From the International Joint Cancer Institute and 301 General Hospital Cancer Center, Second Military Medical University, Shanghai 200433; the National Engineering Research Center for Antibody Medicine and Shanghai Key Laboratory of Cell Engineering & Antibody, Shanghai 201203, and.
From the International Joint Cancer Institute and 301 General Hospital Cancer Center, Second Military Medical University, Shanghai 200433.
J Biol Chem. 2010 Feb 5;285(6):3865-3871. doi: 10.1074/jbc.M109.076547. Epub 2009 Dec 10.
Understanding the evolutionary mechanism that acts at the interfaces of protein-protein complexes is a fundamental issue with high interest for delineating the macromolecular complexes and networks responsible for regulation and complexity in biological systems. To investigate whether the evolution of protein-protein interface acts in a similar way as antibody affinity maturation, we incorporated evolutionary information derived from antibody affinity maturation with common simulation techniques to evaluate prediction success rates of the computational method in affinity improvement in four different systems: antibody-receptor, antibody-peptide, receptor-membrane ligand, and receptor-soluble ligand. It was interesting to find that the same evolutionary information could improve the prediction success rates in all the four protein-protein complexes with an exceptional high accuracy (>57%). One of the most striking findings in our present study is that not only in the antibody-combining site but in other protein-protein interfaces almost all of the affinity-enhancing mutations are located at the germline hotspot sequences (RGYW or WA), indicating that DNA hot spot mechanisms may be widely used in the evolution of protein-protein interfaces. Our data suggest that the evolution of distinct protein-protein interfaces may use the same basic strategy under selection pressure to maintain interactions. Additionally, our data indicate that classical simulation techniques incorporating the evolutionary information derived from in vivo antibody affinity maturation can be utilized as a powerful tool to improve the binding affinity of protein-protein complex with a high accuracy.
了解在蛋白质-蛋白质复合物界面起作用的进化机制是一个具有高度兴趣的基本问题,有助于描绘负责生物系统调控和复杂性的大分子复合物和网络。为了研究蛋白质-蛋白质界面的进化是否以类似于抗体亲和力成熟的方式起作用,我们将源自抗体亲和力成熟的进化信息与常见的模拟技术相结合,以评估计算方法在四个不同系统(抗体-受体、抗体-肽、受体-膜配体和受体-可溶性配体)中提高亲和力的预测成功率。有趣的是,发现相同的进化信息可以提高所有四个蛋白质-蛋白质复合物的预测成功率,准确率异常高(>57%)。我们目前研究中的一个最引人注目的发现是,不仅在抗体结合位点,而且在其他蛋白质-蛋白质界面中,几乎所有增强亲和力的突变都位于原始热点序列(RGYW 或 WA)上,这表明 DNA 热点机制可能广泛用于蛋白质-蛋白质界面的进化。我们的数据表明,不同蛋白质-蛋白质界面的进化可能在选择压力下使用相同的基本策略来维持相互作用。此外,我们的数据表明,将源自体内抗体亲和力成熟的进化信息与经典模拟技术相结合,可以用作提高蛋白质-蛋白质复合物结合亲和力的强大工具,具有很高的准确性。