Department of Biochemistry, University of Washington, Seattle, WA, USA.
Institute for Protein Design, University of Washington, Seattle, WA, USA.
FEBS J. 2018 May;285(10):1783-1785. doi: 10.1111/febs.14394. Epub 2018 Mar 6.
Recent advances in computational protein design now enable the massively parallel de novo design and experimental characterization of small hyperstable binding proteins with potential therapeutic activity. By providing experimental feedback on tens of thousands of designed proteins, the design-build-test-learn pipeline provides a unique opportunity to systematically improve our understanding of protein folding and binding. Here, we review the structures of mini-protein binders in complex with Influenza hemagglutinin and Bot toxin, and illustrate in the case of disulfide bond placement how analysis of the large datasets of computational models and experimental data can be used to identify determinants of folding and binding.
最近在计算蛋白质设计方面的进展使得可以大规模并行从头设计和实验表征具有潜在治疗活性的超小稳定结合蛋白。通过对成千上万种设计的蛋白质进行实验反馈，设计-构建-测试-学习的管道提供了一个独特的机会，可以系统地提高我们对蛋白质折叠和结合的理解。在这里，我们回顾了与流感血凝素和博特毒素复合物的迷你蛋白结合物的结构，并举例说明了如何分析计算模型和实验数据的大型数据集，以确定折叠和结合的决定因素。
