AlphaFold3 and Biomolecular Co-Folding

AlphaFold2 answered a question biology had chased for fifty years: given a protein sequence, what is its fold? But a folded protein alone rarely does anything. It works by binding: to a drug molecule, to a strand of DNA, to a metal ion, to another protein. AlphaFold2 could not see any of that. It spoke one language, amino acids, and everything else in the cell was invisible to it. AlphaFold3 (Abramson et al, Nature 2024) is the model that learned to fold the whole assembly at once: protein plus ligand plus nucleic acid plus ion plus post-translational modification, in a single forward pass. The jump from predicting a structure to predicting an interaction required tearing out the part of AlphaFold2 that made it protein-specific and replacing it with something that does not know or care what an amino acid is.

From a structure module to a diffusion head

AlphaFold2's structure module was built around protein geometry. It reasoned in terms of residue backbone frames and torsion angles, an inductive bias that encodes "this is a chain of amino acids with peptide bonds." That bias is exactly what you cannot afford when the same model must also place a zinc ion, a lipid, or a stretch of double-stranded DNA, none of which have residues or torsions in the protein sense.