Pioneering multiscale model allows researchers to plug in and better understand information as new discoveries are made.
Researchers at the University of Chicago have created the first usable computational model of the entire virus responsible for COVID-19—and they are making this model widely available to help advance research during the pandemic.
“If you can understand how a virus works, that’s the first step towards stopping it,” said Prof. Gregory Voth, whose team created the model published in Biophysical Journal. “Each thing you know about the virus’s life cycle and composition is a vulnerability point where you can hit it.”
Voth and his team drew on their previous experience to find the most important characteristics of each individual component of the virus, and drop the “less important” information to make a computational model that is comprehensive but still feasible to run on a computer. This technique is called coarse-graining, which Voth and his students have helped to pioneer.
The simplified framework helps address a key issue in health research: Even though a virus is one of the simpler biological entities, computational modeling is still a major challenge—especially if you want to model any of a virus’s interactions with its host’s body, which would mean representing billions of atoms.
“You could try running an atom-level model of the actual entire virus, but computationally it would bog you down immediately,” Voth said. “You might be able to manage it long enough to model, say, a few hundred nanoseconds worth of movement, but that’s not really long enough to find out the most useful information.”
Thus, many researchers have focused on creating models of individual proteins of the virus. But Voth said that while this segmented process has its uses, it also misses part of the larger picture.