Novel Algorithms for Crystallographic Computing

描述(申请人提供)：自19世纪中期以来，晶体的X射线衍射数据分析已被广泛用于确定分子结构和性质。虽然这种方法在世界范围内几乎是例行公事，但识别最符合衍射数据的三维结构往往是一个重大挑战。特别是，一个关键的障碍是仅从强度测量来识别衍射光的相位。这一问题被称为结晶学中的“相问题”，其解决方案是推进大分子结晶学和结构生物学前沿的主要障碍。 这个项目的主要目标是开发一种系统的方法来解决晶体计算中的相问题。为此，我们计划：(A)开发新的数学模型，用于根据单晶X射线衍射测量确定三维晶体结构；(B)设计数学优化算法，以可靠和有效的方式求解上述模型，从而增加易处理结构的尺寸；(C)开发实现上述模型和算法的计算系统，并向研究界提供执行上述模型和算法的计算系统；以及(D)应用所开发的方法来确定蛋白质和其他重要生物大分子的三维结构。该项目将建立在首席调查员最近开创的一种新算法的基础上，以解决合作团队已经证明能够解开生物分子结构的模型。 该项目的更广泛影响包括指导研究生和博士后受训人员，将研究成果纳入生物信息学课程，以及通过实施该项目成果的在线软件广泛传播。拟议的工作有望为新一代晶体计算系统奠定基础，这些系统将揭示在理解生命、材料科学和药物设计中重要的结构。对社会的长期影响可能是巨大的，因为该项目可能导致能够破译生命秘密的方法，并在新药开发中发挥关键作用。

DESCRIPTION (provided by applicant): Since the mid nineteen hundreds, analysis of X-ray diffraction data of crystals has been used extensively for the determination of molecular structure and properties. While the method is employed almost on a routine basis worldwide, it is often a major challenge to identify the three-dimensional structure that best fits the diffraction data. A key obstacle, in particular, is the identification of the phases of the diffracted rays from measurements of intensities alone. This problem is known as the "phase problem" in crystallography and its solution represents a major obstacle towards advancing the frontiers of macromolecular crystallography and structural biology. The primary goal of this project is the development of a systematic methodology for resolving the phase problem in crystallographic computing. Towards this goal, we plan to: (a) develop novel mathematical models for determining three-dimensional crystal structures from single crystal X-ray diffraction measurements; (b) devise mathematical optimization algorithms to solve the above models in a reliable and efficient way, thus increasing the size of tractable structures; (c) develop and make available to the research community a computational system implementing the above models and algorithms; and (d) apply the developed methodology to determine the three-dimensional structures of proteins and other important biological macromolecules. The project will build on a novel algorithm recently pioneered by the Principal Investigator to solve a model that has been demonstrated by the collaborating team to be capable of unraveling structures of biomolecules. The broader impacts of the project include mentoring of graduate students and postdoctoral trainees, integration of research results in a Bioinformatics course, and wide dissemination through on-line software implementing the results of this project. The proposed work promises to lay the foundations of a new generation of crystallographic computing systems that will reveal structures important in the understanding of life, materials science, and drug design. The long term impact to society could be immense as the project could lead to methodology capable of deciphering the secrets of life and playing a pivotal role in the development of new drugs.