Cooperative Function with Thermal Fluctuations in Mechanical Networks

Elastic networks can be tuned to exhibit complex mechanical responses and have been extensively used to study protein allosteric functionality, where a localized strain regulates the conformation at a distant site. We show that cooperative binding, where two sites each enhance the other's ability to function, can be trained via a symmetric application of the training previously employed for creating network allostery. We identify a crossover temperature above which cooperative functionality breaks down due to thermal fluctuations. We develop a modified training protocol to increase this crossover temperature, enabling function to remain robust at biologically relevant temperatures.