Department of Computer Science, University of Bristol, UK.
Department of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, USA.
J Struct Biol. 2018 Feb;201(2):100-107. doi: 10.1016/j.jsb.2017.09.001. Epub 2017 Sep 7.
Computational protein design methods have enabled the design of novel protein structures, but they are often still limited to small proteins and symmetric systems. To expand the size of designable proteins while controlling the overall structure, we developed Elfin, a genetic algorithm for the design of novel proteins with custom shapes using structural building blocks derived from experimentally verified repeat proteins. By combining building blocks with compatible interfaces, it is possible to rapidly build non-symmetric large structures (>1000 amino acids) that match three-dimensional geometric descriptions provided by the user. A run time of about 20min on a laptop computer for a 3000 amino acid structure makes Elfin accessible to users with limited computational resources. Protein structures with controlled geometry will allow the systematic study of the effect of spatial arrangement of enzymes and signaling molecules, and provide new scaffolds for functional nanomaterials.
计算蛋白质设计方法已经能够设计新型蛋白质结构,但它们通常仍然限于小分子蛋白和对称系统。为了在控制整体结构的同时扩大可设计蛋白的大小,我们开发了 Elfin,这是一种使用来自实验验证的重复蛋白的结构构建块设计具有自定义形状的新型蛋白的遗传算法。通过将构建块与兼容的接口相结合,有可能快速构建与用户提供的三维几何描述匹配的非对称大型结构(>1000 个氨基酸)。对于一个 3000 个氨基酸的结构,在笔记本电脑上运行大约 20 分钟,使得 Elfin 可以被计算资源有限的用户使用。具有可控几何形状的蛋白质结构将允许系统地研究酶和信号分子的空间排列的影响,并为功能纳米材料提供新的支架。