Persistent homology is a concept in topological data analysis used to reduce the dimensionality and complexity of the data sets, and also to determine topological features and delete noises. In this talk, unfolding process is simulated with the constant velocity pulling algorithm of SMD. Then, we apply the persistent homology to reveal the topological features of intermediate configurations. Furthermore, we construct a quantitative model based on the accumulation bar length A1 to predict the energy and stability of protein configurations, which establishes a solid topology-function relationship of proteins with the constant velocity pulling algorithm of SMD.

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