Abstract：

Protein-protein interactions play an important role in many aspects such as virus infection and immune response. Although there are experimental methods for determining the structure of protein complexes, the experimental methods are time-consuming and labor-intensive, and are difficult to apply in large-scale screening. This project hopes to use the method of extended natural vector to extract the information of the protein-protein binding region, combine some molecular dynamics or topology information, and then use the deep learning method to analyze the protein-protein binding free energy changes after single or multiple point mutation. Then we hope to apply the method to the SARS-CoV-2, HIV and Ebola viruses. This helps greatly improve the efficiency of the optimal design of antiviral drugs. In this report, we mainly introduce the overall ideas and data types.