Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
Protein Sci. 2012 Jul;21(7):949-63. doi: 10.1002/pro.2096. Epub 2012 Jun 8.
Given the importance of protein-protein interactions for nearly all biological processes, the design of protein affinity reagents for use in research, diagnosis or therapy is an important endeavor. Engineered proteins would ideally have high specificities for their intended targets, but achieving interaction specificity by design can be challenging. There are two major approaches to protein design or redesign. Most commonly, proteins and peptides are engineered using experimental library screening and/or in vitro evolution. An alternative approach involves using protein structure and computational modeling to rationally choose sequences predicted to have desirable properties. Computational design has successfully produced novel proteins with enhanced stability, desired interactions and enzymatic function. Here we review the strengths and limitations of experimental library screening and computational structure-based design, giving examples where these methods have been applied to designing protein interaction specificity. We highlight recent studies that demonstrate strategies for combining computational modeling with library screening. The computational methods provide focused libraries predicted to be enriched in sequences with the properties of interest. Such integrated approaches represent a promising way to increase the efficiency of protein design and to engineer complex functionality such as interaction specificity.
鉴于蛋白质-蛋白质相互作用对几乎所有生物过程都很重要,因此设计用于研究、诊断或治疗的蛋白质亲和试剂是一项重要的工作。理想情况下,工程蛋白对其预期目标具有很高的特异性,但通过设计实现相互作用特异性可能具有挑战性。有两种主要的蛋白质设计或重新设计方法。最常见的方法是使用实验文库筛选和/或体外进化来设计蛋白质和肽。另一种方法涉及使用蛋白质结构和计算建模来合理选择预测具有理想特性的序列。计算设计已成功地产生了具有增强稳定性、所需相互作用和酶功能的新型蛋白质。在这里,我们回顾了实验文库筛选和基于结构的计算设计的优缺点,并给出了这些方法应用于设计蛋白质相互作用特异性的例子。我们强调了最近的研究,这些研究展示了将计算建模与文库筛选相结合的策略。计算方法提供了有针对性的文库,这些文库预计会富含具有目标特性的序列。这种集成方法代表了提高蛋白质设计效率和工程复杂功能(如相互作用特异性)的一种很有前途的方式。