Using Coarse-Grained Simulations to Characterize the Mechanisms of Protein-Protein Association
Using Coarse-Grained Simulations to Characterize the Mechanisms of Protein-Protein Association
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DOI：
10.3390/biom10071056
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发表时间：
2020-07-01
期刊：
影响因子：
5.5
通讯作者：
Wu, Yinghao
中科院分区：
文献类型：
--
作者：
Dhusia, Kalyani;Su, Zhaoqian;Wu, Yinghao
功能多样的蛋白质复合物的形成是几乎所有生物过程的基础。估计这些复合物形成的速度对于解开生物分子识别的机制具有广泛的意义。这种动力学性质传统上通过缔合速率来量化，缔合速率可以通过各种实验技术来测量。为了补充这些耗时和劳动密集型的方法，我们开发了一种粗粒度的模拟方法来研究蛋白质-蛋白质缔合的物理过程。我们针对大规模的基准集系统地校准了我们的模拟方法。通过将基于物理的力场与模拟中的物理推导势相结合，我们发现，超过80%的蛋白质复合物的缔合率可以在相对于其实验测量的一个数量级内正确预测。我们进一步表明，来自互补源的力场的混合物能够描述蛋白质-蛋白质缔合的过程与机械细节。例如，我们发现，协会的蛋白质复合物包含多个步骤，其中蛋白质不断搜索其本地的结合方向，并通过反复的解离和重新关联形成非天然的中间体。此外，与松散结合的遭遇复杂的合奏周围观察到他们的天然构象，我们认为，蛋白质-蛋白质协会的过渡状态可能是高度多样化的结构水平。我们的研究还支持了蛋白质复合物的关联是由“漏斗状”能量景观驱动的观点。总之，这些结果阐明了我们对蛋白质-蛋白质识别如何动力学调制的理解，并且我们的粗粒度模拟方法可以作为测量蛋白质-蛋白质缔合率的现有实验方法的有用补充。
The formation of functionally versatile protein complexes underlies almost every biological process. The estimation of how fast these complexes can be formed has broad implications for unravelling the mechanism of biomolecular recognition. This kinetic property is traditionally quantified by association rates, which can be measured through various experimental techniques. To complement these time-consuming and labor-intensive approaches, we developed a coarse-grained simulation approach to study the physical processes of protein-protein association. We systematically calibrated our simulation method against a large-scale benchmark set. By combining a physics-based force field with a statistically-derived potential in the simulation, we found that the association rates of more than 80% of protein complexes can be correctly predicted within one order of magnitude relative to their experimental measurements. We further showed that a mixture of force fields derived from complementary sources was able to describe the process of protein-protein association with mechanistic details. For instance, we show that association of a protein complex contains multiple steps in which proteins continuously search their local binding orientations and form non-native-like intermediates through repeated dissociation and re-association. Moreover, with an ensemble of loosely bound encounter complexes observed around their native conformation, we suggest that the transition states of protein-protein association could be highly diverse on the structural level. Our study also supports the idea in which the association of a protein complex is driven by a "funnel-like" energy landscape. In summary, these results shed light on our understanding of how protein-protein recognition is kinetically modulated, and our coarse-grained simulation approach can serve as a useful addition to the existing experimental approaches that measure protein-protein association rates.