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Ribosome Profiling

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...

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Updated: Jun 20, 2025

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Published on: December 9, 2022

使用Ernwin,SPQR和实验SAXS数据采样全球和本地正确的RNA3D结构.

Bernhard C Thiel¹, Giovanni Bussi², Simón Poblete^3,4

¹Department of Theoretical Chemistry, University of Vienna, Währinger Strasse 17, Vienna 1090, Austria.

Nucleic acids research

|July 18, 2024

概括

我们开发了一个新的计算管道,集成小角度X射线散射 (SAXS) 数据,以建模溶液中大型RNA分子的3D结构. 这种方法将模型从低分辨率改进到原子精度,改善结构预测.

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Analyzing and Building Nucleic Acid Structures with 3DNA

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Published on: November 5, 2018

相关实验视频

Last Updated: Jun 20, 2025

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells

Published on: December 9, 2022

Analyzing and Building Nucleic Acid Structures with 3DNA

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Published on: April 26, 2013

Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering

Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering

Published on: November 5, 2018

科学领域:

结构生物学结构生物学
计算生物学计算生物学
生物物理学的生物物理.

背景情况:

在溶液中确定大RNA的3D结构是复杂的,通常需要多种实验和计算方法.
小角度X射线散射 (SAXS) 提供了几何洞察力,但需要对3D建模进行仔细解释.
现有的方法可能无法充分利用SAXS数据来准确预测RNA结构.

研究的目的:

引入一种新的多尺度计算管道,用于模拟溶液中大型RNA分子的全球形状和原子结构.
将小角度X射线散射 (SAXS) 数据有效地集成到RNA建模过程中.
从低分辨率到明确的溶剂原子细节等级上对RNA结构进行细化.

主要方法:

一个结合低分辨率螺旋模型 (Ernwin) 的多尺度管道,用于使用SAXS数据进行构造性探索.
一个核酸水平模型 (SPQR) 用于消除碰撞和结构改进.
在显式溶剂中实现层次精细化以达到原子精度.

主要成果:

管道成功建模了四个已知的RNA结构 (高达159个核酸) 的准确性.
使用SAXS数据预测了Plasmodium falciparum信号识别粒子ALU RNA的全原子结构.
预测的结构显示了一种替代的形状,比以前公布的模型更适合SAXS数据.

结论:

拟议的多尺度管道有效地整合了SAXS数据,以准确地确定溶液中的3DRNA结构.
这种方法使RNA结构从低分辨率形状到高分辨率原子模型的精细化成为可能.
该方法为结构生物学提供了一个强大的工具,特别是对于具有挑战性的RNA分子,如研究的ALURNA.