Structure

杂志介绍

Structure杂志介绍

《Structure》是一本以English为主的未开放获取国际优秀期刊，中文名称结构，本刊主要出版、报道生物-生物物理领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCI、SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为4.862，最新CiteScore 指数为9.8。

本刊近期中国学者发表的论文主要有：

• A non-canonical target-binding site in Munc18-1 domain 3b for assembling the Mint1-Munc18-1-syntaxin-1 comple

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• An epitope-directed selection strategy facilitating the identification of Frizzled receptor selective antibodie

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• Conformational change of a-synuclein fibrils in cerebrospinal fluid from different clinical phases of Parkinson's diseas

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• Addressing compressive deformation of proteins embedded in crystalline ic

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英文介绍

Structure杂志英文介绍

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.