Protein Engineering

Protein engineering aims to design and optimize proteins with desired properties and functions, often leveraging machine learning to navigate the vast sequence space. Current research heavily utilizes large language models (LLMs), often incorporating multi-modal approaches that integrate protein sequences with textual descriptions or structural information, alongside other techniques like Bayesian optimization and evolutionary algorithms. These advancements are improving the efficiency and accuracy of protein design, with applications ranging from drug discovery and enzyme engineering to the creation of novel biomaterials. The field is also actively addressing challenges in accurately predicting the effects of mutations on protein stability and function, striving for improved model interpretability and generalizability.