The protein folding problem, which involves understanding how a protein's amino acid sequence dictates its three-dimensional structure, has seen significant progress in recent years. The problem is now viewed as three related challenges: (a) determining the folding code, which is the balance of interatomic forces that dictate the structure; (b) predicting the native structure from the sequence; and (c) understanding the folding mechanism. Advances in computational methods and experimental techniques have enabled the design of foldable proteins and nonbiological foldamers, with successful applications in biomedicine. Computational protein structure prediction has become increasingly accurate, with methods now predicting native structures of small proteins to within 2–6 Å of experimental results. The folding code is largely determined by hydrophobic interactions, which drive the formation of the protein's core and influence its secondary and tertiary structures. Proteins fold on funnel-shaped energy landscapes, which explain the conformational heterogeneity and folding kinetics. The Zipping and Assembly (ZA) hypothesis suggests that proteins fold by solving smaller local optimization problems, assembling substructures into the native state. This mechanism allows proteins to avoid searching vast conformational spaces. Current computational algorithms can predict native structures of small proteins accurately, promising significant value in drug discovery and proteomics. The protein folding problem is no longer seen as an insurmountable challenge, with new proteins and foldamers being successfully designed. The field has benefited from advances in experimental and theoretical methods, including the CASP community-wide experiment, the Protein Data Bank, and fast-homology methods. These developments have led to a deeper understanding of the forces and dynamics governing protein properties, enabling the design of synthetic proteins with noncanonical amino acids and foldameric polymers.The protein folding problem, which involves understanding how a protein's amino acid sequence dictates its three-dimensional structure, has seen significant progress in recent years. The problem is now viewed as three related challenges: (a) determining the folding code, which is the balance of interatomic forces that dictate the structure; (b) predicting the native structure from the sequence; and (c) understanding the folding mechanism. Advances in computational methods and experimental techniques have enabled the design of foldable proteins and nonbiological foldamers, with successful applications in biomedicine. Computational protein structure prediction has become increasingly accurate, with methods now predicting native structures of small proteins to within 2–6 Å of experimental results. The folding code is largely determined by hydrophobic interactions, which drive the formation of the protein's core and influence its secondary and tertiary structures. Proteins fold on funnel-shaped energy landscapes, which explain the conformational heterogeneity and folding kinetics. The Zipping and Assembly (ZA) hypothesis suggests that proteins fold by solving smaller local optimization problems, assembling substructures into the native state. This mechanism allows proteins to avoid searching vast conformational spaces. Current computational algorithms can predict native structures of small proteins accurately, promising significant value in drug discovery and proteomics. The protein folding problem is no longer seen as an insurmountable challenge, with new proteins and foldamers being successfully designed. The field has benefited from advances in experimental and theoretical methods, including the CASP community-wide experiment, the Protein Data Bank, and fast-homology methods. These developments have led to a deeper understanding of the forces and dynamics governing protein properties, enabling the design of synthetic proteins with noncanonical amino acids and foldameric polymers.