Searching for protein variants with desired properties using deep generative models.

ABSTRACT:

Background

Protein engineering aims to improve the functional properties of existing proteins to meet people's needs. Current deep learning-based models have captured evolutionary, functional, and biochemical features contained in amino acid sequences. However, the existing generative models need to be improved when capturing the relationship between amino acid sites on longer sequences. At the same time, the distribution of protein sequences in the homologous family has a specific positional relationship in the latent space. We want to use this relationship to search for new variants directly from the vicinity of better-performing varieties.

Results

To improve the representation learning ability of the model for longer sequences and the similarity between the generated sequ

SUBMITTER: Li Y 

PROVIDER: S-EPMC10362698 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature