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介绍大分子实验相图的 SHELX 软件;新增自动追踪功能。

An introduction to experimental phasing of macromolecules illustrated by SHELX; new autotracing features.

机构信息

Structural Biology, IBMB-CSIC, Baldiri Reixach 13-15, 08028 Barcelona, Spain.

Department of Structural Chemistry, Georg-August Universität Göttingen, Tammannstrasse 4, 37077 Göttingen, Germany.

出版信息

Acta Crystallogr D Struct Biol. 2018 Feb 1;74(Pt 2):106-116. doi: 10.1107/S2059798317015121.

Abstract

For the purpose of this article, experimental phasing is understood to mean the determination of macromolecular structures by exploiting small intensity differences of Friedel opposites and possibly of reflections measured at different wavelengths or for heavy-atom derivatives, without the use of specific structural models. The SHELX programs provide a robust and efficient route for routine structure solution by the SAD, MAD and related methods, but involve a number of simplifying assumptions that may limit their applicability in borderline cases. The substructure atoms (i.e. those with significant anomalous scattering) are first located by direct methods, and the experimental data are then used to estimate phase shifts that are added to the substructure phases to obtain starting phases for the native reflections. These are then improved by density modification and, if the resolution of the data and the type of structure permit, polyalanine tracing. A number of extensions to the tracing algorithm are discussed; these are designed to improve its performance at low resolution. Given native data to 2.5 Å resolution or better, a correlation coefficient greater than 25% between the structure factors calculated from such a trace and the native data is usually a good indication that the structure has been solved.

摘要

本文中,实验相角确定法是指利用 Friedel 相反对的小强度差异以及可能的不同波长或重原子衍生物测量的反射来确定大分子结构,而不使用特定的结构模型。SHELX 程序通过 SAD、MAD 和相关方法为常规结构解决提供了一种强大而高效的途径,但涉及到许多简化假设,这些假设可能会限制其在边缘情况下的适用性。首先通过直接法定位亚结构原子(即具有显著异常散射的原子),然后使用实验数据估计相移,将相移添加到亚结构相中来获得天然反射的起始相。然后通过密度修正来改进这些相位,并且如果数据的分辨率和结构类型允许,则进行聚丙氨酸追踪。讨论了追踪算法的一些扩展;这些扩展旨在提高其在低分辨率下的性能。对于分辨率达到 2.5 Å 或更好的天然数据,从这样的轨迹计算的结构因子与天然数据之间的相关系数大于 25%通常是结构已经解决的良好指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aaf/5947774/7d5842efec9c/d-74-00106-fig1.jpg

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