Aberrant tau condensates as catalytic microcompartments propel tau fibrillation

IF 4.4 2区生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Structure Pub Date : 2024-10-03 DOI:10.1016/j.str.2024.09.004

Agustín Mangiarotti, Asima Nayak, Dragomir Milovanovic

引用次数: 0

Abstract

In this issue of Structure, Soeda et al.¹ employed optogenetic tools and demonstrate that an N-terminal truncation of tau and microtubule-binding deficiency lead to the formation of tau condensates, accelerating its fibrillation.

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作为催化微空腔的畸变 tau 凝聚物推动 tau 纤维化

在本期《结构》杂志上，Soeda 等人1 利用光遗传学工具证明，tau 的 N 端截断和微管结合缺陷会导致 tau 凝聚物的形成，从而加速其纤维化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

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.