Protein Stability

Protein stability, crucial for protein function and numerous applications, is actively researched to improve prediction accuracy of stability changes upon mutation. Current efforts focus on developing sophisticated machine learning models, including graph neural networks and large language models, leveraging both sequence and structural information to predict stability changes, often incorporating advanced techniques like equivariant modeling and transfer learning between related protein domains. These advancements aim to enhance the precision and efficiency of protein engineering, drug design, and the understanding of disease-related mutations.