Arnold Sommerfeld Center for Theoretical Physics (ASC) and Center for NanoScience (CeNS), Department of Physics, Ludwig-Maximilians-Universität München, München, Germany.
Elife. 2020 Feb 5;9:e51020. doi: 10.7554/eLife.51020.
A guiding principle in self-assembly is that, for high production yield, nucleation of structures must be significantly slower than their growth. However, details of the mechanism that impedes nucleation are broadly considered irrelevant. Here, we analyze self-assembly into finite-sized target structures employing mathematical modeling. We investigate two key scenarios to delay nucleation: (i) by introducing a slow activation step for the assembling constituents and, (ii) by decreasing the dimerization rate. These scenarios have widely different characteristics. While the dimerization scenario exhibits robust behavior, the activation scenario is highly sensitive to demographic fluctuations. These demographic fluctuations ultimately disfavor growth compared to nucleation and can suppress yield completely. The occurrence of this stochastic yield catastrophe does not depend on model details but is generic as soon as number fluctuations between constituents are taken into account. On a broader perspective, our results reveal that stochasticity is an important limiting factor for self-assembly and that the specific implementation of the nucleation process plays a significant role in determining the yield.
自组装的一个指导原则是，为了获得高产率，结构的成核必须明显慢于其生长。然而，阻碍成核的机制细节通常被认为是不相关的。在这里，我们使用数学建模来分析有限尺寸目标结构的自组装。我们研究了两种延迟成核的关键情况：（i）引入组装成分的缓慢激活步骤，以及（ii）降低二聚化速率。这两种情况具有广泛不同的特征。虽然二聚化方案表现出稳健的行为，但激活方案对人口统计波动非常敏感。与成核相比，这些人口统计波动最终不利于生长，并且可以完全抑制产率。这种随机产率灾难的发生不依赖于模型细节，而是只要考虑到成分之间的数量波动，就具有普遍性。从更广泛的角度来看，我们的结果表明，随机性是自组装的一个重要限制因素，而成核过程的具体实现对确定产率起着重要作用。
