Applications of Real-Space Refinement for Macromolecular Structure Analysis

将开发计算方法，通过X射线结晶学和电子显微镜来确定、精炼和解释大分子结构。晶体结构的确定包括使用交互式计算机程序将原子模型手动建立到电子密度图中，然后自动将模型修正为衍射幅度。结晶学应用将在模型建立和自动互易空间精化之间架起一座桥梁，这一过渡是一个瓶颈，也是晶体结构确定中主要误差的常见来源。使用约束实空间精化的新技术，在放弃相而进行传统的倒易空间精化之前，模型对电子密度的拟合将被优化，这样的局部精化又允许改进相和图，从而完成了一种新的模型改进方法的迭代周期，该方法摆脱了遗漏图的反馈偏差。因此，新方法将产生广泛的科学影响，因为它们将为结构生物学实验室常见的计算机平台而建造。新的方法将增加可完成的大分子结构测定的数量，提高质量，减少出错的机会，并减少所需的资源。因此，这项工作将有助于我们进一步了解单个大分子的功能，以及它们在许多细胞过程中至关重要的大分子组装中的相互作用。该奖项由计算生物学活动和生物物理学项目支持。

Computational methods will be developed for the determination, refinement and interpretation of macromolecular structures by X-ray crystallography and electron microscopy. Crystallographic structure determination involves the manual building of atomic model into an electron density map, using interactive computer programs, followed by automatic refinement of the model to the diffraction amplitudes. The crystallographic applications will bridge the transition between model building and automatic reciprocal-space refinement, a transition that is a bottle-neck and a common source of major errors in crystallographic structure determination. Using new techniques of restrained real-space refinement, the fit of the model to the electron density will be optimized before the phases are abandoned for conventional reciprocal-space refinement Such local refinement, in turn allows the phases and map to be improved, completing an iterative cycle for a new method of model improvement that is free from the feedback bias of omit-maps. Thus the new methods will have broad scientific impact since they will be built for computer platforms common to the structural biology laboratories. The new methods will increase the number of macromolecular structure determinations that can be completed, improve the quality, decrease the chance of errors, and decrease the resources that are required. Thus, this work will help further our understanding of the function of individual macromolecules, and of their interactions in the macromolecular assemblies that are central to many cellular processes. This award is supported by the Computational Biology Activity and the Biophysics programs.