Open-access data: A cornerstone for artificial intelligence approaches to protein structure prediction

The Protein Data Bank (PDB) was established in 1971 to archive three-dimensional (3D) structures of biological macromolecules as a public good. Fifty years later, the PDB is providing millions of data consumers around the world with open access to more than 175,000 experimentally determined structures of proteins and nucleic acids (DNA, RNA) and their complexes with one another and small-molecule ligands. PDB data users are working, teaching, and learning in fundamental biology, biomedicine, bioengineering, biotechnology, and energy sciences. They also represent the fields of agriculture, chemistry, physics and materials science, mathematics, statistics, computer science, and zoology, and even the social sciences. The enormous wealth of 3D structure data stored in the PDB has underpinned significant advances in our understanding of protein architecture, culminating in recent breakthroughs in protein structure prediction accelerated by artificial intelligence approaches and deep or machine learning methods.

Automated summary

Established in 1971, the Protein Data Bank (PDB) serves as a public good by providing open access to over 175,000 experimentally determined structures of proteins, nucleic acids, and their complexes. Users from various fields benefit from the wealth of 3D structure data stored in the PDB, which has led to significant advances in protein structure prediction using artificial intelligence and machine learning methods.