AI and Machine Learning in Protein Design

This chapter explores the intersection of artificial intelligence and machine learning in the design of human antibodies, highlighting the challenges of effective AI-driven approaches. It delves into critical aspects such as target selection and the role of epitope specificity in drug development, while also addressing limitations in current data sources. The discussion emphasizes recent advancements, including the use of sequence large language models, and the ongoing complexities in achieving high-affinity and effective therapeutic proteins.