CCP4 Advanced integrated approaches to macromolecular structure determination

蛋白质、DNA和RNA是构成活的有机体的细胞的活动机器，统称为大分子。它们执行维持生命的所有功能，从新陈代谢、复制到细胞与环境之间的信息交换。它们是由基因组中DNA序列形式的“蓝图”编码的，该蓝图描述了如何使它们成为构建块的线性字符串。然而，为了发挥功能，大多数大分子都会折叠成精确的3D结构，而这又主要取决于构成它们的构件的顺序。对分子3D结构的了解使我们既能了解它的功能，又能设计出干扰它的化学物质。由于分子生物学的进步，包括人类基因组计划在内的许多项目已经导致了许多生物的完整DNA序列的确定，我们现在可以从这些DNA序列中读取许多大分子的线性蓝图。然而，到目前为止，仅根据序列的知识还不能预测3D结构。要“看到”大分子，从而确定其3D结构，一种方法是首先使研究中的分子结晶，然后用适当的辐射对其进行成像。大分子太小，用普通光线看不见，因此需要一种不同的方法。用光学显微镜我们看不到小于光波长的物体，大约是百万分之一米：原子大约比这小1000倍。然而，X射线的波长与原子的大小大致相同。因此，为了解析大分子结构的原子细节，我们用X射线而不是可见光来成像它们。成像已经结晶的大分子结构的过程被称为X射线结晶学。X射线结晶学就像用显微镜放大那些用可见光看不到的小物体。不幸的是，X射线结晶学是复杂的，因为与显微镜不同，没有X射线的透镜系统，因此需要额外的信息和复杂的计算来重建最终的图像。这些信息可能来自使用分子置换(MR)方法的已知蛋白质结构，或者来自包括电子显微镜(EM)在内的其他来源。一旦知道了结构，就更容易确定大分子如何对活的细胞机器做出贡献。药学研究利用这一点作为设计药物的基础，以便在需要时打开或关闭分子。药物被设计成与目标分子相互作用，以阻止或促进它们在体内执行的化学过程。其他应用包括蛋白质工程和碳水化合物工程。该项目的目的是改进从X射线和电子衍射实验中提取3D结构所需的关键计算工具。它将继续支持一个合作计算项目(CCP4，最初设立于1979年)，该项目已成为这项任务的主要软件来源之一。该项目将有助于高效和有效地使用同步加速器，这些同步加速器制造大多数结晶学实验中使用的X射线，但也扩展到电子显微镜的使用，电子显微镜最近获得了很大的宣传，诺贝尔奖被授予该领域的研究人员。它将提供更强大的工具，允许用户在与未知结构匹配非常差的情况下利用已知蛋白质结构的信息。最后，它将允许解决结构，即使得到的质量很差和非常小的晶体。

Proteins, DNA and RNA are the active machines of the cells which make up living organisms, and are collectively known as macromolecules. They carry out all of the functions that sustain life, from metabolism through replication to the exchange of information between a cell and its environment. They are coded for by a 'blueprint' in the form of the DNA sequence in the genome, which describes how to make them as linear strings of building blocks. In order to function, however, most macromolecules fold into a precise 3D structure, which in turn depends primarily on the sequence of building blocks from which they are made. Knowledge of the molecule's 3D structure allows us both to understand its function, and to design chemicals to interfere with it. Due to advances in molecular biology, a number of projects, including the Human Genome Project, have led to the determination of the complete DNA sequences of many organisms, from which we can now read the linear blueprints for many macromolecules. As yet, however, the 3D structure cannot be predicted from knowledge of the sequence alone. One way to "see" macromolecules, and so to determine their 3D structure, involves initially crystallising the molecule under investigation, and subsequently imaging it with suitable radiation. Macromolecules are too small to see with normal light, and so a different approach is required. With an optical microscope we cannot see objects which are smaller than the wavelength of light, roughly 1 millionth of a metre: Atoms are about 1000 times smaller than this. However X-rays have a wavelength about the same as the size of the atoms. For this reason, in order to resolve the atomic detail of macromolecular structure, we image them with X-rays rather than with visible light.The process of imaging the structures of macromolecules that have been crystallised is known as X-ray crystallography. X- ray crystallography is like using a microscope to magnify objects that are too small to be seen with visible light. Unfortunately X-ray crystallography is complicated because, unlike a microscope, there is no lens system for X-rays and so additional information and complex computation are required to reconstruct the final image. This information may come from known protein structures using the Molecular Replacement (MR) method, or from other sources including Electron Microscopy (EM). Once the structure is known, it is easier to pinpoint how macromolecules contribute to the living cellular machinery. Pharmaceutical research uses this as the basis for designing drugs to turn the molecules on or off when required. Drugs are designed to interact with the target molecule to either block or promote the chemical processes which they perform within the body. Other applications include protein engineering and carbohydrate engineering. The aim of this project is to improve the key computational tools needed to extract a 3D structure from X-ray and electron diffraction experiments. It will provide continuing support to a Collaborative Computing Project (CCP4 first established in 1979), which has become one of the leading sources of software for this task. The project will help efficient and effective use to be made of the synchrotrons that make the X-rays that are used in most crystallographic experiments but also extend to use of electron microscopes which have gained much recent publicity with the Nobel prize being awarded to researchers from this field. It will provide more powerful tools to allow users to exploit information from known protein structures when the match to the unknown structure is very poor. Finally, it will allow structures to be solved, even when poor quality and very small crystals are obtained.