Transcription termination—Some like it hot

IF 4.4 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Kristine Bourke Arnvig, Finn Werner
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引用次数: 0

Abstract

In this issue of Structure, Dikunova et al.1 report the structure of the trimeric torpedo complex, the key factor responsible for transcription termination by RNA polymerase II R(NAPII) at the end of protein-encoding genes. The comparison between meso- and thermophilic torpedoes provides intriguing insights into thermal adaptions and mechanisms of termination.
在本期《结构》杂志上,Dikunova 等人1 报告了三聚鱼雷复合体的结构,该复合体是 RNA 聚合酶 II R(NAPII)在编码蛋白质基因末端终止转录的关键因子。通过比较中温鱼雷和嗜热鱼雷,人们对热适应性和终止机制有了更深入的了解。
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来源期刊
Structure
Structure 生物-生化与分子生物学
CiteScore
8.90
自引率
1.80%
发文量
155
审稿时长
3-8 weeks
期刊介绍: Structure aims to publish papers of exceptional interest in the field of structural biology. The journal strives to be essential reading for structural biologists, as well as biologists and biochemists that are interested in macromolecular structure and function. Structure strongly encourages the submission of manuscripts that present structural and molecular insights into biological function and mechanism. Other reports that address fundamental questions in structural biology, such as structure-based examinations of protein evolution, folding, and/or design, will also be considered. We will consider the application of any method, experimental or computational, at high or low resolution, to conduct structural investigations, as long as the method is appropriate for the biological, functional, and mechanistic question(s) being addressed. Likewise, reports describing single-molecule analysis of biological mechanisms are welcome. In general, the editors encourage submission of experimental structural studies that are enriched by an analysis of structure-activity relationships and will not consider studies that solely report structural information unless the structure or analysis is of exceptional and broad interest. Studies reporting only homology models, de novo models, or molecular dynamics simulations are also discouraged unless the models are informed by or validated by novel experimental data; rationalization of a large body of existing experimental evidence and making testable predictions based on a model or simulation is often not considered sufficient.
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