Proteins evolve to highly diverged sequence, function and structure. The dynamics of protein evolution is fundamental for understanding how natural protein evolve, and also for creating new proteins in the laboratory for medical and industrial use. “Epistasis”, which is the interaction between the effects of mutations, is often observed in nature and is the central to understand the dynamics of evolution, because it shapes the passages in the evolution. However, epistasis has been considered to be a quite complicated phenomenon and difficult to predict, thus it seemed that the dynamics of protein evolution was difficult to understand. In this project, I propose a new integrated protein evolution model which describes the fitness of protein from the physico-chemical properties of proteins. In this model, the structure of the fitness cause of epistasis of the fitness even though there is no interaction between the effects of mutations in physico-chemical properties; The fitness of protein (enzymatic activity in the cell: v0) is multiplication of function (enzymatic activity: kcat/KM) and fraction of functional expression level of protein (enzyme concentration: [E]). And the fraction of functional expression level is non-linearly correlated to the stability of proteins (∆∆G) due to unfolding, aggregation, degradation of proteins. This model will provide a new insight of epistasis and enable us to predict and understand the dynamics of protein evolution. I will validate and refine the model comparing the experimental evolution experiments. Furthermore, I will apply this model to analyze mono-genetic disease related proteins to establish the way to diagnose potential patients. This integrated protein evolution model will revolutionize the way how we study the dynamics of protein evolution, innovate the methodology of directed evolution, and make significant impact on the study of the network and biological evolution.