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使用罗塞塔结构预测法解决复杂分子置换问题

Rosetta Structure Prediction as a Tool for Solving Difficult Molecular Replacement Problems.

作者信息

DiMaio Frank

机构信息

Department of Biochemistry, Institute of Protein Design, University of Washington, Seattle, WA, USA.

出版信息

Methods Mol Biol. 2017;1607:455-466. doi: 10.1007/978-1-4939-7000-1_19.

Abstract

Molecular replacement (MR), a method for solving the crystallographic phase problem using phases derived from a model of the target structure, has proven extremely valuable, accounting for the vast majority of structures solved by X-ray crystallography. However, when the resolution of data is low, or the starting model is very dissimilar to the target protein, solving structures via molecular replacement may be very challenging. In recent years, protein structure prediction methodology has emerged as a powerful tool in model building and model refinement for difficult molecular replacement problems. This chapter describes some of the tools available in Rosetta for model building and model refinement specifically geared toward difficult molecular replacement cases.

摘要

分子置换(MR)是一种利用源自目标结构模型的相位来解决晶体学相位问题的方法,已证明具有极高的价值,X射线晶体学解析的绝大多数结构都采用了该方法。然而,当数据分辨率较低,或者起始模型与目标蛋白差异很大时,通过分子置换来解析结构可能极具挑战性。近年来,蛋白质结构预测方法已成为解决困难分子置换问题时进行模型构建和模型优化的有力工具。本章介绍了Rosetta中一些专门针对困难分子置换案例的模型构建和模型优化工具。

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