In vivo functional phenotypes from a computational epistatic model of evolution.

ABSTRACT: Computational models of evolution are valuable for understanding the dynamics of sequence variation, to infer phylogenetic relationships or potential evolutionary pathways and for biomedical and industrial applications. Despite these benefits, few have validated their propensities to generate outputs with in vivo functionality, which would enhance their value as accurate and interpretable evolutionary algorithms. We demonstrate the power of epistasis inferred from natural protein families to evolve sequence variants in an algorithm we developed called Sequence Evolution with Epistatic Contributions. Utilizing the Hamiltonian of the joint probability of sequences in the family as fitness metric, we sampled and experimentally tested for in vivo β-lactamase activity in E. col

SUBMITTER: Alvarez S 

PROVIDER: S-EPMC10245989 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature