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必不可少的工具，可以精确 蛋白质中分子相互作用的测定。大多数计算 衍射数据的先决条件已经开发了可用的晶体学工具 没有诸如孪生之类的病理。为了检测孪生数据和完善 结构，出色的软件已经可用，但是对于更多上游任务，没有一般的任务 目的工具可用。缺少允许处理双数据数据的工具已导致 在从此类数据中求解结构时的实际困难中。该提议解决了这个问题 通过为所有主流开发孪生感知工具和算法，通过开发孪生感知工具和算法 不存在此类工具的晶体学任务。我们建议采用并扩展现有 密度修饰和沉重的原子测定方法，使它们适合 处理孪生数据。提出的算法传播了来自真实的重要事先信息 一路进入数据空间，从数值上稳定了原本不良条件的detwinning 使用受管制的方法步骤。为社区提供完整的工具完成 对于从头阶段，将解决重度原子的细化和相位策略 开发和评估双胞胎萨德可能性所需的数值技术 功能。该问题将使用自适应正交方法解决。