Protein structure prediction involves computational methods to determine the three-dimensional shape of a protein from its amino acid sequence, which is crucial for understanding its function and interaction with other molecules. Advances in machine learning, particularly deep learning, have significantly improved the accuracy of these predictions, exemplified by breakthroughs like AlphaFold.