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

• Published in: Structure (London) Vol. 29; no. 6; pp. 515 - 520
• Main Authors: Burley, Stephen K., Berman, Helen M.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 03.06.2021; Elsevier
• Subjects: Access to Information; Artificial Intelligence; CAMEO; CAPRI; CASP; Databases, Protein; de novo protein structure prediction; drug design data resource; FAIR principles; Humans; machine learning; open-access biodata resource; PDB50; Protein Conformation; Protein Data Bank; protein structure; Proteins - chemistry; Proteins - genetics; structural biology; structure-guided drug discovery; CASP; structure-guided drug discovery; CAPRI; drug design data resource; open-access biodata resource; FAIR principles; machine learning; PDB50; artificial intelligence; protein structure; CAMEO; de novo protein structure prediction; structural biology; Protein Data Bank
• ISSN: 0969-2126; 1878-4186; 1878-4186
• DOI: 10.1016/j.str.2021.04.010

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. [Display omitted]