Schreck John S, Bridstrup John, Yuan Jian-Min
National Center for Atmospheric Research, Boulder, Colorado 80305, United States.
Department of Chemistry, Drexel University, Philadelphia, Pennsylvania 19104, United States.
J Phys Chem B. 2020 Nov 5;124(44):9829-9839. doi: 10.1021/acs.jpcb.0c07175. Epub 2020 Oct 26.
The thermodynamics and kinetics of protein folding and protein aggregation are of great importance in numerous scientific areas including fundamental biophysics research, nanotechnology, and medicine. However, these processes remain poorly understood in both and systems. Here we extend an established model for protein aggregation that is based on the kinetic equations for the moments of the polymer size distribution by introducing macromolecular crowding particles into the model using scaled-particle and transition-state theories. The model predicts that the presence of crowders can either speed up, cause no change to, or slow down the progress of the aggregation compared to crowder-free solutions, in striking agreement with experimental results from nine different amyloid-forming proteins that utilized dextran as the crowder. These different dynamic effects of macromolecular crowding can be understood in terms of the change of excluded volume associated with each reaction step.
蛋白质折叠和蛋白质聚集的热力学与动力学在众多科学领域中都极为重要，这些领域包括基础生物物理学研究、纳米技术和医学。然而，在体外和体内系统中，这些过程仍未被充分理解。在此，我们通过运用定标粒子理论和过渡态理论，将大分子拥挤颗粒引入到基于聚合物尺寸分布矩动力学方程的已建立的蛋白质聚集模型中，从而对该模型进行了扩展。该模型预测，与无拥挤剂的溶液相比，拥挤剂的存在可能会加速、不改变或减缓聚集进程，这与九种不同的以葡聚糖作为拥挤剂的淀粉样蛋白形成蛋白的实验结果惊人地一致。大分子拥挤的这些不同动态效应可以根据每个反应步骤相关的排阻体积变化来理解。
