New Tools for Experimental Phasing of Twinned Diffraction Data

用于孪生衍射数据实验定相的新工具

• 批准号: 10022493
• 负责人: Petrus H Zwart
• 金额: $ 30.14万
• 依托单位: UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-23 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10022493
• 关键词: Achievement; Address; Adopted; Algorithms; Awareness; Bayesian Method; Binding; Biochemical Process; Characteristics; Communities; Complement; Computer software; Crystallization; Crystallography; Data; Data Collection; Detection; Dimensions; Goals; Hybrids; Inequality; Infrastructure; Intuition; Likelihood Functions; Link; Mainstreaming; Maps; Medical; Methods; Modeling; Modernization; Modification; Molecular; Nature; Pathology; Phase; Preparation; Proteins; Research Personnel; Route; Sampling; Shapes; Site; Specific qualifier value; Structural Models; Structure; Techniques; Twin Multiple Birth; Work; base; computer framework; data space; density; improved; insight; macromolecule; novel therapeutics; restraint; structural biology; success; theories; tool

Summary Crystallography is an indispensable tool in modern structural biology, allowing for precise determination of molecular interactions in proteins. The majority of the computational crystallographic tools available have been developed on the prerequisite that the diffraction data is free from pathologies such as twinning. For the detection of twinned data and refinement of structures, excellent software is already available, but for more upstream tasks, no general‐ purpose tools are available. The absence of tools that allow handling of twinned data has resulted in practical difficulties when solving structures from such data. This proposal addresses this critical gap by developing twinning‐aware tools and algorithms for all mainstream crystallographic tasks for which no such tools exist. We propose to adopt and extend existing density modification and heavy atom determination methods such that they are suited for handling twinned data. The proposed algorithm propagates vital prior information from real space all the way into data space, numerically stabilizing an otherwise ill‐conditioned detwinning step using a regularization approach. To provide the community with a full complement of tools for de novo phasing, heavy atom refinement and phasing strategies will be addressed by developing and evaluating numerical techniques needed for the twinned‐SAD likelihood function. This problem will be addressed using an adaptive quadrature approach.

概括 晶体学是现代结构生物学中不可或缺的工具，可以精确地分析 确定蛋白质中的分子相互作用。 可用的晶体学工具是在衍射数据的前提下开发的 没有诸如孪生之类的病态，用于孪生数据的检测和细化。 结构，优秀的软件已经可用，但对于更多的上游任务，没有通用的 导致缺乏可以处理配对数据的工具。 在从此类数据求解结构时遇到实际困难时，该提案解决了这个问题。 通过所有主流的孪生感知工具和算法来开发关键差距 我们建议采用并扩展现有的晶体学任务。 密度修改和重原子测定方法，使其适用于 处理孪生数据。所提出的算法传播来自真实数据的重要先验信息。 空间一直进入数据空间，在数值上稳定否则病态的解孪生 使用正则化方法为社区提供完整的工具。 对于从头定相，重原子精炼和定相策略将通过 开发和评估孪生 SAD 可能性所需的数值技术 该问题将使用自适应正交方法来解决。