and so individual groups of atoms could not be seen. The EM user therefore needed to have some knowledge of the structure of the molecule, or at least parts of it, in advance. These fragments can then be fitted into the EM image to give an indication of the whole structure, and allowed large molecular machines such as the Ribosome to be understood.New electron detectors have allowed EM images to be determined at much higher resolutions, so that small groups of atoms can be distinguished. The resulting images are of similar quality to those from X-ray crystallography. This has allowed the atomic structure of the molecule to be determined without any prior knowledge of the structure in favourable cases. However at the moment the process of interpreting the map in terms of atomic features is often performed manually, at a cost of considerable effort and a potential lack of objectivity in the results.The aim of this project is to take an existing method for automatically building atomic models into images from X-ray crystallography, and modify the software to work effectively with the images from electron microscopy. Not only will this make the process of building an atomic model into an electron microscopy image much less time consuming, it will allow multiple models to be built into different images of the molecule as an assessment of the accuracy and reliability of the results. It will be possible to go back and check existing structures by rebuilding the maps automatically. This will provide a useful check on the quality of existing models determined from EM images.The project involves modifying existing computer software for building atomic models to adapt it to work on a new type of image. The software is already good at interpreting crystallographic images at the kind of resolutions produced by electron microscopy experiments, but works less well with EM images because it has been "trained" to work with crystallography images. Some retraining, and possibly some new methods, will be required.All of the software produced by the project will be distributed freely to academic users through existing software suites for crystallography and electron microscopy. The source code for software will also be distributed so that other developers can learn from it or modify it.

科学家对生物分子的原子结构感兴趣，换句话说，分子的样子。详细了解分子的外观可以为了解其如何发挥作用提供重要线索。如果我们能更进一步，捕获分子与其他生物分子或药物等人工化合物相互作用的过程，我们就能更清楚地了解它们的工作原理。我们对生物分子结构的大部分了解都来自X射线晶体学。然而，在过去的十年中，一种新技术——电子显微镜（EM）变得流行起来。保存在液体溶剂薄膜中的单个分子被冷冻并放置在电子显微镜中，电子显微镜捕获分子的图像。许多单独的视图可以组合起来构建 3 维分子结构的模型。直到最近，这些图像的分辨率有限 - 它们是“模糊的” - 因此无法看到单个原子组。因此，EM 用户需要提前了解分子结构或至少部分结构的知识。然后可以将这些碎片装入 EM 图像中，以指示整个结构，并允许理解核糖体等大型分子机器。新的电子探测器允许以更高的分辨率确定 EM 图像，因此小可以区分原子团。生成的图像与 X 射线晶体学图像的质量相似。这使得在有利的情况下无需事先了解结构即可确定分子的原子结构。然而，目前根据原子特征解释地图的过程通常是手动执行的，需要付出相当大的努力，并且结果可能缺乏客观性。该项目的目的是采用现有的方法来自动构建将原子模型转化为 X 射线晶体学图像，并修改软件以有效地处理电子显微镜图像。这不仅使得将原子模型构建到电子显微镜图像中的过程更加耗时，而且还允许将多个模型构建到分子的不同图像中，以评估结果的准确性和可靠性。通过自动重建地图，可以返回并检查现有结构。这将为根据 EM 图像确定的现有模型的质量提供有用的检查。该项目涉及修改用于构建原子模型的现有计算机软件，以使其适应新型图像。该软件已经能够很好地以电子显微镜实验产生的分辨率解释晶体学图像，但对于电子显微镜图像的处理效果较差，因为它已经过“训练”以处理晶体学图像。需要进行一些再培训，可能还需要一些新方法。该项目生产的所有软件将通过现有的晶体学和电子显微镜软件套件免费分发给学术用户。软件的源代码也将被分发，以便其他开发人员可以学习或修改它。