A novel sequence alignment algorithm based on deep learning of the protein folding code.

ABSTRACT:

Motivation

From evolutionary interference, function annotation to structural prediction, protein sequence comparison has provided crucial biological insights. While many sequence alignment algorithms have been developed, existing approaches often cannot detect hidden structural relationships in the 'twilight zone' of low sequence identity. To address this critical problem, we introduce a computational algorithm that performs protein Sequence Alignments from deep-Learning of Structural Alignments (SAdLSA, silent 'd'). The key idea is to implicitly learn the protein folding code from many thousands of structural alignments using experimentally determined protein structures.

Results

To demonstrate that the folding code was learned, we first show that SAdLSA trained on pure α-he

SUBMITTER: Gao M 

PROVIDER: S-EPMC8599902 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature