Lecture
This lecture covers the evolution of protein structure prediction techniques, focusing on AlphaFold 1 and AlphaFold 2. It explains the modules and mechanisms behind AlphaFold 1, highlighting the use of Multiple Sequence Alignment (MSA) and Distance Constraint Analysis (DCA). The lecture then delves into the advancements in AlphaFold 2, emphasizing its novel approach based on natural language processing concepts. Additionally, it discusses the democratization of AI for biology through OpenFold, providing new insights into AlphaFold2's learning mechanisms. The lecture also touches on the differences between AlphaFold and DCA, the future prospects of DCA-like methods, and the unsupervised exploration of sequence landscapes using transformers and attention mechanisms.