Architecture and coevolution of allosteric materials
By Le Yan, Riccardo Ravasio, Carolina Brito, Matthieu Wyart. 2016
123 citations recorded by the source corpus.
Significance In allosteric proteins, binding a ligand affects activity at a distant site. The physical principles allowing for such an action at a distance are not well understood. Here we introduce a numerical scheme to evolve allosteric materials in which the number of solutions, their spatial architectures, and the correlations among them can be computed. We show that allostery in these materials uses recently discovered elastic edge modes near the active site to transmit information, and that correlations generated during evolution alone can reveal key aspects of this architecture. 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.
Subfields: Biomedical Engineering, Materials Chemistry, Statistical and Nonlinear Physics
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In Biomedical Engineering
In Materials Chemistry
- Nidhi Pashine
- Carl P. Goodrich
- Irmgard Bischofberger
- Jason W. Rocks
- Sidney R. Nagel
- Andrea J. Liu
- Srikanth Sastry
- Anne-Florence Bitbol
In Statistical and Nonlinear Physics
Citations in the corpus
- Memory formation in matter (2018, background): “Rigid disordered materials can become auxetic (i.e., have a negative Poisson’s ratio), or even develop a coordinated response at one location due to a stress applied elsewhere, when certain bonds are cut (Goodrich et al., 2015; Hexner et al., 2018a,b; Rocks et al., 2017, 2019; Yan et al., 2017).”
- Designing allostery-inspired response in mechanical networks (2016, background): “(31) present a different computational algorithm for tuning mechanical networks to generate an allosteric response.”
- Direct coupling analysis of epistasis in allosteric materials (2018, unknown): “We follow the scheme of [29, 30] where a protein is described by an elastic network of size L made of harmonic springs of unit stiffness (here we consider L = 12).”
- Inferring interaction partners from protein sequences using mutual information (2018, background): “However, correlations in protein sequences also have 23 important collective modes [18, 19], which can arise from functional selection [20, 21], and addi- 24 tional correlations are due to phylogeny [18, 22, 23].”