Predicting the structural impact of human alternative splicing.

ABSTRACT:

Background

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 use AlphaFold2 to predict the structures of more than 11,000 human isoforms. We employ 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.

Results

We identify examples of how alternative splicing induces clear changes in each of

SUBMITTER: Song Y 

PROVIDER: S-EPMC12442299 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature