Abstract: To solve the problem of how to screen out more effective antiviral compounds, the relationship between dissociation rate (k_off) and antiviral drug structure was studied in this research. The theoretical basis is that k_off is often used to evaluate the activity of the drug in the open system of the human body. The molecular descriptor of each antiviral compound was calculated by using molecular descriptor software, and the descriptors were screened by multiple stepwise regression analysis, partial least squares method and genetic algorithm. Then, the support vector machine (SVM) and BP neural network were used to establish the prediction model of antiviral compound structure and dissociation rate k_off value, and the model was verified. Results show that this experiment screens out the descriptors with good predictive power, and the two predictive models are proved to be reasonable and have guiding significance for the future development of antiviral drugs.