Trubiano Anthony, Holmes-Cerfon Miranda
Courant Institute of Mathematical Sciences, New York University, New York, New York 10012, USA.
Soft Matter. 2021 Jul 21;17(28):6797-6807. doi: 10.1039/d1sm00681a.
A challenge in designing self-assembling building blocks is to ensure the target state is both thermodynamically stable and kinetically accessible. These two objectives are known to be typically in competition, but it is not known how to simultaneously optimize them. We consider this problem through the lens of multi-objective optimization theory: we develop a genetic algorithm to compute the Pareto fronts characterizing the tradeoff between equilibrium probability and folding rate, for a model system of small polymers of colloids with tunable short-ranged interaction energies. We use a coarse-grained model for the particles' dynamics that allows us to efficiently search over parameters, for systems small enough to be enumerated. For most target states there is a tradeoff when the number of types of particles is small, with medium-weak bonds favouring fast folding, and strong bonds favouring high equilibrium probability. The tradeoff disappears when the number of particle types reaches a value m*, that is usually much less than the total number of particles. This general approach of computing Pareto fronts allows one to identify the minimum number of design parameters to avoid a thermodynamic-kinetic tradeoff. However, we argue, by contrasting our coarse-grained model's predictions with those of Brownian dynamics simulations, that particles with short-ranged isotropic interactions should generically have a tradeoff, and avoiding it in larger systems will require orientation-dependent interactions.
设计自组装构建模块面临的一个挑战是确保目标状态在热力学上稳定且在动力学上易于实现。众所周知，这两个目标通常相互竞争，但尚不清楚如何同时对它们进行优化。我们通过多目标优化理论的视角来考虑这个问题：对于具有可调短程相互作用能的胶体小聚合物模型系统，我们开发了一种遗传算法来计算表征平衡概率和折叠速率之间权衡的帕累托前沿。对于粒子动力学，我们使用一种粗粒度模型，该模型使我们能够针对足够小以至于可以枚举的系统，有效地搜索参数。当粒子类型数量较少时，对于大多数目标状态存在一种权衡，中等强度的键有利于快速折叠，而强键有利于高平衡概率。当粒子类型数量达到值(m^)时，这种权衡消失，(m^)通常远小于粒子总数。这种计算帕累托前沿的通用方法使人们能够确定避免热力学 - 动力学权衡所需的最少设计参数数量。然而，通过将我们的粗粒度模型预测与布朗动力学模拟的预测进行对比，我们认为具有短程各向同性相互作用的粒子通常应该存在权衡，并且在更大的系统中避免这种权衡将需要依赖于取向的相互作用。
