Topological learning prediction of virus-like particle stoichiometry and stability.

Abstract excerpt

Understanding the stoichiometry and associated stability of virus-like particles (VLPs) is crucial for optimizing their assembly efficiency and immunogenic properties, which are essential for advancing biotechnology, vaccine design, and drug delivery. However, current experimental methods for determining VLP stoichiometry are labor intensive and time-consuming. Machine learning approaches have hardly been applied...

Topics

• Machine Learning
• Virion
• Protein Stability
• Mutation