AI Drug discovery

AlphaFold2 by DeepMind achieved atomic-level accuracy in protein structure prediction, solving a 50-year grand challenge in biology. Its deep learning architecture (Evoformer + structure module) predicts protein 3D structures from amino acid sequences with accuracy rivaling experimental methods. Transformed drug discovery by enabling structure-based design for previously intractable targets. 44,000+ citations, awarded the 2024 Nobel Prize in Chemistry.

Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort, the structures of around 100,000 unique proteins have been determined, but this represents a small fraction of the billions of known protein sequences. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even where no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14), demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods.