Highly accurate protein structure prediction with AlphaFold

Predicting a protein’s structure from its primary sequence has been a long standing grand challenge in biology. In this talk, we will describe work at DeepMind to develop AlphaFold, a deep learning-based system for protein structure prediction that achieves high accuracy across a wide range of targets.  We demonstrated our system in the 14th biennial Critical Assessment of Protein Structure Prediction (CASP14) across a wide range of difficult targets, where the assessors judged our predictions to be at an accuracy “competitive with experiment” for approximately 2/3rds of proteins. The talk will cover both the underlying machine learning ideas and the implications for biological research as well as some promising further work.

Join on ZOOM: https://umu.zoom.us/j/66616468539