On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering.

ABSTRACT: Protein design and directed evolution have separately contributed enormously to protein engineering. Without being mutually exclusive, the former relies on computation from first principles, while the latter is a combinatorial approach based on chance. Advances in ultrahigh throughput (uHT) screening, next generation sequencing and machine learning may create alternative routes to engineered proteins, where functional information linked to specific sequences is interpreted and extrapolated in silico. In particular, the miniaturisation of functional tests in water-in-oil emulsion droplets with picoliter volumes and their rapid generation and analysis (>1 kHz) allows screening of >10⁷-membered libraries in a day. Subsequently, decoding the selected clones by short or long-r

SUBMITTER: Gantz M 

PROVIDER: S-EPMC11318516 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature