Department of Physics and Astronomy, Rutgers University, Piscataway, New Jersey 08854, USA.
Phys Rev Lett. 2013 Aug 23;111(8):088102. doi: 10.1103/PhysRevLett.111.088102. Epub 2013 Aug 22.
We develop a path-based approach to continuous-time random walks on networks with arbitrarily weighted edges. We describe an efficient numerical algorithm for calculating statistical properties of the stochastic path ensemble. After demonstrating our approach on two reaction rate problems, we present a biophysical model that describes how proteins evolve new functions while maintaining thermodynamic stability. We use our methodology to characterize dynamics of evolutionary adaptation, reproducing several key features observed in directed evolution experiments. We find that proteins generally fall into two qualitatively different regimes of adaptation depending on their binding and folding energetics.
我们开发了一种针对具有任意加权边的网络上的连续时间随机行走的基于路径的方法。我们描述了一种用于计算随机路径集合的统计性质的有效数值算法。在两个反应速率问题上展示了我们的方法之后，我们提出了一个生物物理模型，该模型描述了蛋白质如何在保持热力学稳定性的同时发展新功能。我们使用我们的方法来描述进化适应的动态，再现了定向进化实验中观察到的几个关键特征。我们发现，根据它们的结合和折叠能，蛋白质通常分为两种不同的适应定性状态。
