Sensitive remote homology search by local alignment of small positional embeddings from protein language models.

ABSTRACT: Accurately detecting distant evolutionary relationships between proteins remains an ongoing challenge in bioinformatics. Search methods based on primary sequence struggle to accurately detect homology between sequences with less than 20% amino acid identity. Profile- and structure-based strategies extend sensitive search capabilities into this twilight zone of sequence similarity but require slow pre-processing steps. Recently, whole-protein and positional embeddings from deep neural networks have shown promise for providing sensitive sequence comparison and annotation at long evolutionary distances. Embeddings are generally faster to compute than profiles and predicted structures but still suffer several drawbacks related to the ability of whole-protein embeddings to discriminate domain-l

SUBMITTER: Johnson SR 

PROVIDER: S-EPMC10942778 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature