.png){kind=icon}
返回
A new algorithm for particle weighted subtraction to decrease signals from unwanted components in single particle analysis
.png){kind=icon}
OA
AI
DOI：10.1016/j.jsb.2023.108024.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Single particle analysis (SPA) in cryo-electron microscopy (cryo-EM) is highly used to obtain the near-atomic structure of biological macromolecules. The current methods allow users to produce high-resolution maps from many samples. However, there are still challenging cases that require extra processing to obtain high resolution. This is the case when the macromolecule of the sample is composed of different components and we want to focus just on one of them. For example, if the macromolecule is composed of several flexible subunits and we are interested in a specific one, if it is embedded in a viral capsid environment, or if it has additional components to stabilize it, such as nanodiscs. The signal from these components, which in principle we are not interested in, can be removed from the particles using a projection subtraction method. Currently, there are two projection subtraction methods used in practice and both have some limitations. In fact, after evaluating their results, we consider that the problem is still open to new solutions, as they do not fully remove the signal of the components that are not of interest. Our aim is to develop a new and more precise projection subtraction method, improving the performance of state-of-the-art methods. We tested our algorithm with data from public databases and an in-house data set. In this work, we show that the performance of our algorithm improves the results obtained by others, including the localization of small ligands, such as drugs, whose binding location is unknown a priori.
Keyword:
Projection subtraction
Nanodisc
Ligand
SPA
Cryo-EM
期刊
IF:
2.7
论文数:
4.4K
被引数:
1.0W
机构
引用论文
分享收藏Cryo-EM density maps adjustment for subtraction, consensus and sharpening用于减法，共识和锐化的cryo-em密度图调整OAAI
OAAI分享收藏cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determinationcryoSPARC: 用于快速无监督cryo-em结构确定的算法.png)
NATURE METHODS
NATURE METHODSIF32.1
PREAI
分享收藏Xmipp 3.0: An improved software suite for image processing in electron microscopyXmipp 3.0: 一种改进的电子显微镜图像处理软件套件
PREAI
分享收藏Advances in Xmipp for Cryo-Electron Microscopy: From Xmipp to ScipionXmipp用于低温电子显微镜的研究进展: 从Xmipp到ScipionMOLECULES
OAAI
MOLECULESIF4.6
OAAI分享收藏
查看更多内容