Computational Design of Functional Amyloid Materials with Cesium Binding, Deposition, and Capture Properties.

Amyloid materials are gaining increasing attention as promising materials for applications in numerous fields. Computational methods have been successfully implemented to investigate the structures of short amyloid-forming peptides, yet their application in the design of functional amyloid materials is still elusive. Here, we developed a computational protocol for the design of functional amyloid materials capable of binding to an ion of interest. We applied the protocol in a test case involving the design of amyloid materials with cesium ion deposition and capture properties. As part of the protocol, we used an optimization-based design model to introduce mutations at non-β-sheet residue positions of an amyloid designable scaffold. The designed amino acids introduced to the scaffold mimic how amino acids bind to cesium ions according to experimentally resolved structures and also aim at energetically stabilizing the bound conformation of the pockets. The optimum designs were computationally validated using a series of simulations and structural analysis to select the top designed peptides, which are predicted to form fibrils with cesium ion binding properties for experimental testing. Experiments verified the amyloid-forming properties of the selected top designed peptides, as well as the cesium ion deposition and capture properties by the amyloid materials formed. This study demonstrates the first, to the best of our knowledge, computational design protocol to functionalize amyloid materials for ion binding properties and suggests that its further advancement can lead to novel, highly promising functional amyloid materials of the future.