The virus lesson: Teaching viral structure and quasi‐symmetry in mixed reality
Year: 2026
Type: article
Abstract: Traditional approaches to teaching structural biology struggle to capture the dynamic, three-dimensional nature of biomolecular structures. Viral capsids, which employ quasi-symmetric arrangements, are especially difficult to conceptualize at the human scale. While physical models can illustrate geometry, they are costly, static, and disconnected from the digital domain. Recent advances in mixed reality (MR) offer an opportunity to overcome these limitations by combining immersion, interactivity, and collaboration. We present Virus Lesson, an MR application designed to teach viral quasi-symmetry through shared immersive experiences. Developed in Unity and optimized for standalone MR headsets such as the Meta Quest 3/3S, the platform integrates multiplayer networking to allow students and instructors to co-localize in the same virtual classroom. Activities include interactive exploration of virus size and composition, dissection of capsids to reveal encapsidated RNA, construction of quasi-symmetric shells using Caspar-Klug triangulation theory, and antibody-antigen recognition tasks. Educational design elements such as spatially separated "learning stations," memory palace techniques, and scaffolded problem-solving guide learners through increasingly complex concepts. Pilot demos with participants of all ages showed high engagement, improved comprehension of virus structure, quasi-symmetry, and immunological interactions, and strong appreciation of collaborative learning in MR. The Virus Lesson demonstrates that MR can enhance understanding of challenging structural biology concepts while providing a scalable framework for interactive, human-scale education in biomolecular sciences.
Source: Protein Science
DOI: 10.1002/pro.70570
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
Estimated APC paid: $4,480
Funder: National Institutes of Health
OpenAlex ID: W7154011058
