Protein structure prediction by AlphaFold2: are attention and symmetries all you need?

ABSTRACT: The functions of most proteins result from their 3D structures, but determining their structures experimentally remains a challenge, despite steady advances in crystallography, NMR and single-particle cryoEM. Computationally predicting the structure of a protein from its primary sequence has long been a grand challenge in bioinformatics, intimately connected with understanding protein chemistry and dynamics. Recent advances in deep learning, combined with the availability of genomic data for inferring co-evolutionary patterns, provide a new approach to protein structure prediction that is complementary to longstanding physics-based approaches. The outstanding performance of AlphaFold2 in the recent Critical Assessment of protein Structure Prediction (CASP14) experiment demonstrates the rem

SUBMITTER: Bouatta N 

PROVIDER: S-EPMC8329862 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature