Centre for Engineering Biology, Institute of Quantitative Biology, Biochemistry and Biotechnology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK.
Protein Sci. 2024 Sep;33(9):e5148. doi: 10.1002/pro.5148.
In protein design, the ultimate test of success is that the designs function as desired. Here, we discuss the utility of cell free protein synthesis (CFPS) as a rapid, convenient and versatile method to screen for activity. We champion the use of CFPS in screening potential designs. Compared to in vivo protein screening, a wider range of different activities can be evaluated using CFPS, and the scale on which it can easily be used-screening tens to hundreds of designed proteins-is ideally suited to current needs. Protein design using physics-based strategies tended to have a relatively low success rate, compared with current machine-learning based methods. Screening steps (such as yeast display) were often used to identify proteins that displayed the desired activity from many designs that were highly ranked computationally. We also describe how CFPS is well-suited to identify the reasons designs fail, which may include problems with transcription, translation, and solubility, in addition to not achieving the desired structure and function.
在蛋白质设计中,成功的最终检验标准是设计是否能按预期发挥作用。在这里,我们讨论了无细胞蛋白合成(CFPS)作为一种快速、方便、通用的筛选方法的实用性。我们提倡在筛选潜在设计时使用 CFPS。与体内蛋白质筛选相比,CFPS 可以评估更广泛的不同活性,而且它的使用规模(可以轻松筛选数十到数百种设计的蛋白质)非常适合当前的需求。与基于当前机器学习的方法相比,基于物理策略的蛋白质设计的成功率相对较低。筛选步骤(如酵母展示)通常用于从许多计算上排名较高的设计中识别出表现出所需活性的蛋白质。我们还描述了 CFPS 如何适合识别设计失败的原因,这些原因可能包括转录、翻译和溶解度问题,以及无法达到预期的结构和功能。