Predicting the Structural Impact of Human Alternative Splicing.

ABSTRACT: Protein structure prediction with neural networks is a powerful new method for linking protein sequence, structure, and function, but structures have generally been predicted for only a single isoform of each gene, neglecting splice variants. To investigate the structural implications of alternative splicing, we used AlphaFold2 to predict the structures of more than 11,000 human isoforms. We employed multiple metrics to identify splicing-induced structural alterations, including template matching score, secondary structure composition, surface charge distribution, radius of gyration, accessibility of post-translational modification sites, and structure-based function prediction. We identified examples of how alternative splicing induced clear changes in each of these properties. Structural

SUBMITTER: Song Y 

PROVIDER: S-EPMC10769328 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature