Pre Trained Protein Model

Pre-trained protein models leverage deep learning to learn representations of protein sequences and structures, aiming to improve prediction of protein properties and functions. Current research focuses on developing models that integrate both sequence and structural information, employing techniques like graph neural networks, transformers, and diffusion models to capture complex relationships within and between proteins. These models are proving valuable for diverse applications, including drug discovery, protein engineering, and understanding protein-protein interactions, by enabling more accurate and efficient predictions than traditional methods. The ability to learn from large datasets and generalize to new proteins is a key area of ongoing development.