Hopfield-Ninio 动力学校正模型的随机化版本

In this paper we study a simple stochastic version of the Hopfield-Ninio kinetic proofreading model。The model is characterized by means of two parameters, the unbinding time, which depends on the binding energy between a ligand and a receptor, and the number of times $M \geq 1$ that a ligand attaches to a receptor。We prove that, under suitable assumptions on M, our model has an extreme specificity, i.e. it is capable to discriminate between different ligands, and a high sensitivity, i.e. the response of the system does not change in a significant manner for ranges of ligands varying within several orders of magnitude。Additional quantities like the amount of energy used by the network or the time required to yield a response will be also computed。We also show that our results are robust, i.e., they do not depend on the specific choice of parameters that we make in this paper。