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This website tracks recent publications on the development of AlphaFold - the AI system developed by DeepMind to predict 3D protein structure from an amino acid sequence - and its applications. Further, the Examples page offers several interactive comparisons between experimentally-determined structures and AlphaFold 2 predictions.

Recent Publications

bioRxiv, 2021

Evans et al.

Protein complex prediction with AlphaFold-Multimer. "In this work, we demonstrate that an AlphaFold model trained specifically for multimeric inputs of known stoichiometry, which we call AlphaFold-Multimer, significantly increases accuracy of predicted multimeric interfaces over input-adapted single-chain AlphaFold while maintaining high intra-chain accuracy."
bioRxiv, 2021

Akdel et al.

A structural biology community assessment of AlphaFold 2 applications. "Here, we evaluate the use of AlphaFold 2 (AF2) predictions in the study of characteristic structural elements; the impact of missense variants; function and ligand binding site predictions; modelling of interactions; and modelling of experimental structural data."
bioRxiv, 2021

Mosalaganti et al.

Artificial intelligence reveals nuclear pore complexity. "We combined AI-based structure prediction with in situ and in cellulo cryo-electron tomography and integrative modeling. We show that linker Nups spatially organize the scaffold within and across subcomplexes to establish the higher-order structure. Our work exemplifies how AI-based modeling can be integrated with in situ structural biology to understand subcellular architecture across spatial organization levels."
Nature, 2021

Jumper et al.

Highly accurate protein structure prediction with AlphaFold. "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. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm."