Suppr超能文献

新型重复蜘蛛丝序列的计算机分析,以了解纤维蛋白材料的进化和力学性能。

Novel In Silico Analyses of Repetitive Spider Silk Sequences to Understand the Evolution and Mechanical Properties of Fibrous Protein Materials.

机构信息

Department of Chemical Engineering, Pohang University of Science and Technology, Pohang, 37673, Korea.

出版信息

Biotechnol J. 2019 Oct;14(10):e1900138. doi: 10.1002/biot.201900138. Epub 2019 Jul 1.

Abstract

The mechanical properties of spider silks have diverged as spiders have diversely speciated. Because the main components of silks are proteins, it is valuable to investigate their sequences. However, silk sequences have been regarded as difficult information to analyze due to their imbalance and imperfect tandem repeats (ITR). Here, an in silico approach is applied to systemically analyze a group of silk sequences. It is found that every time new spider groups emerge, unique trimer motifs appear. These trimer motifs are used to find additional clues of evolution and to determine relationships with mechanical properties. For the first time, crucial evidence is provided that shows silk sequences coevolved with spider species and the mechanical properties of their fibers to adapt to new living environments. This novel approach can be used as a platform for analyzing other groups of ITR-harboring proteins and to obtain information for the design of tailor-made fibrous protein materials.

摘要

蜘蛛丝的机械性能随着蜘蛛的多样化而发生了变化。由于丝的主要成分是蛋白质,因此研究它们的序列具有重要价值。然而,由于丝序列的不平衡和不完美串联重复(ITR),它们一直被认为是难以分析的信息。在这里,采用一种计算机模拟方法来系统地分析一组丝序列。结果发现,每当新的蜘蛛群体出现时,都会出现独特的三聚体基序。这些三聚体基序用于寻找进化的额外线索,并确定与机械性能的关系。这是首次提供了重要证据,表明丝序列与蜘蛛物种以及它们纤维的机械性能共同进化,以适应新的生活环境。这种新方法可作为分析其他 ITR 富含蛋白质组的平台,并为设计定制纤维蛋白材料提供信息。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验