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相位推断的有向无环图

Phasertng: directed acyclic graphs for crystallographic phasing.

机构信息

Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom.

出版信息

Acta Crystallogr D Struct Biol. 2021 Jan 1;77(Pt 1):1-10. doi: 10.1107/S2059798320014746.

Abstract

Crystallographic phasing strategies increasingly require the exploration and ranking of many hypotheses about the number, types and positions of atoms, molecules and/or molecular fragments in the unit cell, each with only a small chance of being correct. Accelerating this move has been improvements in phasing methods, which are now able to extract phase information from the placement of very small fragments of structure, from weak experimental phasing signal or from combinations of molecular replacement and experimental phasing information. Describing phasing in terms of a directed acyclic graph allows graph-management software to track and manage the path to structure solution. The crystallographic software supporting the graph data structure must be strictly modular so that nodes in the graph are efficiently generated by the encapsulated functionality. To this end, the development of new software, Phasertng, which uses directed acyclic graphs natively for input/output, has been initiated. In Phasertng, the codebase of Phaser has been rebuilt, with an emphasis on modularity, on scripting, on speed and on continuing algorithm development. As a first application of phasertng, its advantages are demonstrated in the context of phasertng.xtricorder, a tool to analyse and triage merged data in preparation for molecular replacement or experimental phasing. The description of the phasing strategy with directed acyclic graphs is a generalization that extends beyond the functionality of Phasertng, as it can incorporate results from bioinformatics and other crystallographic tools, and will facilitate multifaceted search strategies, dynamic ranking of alternative search pathways and the exploitation of machine learning to further improve phasing strategies.

摘要

晶体学相位确定策略越来越需要探索和评估关于晶胞中原子、分子和/或分子片段数量、类型和位置的许多假说,而每个假说正确的可能性都很小。相位确定方法的改进加速了这一进程,现在这些方法能够从结构的非常小的片段、较弱的实验相位确定信号或分子置换和实验相位确定信息的组合中提取相位信息。用有向无环图来描述相位确定可以使图形管理软件跟踪和管理解决结构问题的路径。支持图形数据结构的晶体学软件必须严格模块化,以便图形中的节点可以通过封装的功能有效地生成。为此,已经启动了新软件 Phasertng 的开发,该软件原生地使用有向无环图进行输入/输出。在 Phasertng 中,Phaser 的代码库已经重建,重点是模块化、脚本化、速度和不断发展的算法。作为 Phasertng 的首次应用,phasertng.xtricorder 工具分析和分类合并数据,为分子置换或实验相位确定做准备,phaertng.xtricorder 展示了 Phasertng 的优势。有向无环图的相位确定策略描述是一种推广,它不仅限于 Phasertng 的功能,因为它可以纳入生物信息学和其他晶体学工具的结果,并将促进多方面的搜索策略、替代搜索路径的动态排名以及利用机器学习进一步改进相位确定策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e28b/7787104/7468c0470c38/d-77-00001-fig1.jpg

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