The latest version of AlphaFold can predict the structures of proteins, nucleic acids, and molecules containing PTM, achieving high-accuracy atomic-level predictions for ligands, proteins, and nucleic acids. It significantly surpasses earlier versions in antibody-binding-related issues and is capable of predicting protein-ligand structures more quickly and accurately, aiding in the understanding of complex biological mechanisms and accelerating medical applications.

Harvard and Columbia have released the open dataset OpenProteinSet, containing 16 million protein multiple sequence alignments and related data to support AI model training. AlphaFold 2 has achieved a milestone in the accuracy of protein structure predictions, but its proprietary data has limited progress for other researchers. OpenProteinSet includes MSAs for all proteins in the PDB, providing ample precomputed MSA resources for the protein machine learning community. This dataset can be used for various tasks in structural biology.