Vangone Anna, Bonvin Alexandre M J J
Computational Structural Biology group, Bijvoet Center for Biomolecular Research, Faculty of Science Chemistry, Utrecht University, Utrecht, the Netherlands.
Bio Protoc. 2017 Feb 5;7(3):e2124. doi: 10.21769/BioProtoc.2124.
Biomolecular interactions between proteins regulate and control almost every biological process in the cell. Understanding these interactions is therefore a crucial step in the investigation of biological systems and in drug design. Many efforts have been devoted to unraveling principles of protein-protein interactions. Recently, we introduced a simple but robust descriptor of binding affinity based only on structural properties of a protein-protein complex. In Vangone and Bonvin (2015), we demonstrated that the number of interfacial contacts at the interface of a protein-protein complex correlates with the experimental binding affinity. Our findings have led one of the best performing predictor so far reported (Pearson's Correlation r = 0.73; RMSE = 1.89 kcal mol). Despite the importance of the topic, there is surprisingly only a limited number of online tools for fast and easy prediction of binding affinity. For this reason, we implemented our predictor into the user-friendly PRODIGY web-server. In this protocol, we explain the use of the PRODIGY web-server to predict the affinity of a protein-protein complex from its three-dimensional structure. The PRODIGY server is freely available at: http://milou.science.uu.nl/services/PRODIGY.
蛋白质之间的生物分子相互作用调节和控制着细胞内几乎所有的生物过程。因此，了解这些相互作用是研究生物系统和药物设计的关键步骤。人们已经付出了很多努力来揭示蛋白质-蛋白质相互作用的原理。最近，我们仅基于蛋白质-蛋白质复合物的结构特性，引入了一种简单而可靠的结合亲和力描述符。在万戈内和邦文（2015年）的研究中，我们证明了蛋白质-蛋白质复合物界面处的界面接触数量与实验结合亲和力相关。我们的研究结果产生了迄今为止报道的性能最佳的预测器之一（皮尔逊相关系数r = 0.73；均方根误差 = 1.89千卡/摩尔）。尽管这个主题很重要，但令人惊讶的是，用于快速、轻松预测结合亲和力的在线工具数量有限。出于这个原因，我们将我们的预测器集成到了用户友好的PRODIGY网络服务器中。在本方案中，我们解释了如何使用PRODIGY网络服务器根据蛋白质-蛋白质复合物的三维结构预测其亲和力。PRODIGY服务器可免费获取，网址为：http://milou.science.uu.nl/services/PRODIGY 。
