HT3: Databases
L3 (Lecture): AlphaFold DB – Accessing a wealth of predicted protein structure data
David Armstrong
Protein Data Bank in Europe (PDBe)
European Bioinformatics Institute (EMBL-EBI)
E-mail: davida@ebi.ac.uk
Predicting the 3D structure of proteins is one of the fundamental grand challenges in biology. By solving this challenge, we can dramatically deepen our understanding of human health, disease, and our environment, especially within areas like drug design and sustainability.
AlphaFold, the state-of-the-art AI system developed by DeepMind, is able to computationally predict protein structures with unprecedented accuracy and speed. The AlphaFold Protein Structure Database (AlphaFold DB), a collaboration between DeepMind and EMBL-EBI, enables free and open access to over 200 million protein structure predictions by AlphaFold. Included are nearly all cataloged proteins known to science – with the potential to increase humanity’s understanding of biology by orders of magnitude.
Explore stories of AlphaFold’s impact: unfolded.deepmind.com/
This talk will cover the background of AlphaFold DB, how to access the predicted structures, and how to interpret the data. Using some specific case studies, the talk will highlight how we can use this data to generate new hypotheses for testing to accelerate the progress of scientific research.