Deep representation learning improves prediction of LacI-mediated transcriptional repression.

ABSTRACT: Recent progress in DNA synthesis and sequencing technology has enabled systematic studies of protein function at a massive scale. We explore a deep mutational scanning study that measured the transcriptional repression function of 43,669 variants of the Escherichia coli LacI protein. We analyze structural and evolutionary aspects that relate to how the function of this protein is maintained, including an in-depth look at the C-terminal domain. We develop a deep neural network to predict transcriptional repression mediated by the lac repressor of Escherichia coli using experimental measurements of variant function. When measured across 10 separate training and validation splits using 5,009 single mutations of the lac repressor, our best-performing model achieved a median Pears

SUBMITTER: Garruss AS 

PROVIDER: S-EPMC8271634 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature