In Silico Prediction of New Mutations That Can Improve the Binding Abilities Between 2019-nCoV Coronavirus and Human ACE2.

The Coronavirus Disease 2019 (COVID-19) has become an international public health emergency, posing a serious threat to human health and safety around the world. The 2019-nCoV coronavirus spike protein was confirmed to be highly susceptible to various mutations, which can trigger apparent changes of virus transmission capacity and the pathogenic mechanism. In this article, the binding interface was obtained by analyzing the interaction modes between 2019-nCoV coronavirus and the human ACE2. Based on the "SIFT server" and the "bubble" identification mechanism, 9 amino acid sites were selected as potential mutation-sites from the 2019-nCoV-S1-ACE2 binding interface. Subsequently, a total number of 171 mutant systems for 9 mutation-sites were optimized for binding-pattern comparsion analysis, and 14 mutations that may improve the binding capacity of 2019-nCoV-S1 to ACE2 were selected. The Molecular Dynamic Simulations were conducted to calculate the binding free energies of all the 14 mutant systems. Finally, we found that most of the 14 mutations on the 2019-nCoV-S1 protein could enhance the binding ability between 2019-nCoV coronavirus and human ACE2. Among which, the binding capacities for G446R, Y449R and F486Y mutations could be increased by 20 percent, and that for S494R mutant increased even by 38.98 percent. We hope this research could provide significant help for the future epidemic detection, drug and vaccine development.