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通过多尺度模拟和蛋白质设计预测丝纤维的力学性能。

Predicting Silk Fiber Mechanical Properties through Multiscale Simulation and Protein Design.

作者信息

Rim Nae-Gyune, Roberts Erin G, Ebrahimi Davoud, Dinjaski Nina, Jacobsen Matthew M, Martín-Moldes Zaira, Buehler Markus J, Kaplan David L, Wong Joyce Y

机构信息

Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, Massachusetts 02215, United States.

Division of Materials Science and Engineering, Boston University, 44 Cummington Mall, Boston, Massachusetts 02215, United States.

出版信息

ACS Biomater Sci Eng. 2017 Aug 14;3(8):1542-1556. doi: 10.1021/acsbiomaterials.7b00292. Epub 2017 Jul 3.

Abstract

Silk is a promising material for biomedical applications, and much research is focused on how application-specific, mechanical properties of silk can be designed synthetically through proper amino acid sequences and processing parameters. This protocol describes an iterative process between research disciplines that combines simulation, genetic synthesis, and fiber analysis to better design silk fibers with specific mechanical properties. Computational methods are used to assess the protein polymer structure as it forms an interconnected fiber network through shearing and how this process affects fiber mechanical properties. Model outcomes are validated experimentally with the genetic design of protein polymers that match the simulation structures, fiber fabrication from these polymers, and mechanical testing of these fibers. Through iterative feedback between computation, genetic synthesis, and fiber mechanical testing, this protocol will enable a priori prediction capability of recombinant material mechanical properties via insights from the resulting molecular architecture of the fiber network based entirely on the initial protein monomer composition. This style of protocol may be applied to other fields where a research team seeks to design a biomaterial with biomedical application-specific properties. This protocol highlights when and how the three research groups (simulation, synthesis, and engineering) should be interacting to arrive at the most effective method for predictive design of their material.

摘要

丝绸是生物医学应用中一种很有前景的材料,许多研究都集中在如何通过适当的氨基酸序列和加工参数来综合设计特定应用的丝绸机械性能。本方案描述了不同研究学科之间的迭代过程,该过程结合了模拟、基因合成和纤维分析,以更好地设计具有特定机械性能的丝绸纤维。计算方法用于评估蛋白质聚合物结构,因为它通过剪切形成相互连接的纤维网络,以及这个过程如何影响纤维的机械性能。通过对与模拟结构匹配的蛋白质聚合物进行基因设计、用这些聚合物制造纤维并对这些纤维进行机械测试,对模型结果进行实验验证。通过计算、基因合成和纤维机械测试之间的迭代反馈,本方案将能够通过完全基于初始蛋白质单体组成的纤维网络分子结构所获得的见解,对重组材料的机械性能进行先验预测。这种方案风格可应用于其他领域,即研究团队试图设计具有特定生物医学应用性能的生物材料的领域。本方案强调了三个研究小组(模拟、合成和工程)何时以及如何相互作用,以找到最有效的材料预测设计方法。

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Progress and Trends in Artificial Silk Spinning: A Systematic Review.人造丝纺丝的进展与趋势:一项系统综述
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Predicting rates of in vivo degradation of recombinant spider silk proteins.预测重组蜘蛛丝蛋白在体内的降解速率。
J Tissue Eng Regen Med. 2018 Jan;12(1):e97-e105. doi: 10.1002/term.2380. Epub 2017 May 23.
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Recombinant DNA production of spider silk proteins.蜘蛛丝蛋白的重组 DNA 生产。
Microb Biotechnol. 2013 Nov;6(6):651-63. doi: 10.1111/1751-7915.12081.
9
Heat Capacity of Spider Silk-like Block Copolymers.类蜘蛛丝嵌段共聚物的热容量
Macromolecules. 2011 Jul 12;44(13):5299-5309. doi: 10.1021/ma200563t.

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