Xu Yongtao, Zhou Xu, Huang Meilan
School of Chemistry and Chemical Engineering, Queen's University Belfast, David Keir Building, Stranmillis Road, Belfast, Northern Ireland, United Kingdom.
PLoS One. 2015 Mar 25;10(3):e0119417. doi: 10.1371/journal.pone.0119417. eCollection 2015.
Repeat proteins have become increasingly important due to their capability to bind to almost any proteins and the potential as alternative therapy to monoclonal antibodies. In the past decade repeat proteins have been designed to mediate specific protein-protein interactions. The tetratricopeptide and ankyrin repeat proteins are two classes of helical repeat proteins that form different binding pockets to accommodate various partners. It is important to understand the factors that define folding and stability of repeat proteins in order to prioritize the most stable designed repeat proteins to further explore their potential binding affinities. Here we developed distance-dependant statistical potentials using two classes of alpha-helical repeat proteins, tetratricopeptide and ankyrin repeat proteins respectively, and evaluated their efficiency in predicting the stability of repeat proteins. We demonstrated that the repeat-specific statistical potentials based on these two classes of repeat proteins showed paramount accuracy compared with non-specific statistical potentials in: 1) discriminate correct vs. incorrect models 2) rank the stability of designed repeat proteins. In particular, the statistical scores correlate closely with the equilibrium unfolding free energies of repeat proteins and therefore would serve as a novel tool in quickly prioritizing the designed repeat proteins with high stability. StaRProtein web server was developed for predicting the stability of repeat proteins.
重复蛋白因其能够与几乎任何蛋白质结合以及作为单克隆抗体替代疗法的潜力而变得越来越重要。在过去十年中，重复蛋白已被设计用于介导特定的蛋白质-蛋白质相互作用。四肽重复蛋白和锚蛋白重复蛋白是两类螺旋重复蛋白，它们形成不同的结合口袋以容纳各种配体。了解决定重复蛋白折叠和稳定性的因素对于优先选择最稳定的设计重复蛋白以进一步探索其潜在结合亲和力非常重要。在这里，我们分别使用两类α-螺旋重复蛋白，即四肽重复蛋白和锚蛋白重复蛋白，开发了距离依赖性统计势，并评估了它们在预测重复蛋白稳定性方面的效率。我们证明，基于这两类重复蛋白的重复特异性统计势在以下方面与非特异性统计势相比显示出极高的准确性：1）区分正确与错误模型；2）对设计的重复蛋白的稳定性进行排名。特别是，统计分数与重复蛋白的平衡解折叠自由能密切相关，因此将作为一种新工具，用于快速筛选出具有高稳定性的设计重复蛋白。我们开发了StaRProtein网络服务器来预测重复蛋白的稳定性。
