Artificial intelligence-driven advances in protein structure prediction in recent years have
raised the question: has the protein structure-prediction problem been solved? Here, with a …

AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of
biological sequence data and artificial intelligence (AI). AlphaFold has appended projects …

AlphaFold2 and related computational systems predict protein structure using deep learning
and co-evolutionary relationships encoded in multiple sequence alignments (MSAs) …

Highly accurate protein structure predictions by deep neural networks such as AlphaFold2
and RoseTTAFold have tremendous impact on structural biology and beyond. Here, we …

Recent work suggests that AlphaFold (AF)–a deep learning-based model that can
accurately infer protein structure from sequence–may discern important features of folded …

The greatly improved prediction of protein 3D structure from sequence achieved by the
second version of AlphaFold in 2020 has already had a huge impact on biological research …

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 …

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

Antibodies are versatile molecular binders with an established and growing role as
therapeutics. Computational approaches to develo** and designing these molecules are …

Recognition of remote homologous structures is a necessary module in AlphaFold2 and is
also essential for the exploration of protein folding pathways. Here, we propose a method …