How deep can we decipher protein evolution with deep learning models.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 39233697.
- Also identified by DOI 10.1016/j.patter.2024.101043 and PMC identifier 11368669.
- Licence recorded as CC BY-NC-ND.
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Abstract
Evolutionary-based machine learning models have emerged as a fascinating approach to mapping the landscape for protein evolution. Lian et al. demonstrated that evolution-based deep generative models, specifically variational autoencoders, can organize SH3 homologs in a hierarchical latent space, effectively distinguishing the specific Sho1<sup>SH3</sup> domains.