Yan Le, Ravasio Riccardo, Brito Carolina, Wyart Matthieu
Kavli Institute for Theoretical Physics, University of California, Santa Barbara, CA 93106;
Institute of Physics, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.
Proc Natl Acad Sci U S A. 2017 Mar 7;114(10):2526-2531. doi: 10.1073/pnas.1615536114. Epub 2017 Feb 21.
We introduce a numerical scheme to evolve functional elastic materials that can accomplish a specified mechanical task. In this scheme, the number of solutions, their spatial architectures, and the correlations among them can be computed. As an example, we consider an "allosteric" task, which requires the material to respond specifically to a stimulus at a distant active site. We find that functioning materials evolve a less-constrained trumpet-shaped region connecting the stimulus and active sites, and that the amplitude of the elastic response varies nonmonotonically along the trumpet. As previously shown for some proteins, we find that correlations appearing during evolution alone are sufficient to identify key aspects of this design. Finally, we show that the success of this architecture stems from the emergence of soft edge modes recently found to appear near the surface of marginally connected materials. Overall, our in silico evolution experiment offers a window to study the relationship between structure, function, and correlations emerging during evolution.
我们引入了一种数值方案来演化能够完成特定机械任务的功能性弹性材料。在该方案中,可以计算解的数量、它们的空间结构以及它们之间的相关性。作为一个例子,我们考虑一个“变构”任务,该任务要求材料对远处活性位点处的刺激做出特异性响应。我们发现,起作用的材料会演化出一个连接刺激位点和活性位点的约束较少的喇叭形区域,并且弹性响应的幅度沿喇叭形呈非单调变化。正如之前在一些蛋白质中所显示的那样,我们发现仅在演化过程中出现的相关性就足以识别这种设计的关键方面。最后,我们表明这种结构的成功源于最近在边缘连接材料表面附近发现的软边缘模式的出现。总体而言,我们的计算机模拟演化实验为研究演化过程中出现的结构、功能和相关性之间的关系提供了一个窗口。