https://cen.acs.org/physical-chemistry/computational-chemistry/Computational-scientists-look-lessons-learned/99/i28
QT:{{”
One computational achievement stands out from the rest—models of the virus’s proteins. In February 2020, with the virus spreading rapidly around the world, structural biologist Jason S. McLellan at the University of Texas at Austin and colleagues at the National Institutes of Health used cryo-electron microscopy (cryo-EM) to make detailed structures of SARS-CoV-2’s spike protein. The virus uses the spike protein to attach to and enter human cells. This protein is a major target for drugs and vaccines. Within weeks of McLellan’s team publishing the cryo-EM data, Rommie Amaro’s group at the University of California San Diego used those structures to create the first computer models of the protein using artificial intelligence and other computational techniques.
In the months that followed, the group used those tools to make more-highly-detailed models of the spike protein. For example, the researchers modeled what the sugars that dot the protein’s surface look like—a feature that cryo-EM can’t capture but that is important for understanding how antibodies or drugs may interact with the protein. Their simulations also showed how the protein’s shape changes to reveal its receptor-binding domain, a region that scientists want to target with therapeutics. The work won Amaro’s group a special kind of Gordon Bell Prize, one of the most prestigious awards in
supercomputing.
“}}
linkstream2 microblog 