Department of Mathematics and Computer Science, Freie Universität Berlin, Arnimallee 6, 14195 Berlin, Germany.
Computational Biophysics Laboratory (GRIB-IMIM), Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), C/ Doctor Aiguader 88, 08003 Barcelona, Spain.
Nat Chem. 2017 Oct;9(10):1005-1011. doi: 10.1038/nchem.2785. Epub 2017 Jun 5.
Protein-protein association is fundamental to many life processes. However, a microscopic model describing the structures and kinetics during association and dissociation is lacking on account of the long lifetimes of associated states, which have prevented efficient sampling by direct molecular dynamics (MD) simulations. Here we demonstrate protein-protein association and dissociation in atomistic resolution for the ribonuclease barnase and its inhibitor barstar by combining adaptive high-throughput MD simulations and hidden Markov modelling. The model reveals experimentally consistent intermediate structures, energetics and kinetics on timescales from microseconds to hours. A variety of flexibly attached intermediates and misbound states funnel down to a transition state and a native basin consisting of the loosely bound near-native state and the tightly bound crystallographic state. These results offer a deeper level of insight into macromolecular recognition and our approach opens the door for understanding and manipulating a wide range of macromolecular association processes.
蛋白质-蛋白质相互作用是许多生命过程的基础。然而,由于结合状态的寿命很长,直接分子动力学 (MD) 模拟无法有效地进行采样,因此缺乏描述结合和解离过程中结构和动力学的微观模型。在这里,我们通过结合自适应高通量 MD 模拟和隐马尔可夫模型,以原子分辨率展示了核糖核酸酶 barnase 与其抑制剂 barstar 的蛋白质-蛋白质相互作用和解离。该模型揭示了实验上一致的中间结构、能量和动力学,时间尺度从微秒到小时不等。各种灵活附着的中间体和错误结合的状态都通向一个过渡态和一个由松散结合的近天然状态和紧密结合的晶体状态组成的天然盆地。这些结果提供了对大分子识别的更深入的了解,我们的方法为理解和操纵广泛的大分子结合过程打开了大门。