Abstract
As a DNA binding transcriptional activator, Gal4 promotes the expression of genes responsible for galactose metabolism. The Gal4 protein from Saccharomyces cerevisiae (baker’s yeast) has become a model for studying eukaryotic transcriptional activation in general because its regulatory properties mirror those of several eukaryotic organisms, including mammals. Given the availability of a crystallographic structure for Gal4, here we implement an in silico mutagenesis technique that makes use of a four-body knowledge-based energy function, in order to empirically quantify the structural impacts associated with single residue substitutions on the Gal4 protein. These results were used to examine the structure-function relationship in Gal4 based on a recently published experimental mutagenesis study, whereby functional changes to a uniformly distributed set of 1,068 single residue Gal4 variants were obtained by measuring their transcriptional activation levels relative to wild-type. A significant correlation was observed between computed (scalar) structural effect data and measured activity values for this collection of single residue Gal4 variants. Additionally, attribute vectors quantifying position-specific environmental impacts were generated for each of the Gal4 variants via computational mutagenesis, and we implemented supervised classification and regression statistical machine learning algorithms to train predictive models of variant Gal4 activity based on these structural changes. All models performed well under cross-validation testing, with balanced accuracy reaching 91% among the classification models, and with the actual and predicted activity values displaying a correlation as high as r = 0.80 for the regression models. Reliable predictions of transcriptional activation levels for Gal4 variants that have yet to be studied can be instantly generated by submitting their respective structure-based feature vectors to the trained models for testing. Such a computational pre-screening of Gal4 variants may potentially reduce costs associated with running large-scale mutagenesis experiments.
Highlights
Galactose utilization by Saccharomyces cerevisiae requires the orchestrated collaboration of GAL gene products for its transport into the cell and subsequent metabolism via glycolysis (Johnston, 1987)
Observations presented are based on the analyses of data obtained from the structural tessellation of a single chain of the Gal4 protein (PDB accession code 3coq, chain A), followed by a similar investigation based on the tessellation of a biologically functional Gal4 homodimeric structure (3coq, chains A and B)
Residual scores were calculated for the 1,084 Gal4 variants with experimentally determined function, and these scores were averaged over all variants in each of the three activity categories described in the Introduction (Fig. 3, black bars)
Summary
Galactose utilization by Saccharomyces cerevisiae (baker’s yeast) requires the orchestrated collaboration of GAL gene products for its transport into the cell and subsequent metabolism via glycolysis (Johnston, 1987). GAL2, GAL7, and GAL10) and regulatory (GAL3, GAL4, and GAL80) genes, with the GAL4 protein serving as a transcriptional activator for the structural genes which binds upstream activating sequences (UASGAL) located in their promoters (Lohr, Venkov & Zlatanova, 1995; Traven, Jelicic & Sopta, 2006). The availability of galactose converts the Gal protein to a transducer form which competitively binds Gal (Egriboz et al, 2013; Lavy et al, 2012), leading to a significant rise in Gal3–Gal interactions along with a concomitant decline in Gal self-associations, as well as a rapid induction of transcriptional activation by Gal via recruitment of coactivators and transcription machinery to promoter regions through its activation domain upon Gal dissociation (Egriboz et al, 2013). Extensive studies have revealed this mechanism of transcriptional activation by Gal to be conserved among eukaryotes; in particular, Gal was shown to activate transcription when expressed in mammalian cells (Traven, Jelicic & Sopta, 2006)
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