蛋白质-蛋白质碰撞动力学：带反应斑的Langevin方程方法
Dynamics of protein-protein encounter: a Langevin equation approach with reaction patches
摘要：
我们研究了蛋白质-蛋白质相遇复合物的形成与朗之万方程的方法，认为直接，空间和热力学。作为具有明显不同性质的三个模型系统，我们考虑对芽孢杆菌RNA酶：芽孢杆菌RNA酶抑制剂，细胞色素c：细胞色素c过氧化物酶和p53：MDM 2。在每种情况下，蛋白质被建模为球形颗粒，偶极球或具有一个偶极的几个小珠的集合。根据蛋白质复合物的已知实验结构，在模型蛋白质上放置球形反应斑。在计算机模拟中，通过改变盒子的大小来改变浓度。相遇被定义为反应斑的重叠，并记录相应的首次通过时间以及相遇前不成功接触的次数。我们发现，遇到频率与蛋白质浓度呈线性关系，从而证明我们的微观模型导致一个定义良好的宏观遇到率。遭遇前的不成功接触的数量随着遭遇率的增加而减少，范围从20-9000。对于所有这三个模型，遇到率在一个数量级的实验测得的关联率。静电转向增强联想高达50倍。如果扩散相遇占主导地位（p53：MDM 2）或与静电转向（barnase：barstar）同样重要，则相遇率随斑块半径的减小而减小。更详细的蛋白质形状建模将遭遇率降低5- 95%。我们的研究显示了蛋白质-蛋白质缔合的一般原则是如何被所考虑的系统的分子特征所调制的。此外，它使我们能够评估不同的粗粒化策略，为未来的大型蛋白质复合物的动力学建模。
英文摘要：
We study the formation of protein-protein encounter complexes with a Langevin equation approach that considers direct, steric and thermal forces. As three model systems with distinctly different properties we consider the pairs barnase:barstar, cytochrome c:cytochrome c peroxidase and p53:MDM2. In each case, proteins are modeled either as spherical particles, as dipolar spheres or as collection of several small beads with one dipole. Spherical reaction patches are placed on the model proteins according to the known experimental structures of the protein complexes. In the computer simulations, concentration is varied by changing box size. Encounter is defined as overlap of the reaction patches and the corresponding first passage times are recorded together with the number of unsuccessful contacts before encounter. We find that encounter frequency scales linearly with protein concentration, thus proving that our microscopic model results in a well-defined macroscopic encounter rate. The number of unsuccessful contacts before encounter decreases with increasing encounter rate and ranges from 20-9000. For all three models, encounter rates are obtained within one order of magnitude of the experimentally measured association rates. Electrostatic steering enhances association up to 50-fold. If diffusional encounter is dominant (p53:MDM2) or similarly important as electrostatic steering (barnase:barstar), then encounter rate decreases with decreasing patch radius. More detailed modeling of protein shapes decreases encounter rates by 5-95 percent. Our study shows how generic principles of protein-protein association are modulated by molecular features of the systems under consideration. Moreover it allows us to assess different coarse-graining strategies for the future modelling of the dynamics of large protein complexes.
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