Pena-Francesch Abdon, Jung Huihun, Segad Mo, Colby Ralph H, Allen Benjamin D, Demirel Melik C
Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
ACS Biomater Sci Eng. 2018 Mar 12;4(3):884-891. doi: 10.1021/acsbiomaterials.7b00830. Epub 2018 Feb 15.
Topological defects in highly repetitive structural proteins strongly affect their mechanical properties. However, there are no universal rules for structure-property prediction in structural proteins due to high diversity in their repetitive modules. Here, we studied the mechanical properties of tandem-repeat proteins inspired by squid ring teeth proteins using rheology and tensile experiments as well as spectroscopic and X-ray techniques. We also developed a network model based on entropic elasticity to predict structure-property relationships for these proteins. We demonstrated that shear modulus, elastic modulus, and toughness scale inversely with the number of repeats in these proteins. Through optimization of structural repeats, we obtained highly efficient protein network topologies with 42 MJ/m ultimate toughness that are capable of withstanding deformations up to 350% when hydrated. Investigation of topological network defects in structural proteins will improve the prediction of mechanical properties for designing novel protein-based materials.
高度重复的结构蛋白中的拓扑缺陷会强烈影响其力学性能。然而，由于结构蛋白重复模块的高度多样性，目前尚无用于预测其结构-性能关系的通用规则。在此，我们以鱿鱼环齿蛋白为灵感来源，通过流变学和拉伸实验以及光谱和X射线技术，研究了串联重复蛋白的力学性能。我们还基于熵弹性开发了一个网络模型，以预测这些蛋白的结构-性能关系。我们证明，这些蛋白的剪切模量、弹性模量和韧性与重复次数成反比。通过优化结构重复序列，我们获得了具有42 MJ/m极限韧性的高效蛋白质网络拓扑结构，水合时能够承受高达350%的变形。对结构蛋白拓扑网络缺陷的研究将改善对力学性能的预测，从而设计新型蛋白质基材料。
