1. How can computational techniques allow to study the effects of mutations of SARS-CoV-2 ?
Computational methods allow us to describe molecular interactions at a space and time resolution that is often unattainable experimentally. This means that we can zoom in at an atomic level to understand visualize, rationalize, and predict what the effect of mutations of SARS-CoV-2 may be. Using statistical mechanical methods, we can, for instance, quantify the relative binding affinity of a mutated Spike protein against the ACE2 receptor. This will give insight into the mechanisms by which mutations change the behavior of SARS-CoV-2.
2. What is so special about the coronavirus ?
For us, as computational chemists, it is amazing how quickly there were high-quality structures available. We were able to complement these with the appropriate glycosylation and then to use them in molecular simulations.
3. How can the interaction between SARS-CoV-2 and its cellular receptor ACE2 be described ?
This is a highly complex interaction. First, it seems that glycosylation on both the viral Spike protein and on ACE2 affect the interactions. Some glycans directly strengthen the interactions, while some glycans on ACE2 rather seem to hamper an even more efficient binding. By using molecular simulations, the structure and the dynamics of the interactions can be described at an atomic resolution.