Mining of protein data bank and feedback to X-ray crystal structure solution and analysis

其目的是改进用于确定组成活生物体的复杂生物分子的三维结构的计算机软件。这些分子是由基因组中描述如何制造它们的DNA序列形式的“蓝图”编码的。由于分子生物学的巨大进步，包括人类基因组计划在内的一些项目已经导致了一些生物的完整DNA序列的确定。因此，我们可以读懂生命中许多分子的平面。然而，如果不了解它们的3-D结构，就很难理解它们的实际工作原理。了解这一点是在它们出错时修复它们的重要一步，因此也是治愈一系列疾病以及在生物技术的一系列应用中使用这些分子的重要一步。这个问题的解决方案是通过结构生物学来解决的，在结构生物学中，分子是根据它们的蓝图制造的，并且通常使用X射线结晶学为它们构建3D模型。这使得可以用生物分子制作图片，其中的单个原子可以被识别。结晶学类似于使用显微镜来放大物体，这些物体比肉眼所能看到的要小。然而，即使是光学显微镜也有局限性，我们看不到小于光波长的物体，大约是百万分之一米。原子大约比这个小1000倍，我们需要使用X射线才能看到它们，X射线的波长与原子的大小大致相同。不幸的是，X射线结晶学的结构解决方案是复杂的，因为与光学显微镜不同，没有X射线的透镜系统，我们需要进行一些具有挑战性的实验，然后由经验丰富的科学家进行复杂的计算和解决问题。当我们观察蛋白质的晶体时，这尤其复杂，因为蛋白质晶体实际上并不完美，含有大约50%的水。这个项目的目的是改进结晶学的一些关键计算工具，使这项任务更容易和更自动化，并允许解决更困难的问题。最基本的问题在于蛋白质结晶学对参数比的观察率较低(相当于图像识别中的低信噪比)。需要先进的统计方法才能最大限度地利用现有的有限数据。

The aim is to improve the computer software used in determining the 3-D structures of complex biological molecules which make up living organisms. These molecules are coded for by a 'blueprint', in the form of a DNA sequence in the genome, which describes how to make them. Due to enormous advances in molecular biology, a number of projects, including the Human Genome Project, have led to the determination of the complete DNA sequences of a number of organisms. We can therefore read the plans for many of the molecules of life. However without knowledge of their 3-D structure, it is very hard to understand how they actually work. Understanding this is an important step in fixing them when they go wrong, and therefore, in curing a range of illnesses as well as using such molecules in a range of applications in biotechnology. The solution to this problem is through Structural Biology, in which the molecules are manufactured on the basis of their blueprints and 3-D models are constructed for them usually using X-ray crystallography. This allows pictures to be made of biological molecules in which individual atoms can be identified. Crystallography is analogous to the use of a microscope to magnify objects, which are smaller than can seen with the naked eye. However, even the optical microscope has limitations, and we cannot see objects which are smaller than the wavelength of light, roughly 1 millionth of a metre. Atoms are about 1000 times small than this, and we need to use X-rays, which have a wavelength about the same as the size of the atoms, in order to see them. Unfortunately structure solution by X-ray crystallography is complicated because unlike the optical microscope, there is no lens system for X-rays and we need to carry out a number of challenging experiments followed by complex computation and problem solving by experienced scientists. This is especially complex when we look at crystals of proteins, which are actually imperfect and contain about 50% water. The aim of this project is to improve some of the key computational tools of crystallography to make this task easier and more automatic, and to allow the solution of more difficult problems. The basic problem lies in the low observation to parameter ration in protein crystallography (equivalent to a low signal-to-noise ratio in image recognition). Advanced statistical methods are required to make the best use of the limited data available.