Most proteins fold into 3D structures that determine how they function and orchestrate the
biological processes of the cell. Recent developments in computational methods for protein …

In Dec 2020, the results of AlphaFold version 2 were presented at CASP14, sparking a
revolution in the field of protein structure predictions. For the first time, a purely …

Characterizing the three-dimensional structure of macromolecules is central to
understanding their function. Traditionally, structures of proteins and their complexes have …

To the Editor—AlphaFold2 is a machine-learning algorithm for protein structure prediction
that has now been used to obtain hundreds of thousands of protein models. The resulting …

Arguably, 2020 was the year of high‐accuracy protein structure predictions, with AlphaFold
2.0 achieving previously unseen accuracy in the Critical Assessment of Protein Structure …

AlphaFold 2 (AF2) was the star of CASP14, the last biannual structure prediction experiment.
Using novel deep learning, AF2 predicted the structures of many difficult protein targets at or …

Artificial intelligence-based protein structure prediction methods such as AlphaFold have
revolutionized structural biology. The accuracies of these predictions vary, however, and …

AlphaFold2 has revolutionized protein structure prediction by leveraging sequence
information to rapidly model protein folds with atomic‐level accuracy. Nevertheless, previous …

The unprecedented performance of Deepmind's Alphafold2 in predicting protein structure in
CASP XIV and the creation of a database of structures for multiple proteomes and protein …

De novo protein design is a longstanding fundamental goal of synthetic biology, but has
been hindered by the difficulty in reliable prediction of accurate high-resolution protein …