Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel.
Protein Sci. 2021 Jan;30(1):151-159. doi: 10.1002/pro.3970. Epub 2020 Oct 28.
The functional sites of many protein families are dominated by diverse backbone regions that lack secondary structure (loops) but fold stably into their functionally competent state. Nevertheless, the design of structured loop regions from scratch, especially in functional sites, has met with great difficulty. We therefore developed an approach, called AbDesign, to exploit the natural modularity of many protein families and computationally assemble a large number of new backbones by combining naturally occurring modular fragments. This strategy yielded large, atomically accurate, and highly efficient proteins, including antibodies and enzymes exhibiting dozens of mutations from any natural protein. The combinatorial backbone-conformation space that can be accessed by AbDesign even for a modestly sized family of homologs may exceed the diversity in the entire PDB, providing the sub-Ångstrom level of control over the positioning of active-site groups that is necessary for obtaining highly active proteins. This manuscript describes how to implement the pipeline using code that is freely available at https://github.com/Fleishman-Lab/AbDesign_for_enzymes.
许多蛋白质家族的功能位点主要由不同的骨架区域主导,这些区域缺乏二级结构(环),但能稳定折叠成具有功能的状态。然而,从头开始设计结构环区域,特别是在功能位点,一直具有很大的难度。因此,我们开发了一种名为 AbDesign 的方法,利用许多蛋白质家族的自然模块化,并通过组合天然存在的模块片段来计算组装大量新的骨架。该策略生成了大型的、原子精确的、高效的蛋白质,包括抗体和酶,它们具有几十种来自任何天然蛋白质的突变。即使对于一个中等大小的同源家族,AbDesign 可以访问的组合骨架构象空间也可能超过整个 PDB 的多样性,从而提供对活性位点基团定位的亚埃级控制,这对于获得高活性的蛋白质是必要的。本文档介绍了如何使用可在 https://github.com/Fleishman-Lab/AbDesign_for_enzymes 上免费获得的代码来实现该流水线。