The recognition and binding of proteins through the "fly-casting" mechanism are important biological processes. In this paper, a physical model for fly-casting binding is described based on the capillarity theory for protein chains. It is found that the capture radius for the fly-casting binding process is maximized at the transition temperature at which the free energy of the monomeric extended state of the protein equals that of the folded state. The factors related to the folding barrier or binding affinity do not change the condition needed to realize the optimization for fly-casting processes. These results will aid in the comprehensive understanding of binding processes.
Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feed-forward network composed of Hodgkin-Huxley （HH） neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant Tsyn varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of Tsyn, suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks.
