Statistical and rule-based mesoscale modeling of the SARS-CoV-2 virus
Ivan Viola and his team have developed a new technique for rapid modeling and construction of scientifically accurate mesoscale biological models, which is being applied to the SARS-CoV-2 virus. The result is a 3D model based on 2D microscopy scans and the latest knowledge about the biological entity represented as a set of geometric relationships. This new technique is based on statistical and rule-based modeling approaches that are rapid to author, fast to construct, and easy to revise—techniques developed, in part, in collaboration with a team at The Scripps Research Institute for the purposes of better understanding the HIV virus. Collaborators at Nanographics GmbH created the video you see below.
From a few 2D microscopy scans, Viola’s team is able to learn the statistical properties of various structural aspects, such as outer membrane shape, spatial properties and distribution characteristics of the macromolecular elements on the membrane. This information is utilized in 3D model construction. Once all imaging evidence is incorporated in the model, additional information can be incorporated by interactively defining rules that spatially characterize the rest of the biological entity, such as mutual interactions among macromolecules, their distances and orientations to other structures. These rules are defined through an intuitive 3D interactive visualization and modeling feedback loop.
The team hopes that this 3D experience can help steer biological research to new promising directions in fighting the spread of the SARS-CoV-2 virus.