Automated building of carbohydrate molecules using X-ray crystallography data

碳水化合物分子是生命世界中必不可少的一部分，构成了我们食物中的糖、衣服中的纤维和绿色植物的细胞壁。碳水化合物与其他生物分子，特别是蛋白质的相互作用是许多生物过程的重要组成部分。了解这种相互作用对于了解细胞如何工作和相互作用很重要，对于分解纤维垃圾和开发生物洗衣粉等各种生物技术也很重要。高等生物分泌的许多蛋白质都有直接构建在其结构中的碳水化合物，那些被结合到细胞膜中的蛋白质有助于细胞-细胞识别。X射线结晶学-本质上是一种极其强大的显微镜-使我们能够看到蛋白质等生物大分子三维结构中的原子。这一知识对于理解此类分子执行其任务至关重要。蛋白质-糖复合体和糖蛋白可以用结晶学来研究，但虽然蛋白质通常可以在生成的3D结构中相当清楚地看到，但糖往往是模糊的，因为碳水化合物通常相当灵活。用原子和键来解释放大的图像可能是一个耗时的项目，并且结果有点主观性。这个项目的目的是提供一种执行这种解释的自动化方法。虽然自动化是有价值的，因为它解放了研究人员的时间专注于科学问题，但更重要的好处是，它允许探索放大的电子密度图像的许多可能的解释。在困难的情况下，这一较大的起始模型集更有可能包含由结晶学家建立的单个模型的正确答案。然后，可以对不同的模型进行排序，以选择最好的模型。蛋白质的结构很容易通过已知的方法建立，留下一个无法解释的电子密度块，必须将糖放入其中。将使用现有的基于网络的软件和蛋白质数据库(PDB)确定糖的初步可能结构。约克大学的考坦博士此前曾编写计算机软件，仅凭电子密度就能成功识别出核酸(包括携带遗传信息的DNA)中的糖环。“指纹”技术涉及识别糖存在时始终存在的形状。这一方法将被修改，以识别碳水化合物中的糖环。每个可能的环形状都将根据X射线结果进行测试，并将相邻的环连接在一起。这将给出一大堆可能的结构，这些结构可以通过基于3D X射线图的自动评分方法和化学的可信程度进行排序。(1)碳水化合物分子(如酶底物)与蛋白质形成复合体结晶，(2)糖是糖蛋白的组成部分。该软件将在无处不在的‘Coot’图形建模软件中实现，从而使整个用户社区，无论是学术上的还是商业上的，都可以使用。结果将是对来自活的生物体的大分子的3D结构中的糖的更可靠和更客观的解释，这反过来将使人们能够更好地了解这些糖在基本生物过程中的作用。

Carbohydrate molecules are an essential part of the living world, making up the sugars in our food, the fibres in clothes and the cell walls of green plants. The interaction of carbohydrates with other biological molecules, and in particular proteins, is an important part of many biological processes. Understanding this interaction is important for understanding how cells work and interact with one another, as well as being important to diverse bio-technologies such as the breaking down of fibrous landfill waste and the development of biological washing powders. Many proteins secreted by higher organisms have carbohydrates built directly into their structure and those incorporated into the cell membrane contribute to cell-cell recognition.X-ray crystallography - essentially an extremely powerful microscope - allows us to see the atoms in the 3D structures of biological macromolecules such as proteins. This knowledge is vital to an understanding of such molecules carry out their tasks. Protein-sugar complexes and glycoproteins can be studied using crystallography, but while the protein can often be seen fairly clearly in the resulting 3D structure, the sugar is often blurry because carbohydrates are often rather flexible. Interpreting the magnified image in terms of atoms and bonds can be a time consuming project, and the results somewhat subjective.The aim of this project is to provide an automated method for performing this interpretation. While automation is of value in that it frees up researcher time to concentrate on the scientific problems, a more important benefit is that it allows many possible interpretations of the magnified electron density image to be explored. In difficult cases this larger starting set of models is more likely to contain the correct answer that a single model built by a crystallographer. The different models can then be ranked to choose the best one.The structure of the protein is easily built by known methods, leaving a 'blob' of unaccounted for electron density into which the sugar must be placed. An initial set of possible structures for the sugar will be determined using existing web-based software and the Protein Data Bank (PDB). Dr. Cowtan at York University has previously written computer software which successfully identifyies the sugar rings in nucleic acids (including DNA which carries the genetic information) from their electron density alone. The 'fingerprint' technique involves the identification of shapes which are always present when the sugar is present. This approach will be modified to identify sugar rings in the carbohydrates. Each possible ring shape will be tested against the X-ray result, and neighbouring rings will be linked together. This will give a large pool of possible structures which can be ranked by automatic scoring methods based on the 3D X-ray maps and the plausibility of the chemistry.The resulting methods will be applied to two problems. The building of (1) carbohydrate molecules (such as enzyme substrates) crystallised in complex with proteins and (2) the sugars which are an integral part of glycoproteins. The software will be implemented in the ubiquitous 'Coot' graphical model building software, and will thus be made available to whole user community, both academic and commercial.The result will be a more reliable and more objective interpretation of sugars in 3D structures of macromolecules from living organisms, which in turn will enable greater understanding of the roles of these sugars in essential biological processes.