Structure of galactarate dehydratase, a new fold in an enolase involved in bacterial fitness after antibiotic treatment.

Galactarate dehydratase (GarD) is the first enzyme in the galactarate/glucarate pathway and catalyzes the dehydration of galactarate to 3-keto-5-dehydroxygalactarate. This protein is known to increase colonization fitness of intestinal pathogens in antibiotic-treated mice and to promote bacterial survival during stress. The galactarate/glucarate pathway is widespread in bacteria, but not in humans, and thus could be a target to develop new inhibitors for use in combination therapy to combat antibiotic resistance. The structure of almost all the enzymes of the galactarate/glucarate pathway were solved previously, except for GarD, for which only the structure of the N-terminal domain was determined previously. Herein, we report the first crystal structure of full-length GarD solved using a seleno-methoionine derivative revealing a new protein fold. The protein consists of three domains, each presenting a novel twist as compared to their distant homologs. GarD in the crystal structure forms dimers and each monomer consists of three domains. The N-terminal domain is comprised of a ß-clip fold, connected to the second domain by a long unstructured linker. The second domain serves as a dimerization interface between two monomers. The C-terminal domain forms an unusual variant of a Rossmann fold with a crossover and is built around a seven-stranded parallel ß-sheet supported by nine α-helices. A metal binding site in the C-terminal domain is occupied by Ca2+ . The activity of GarD was corroborated by the production of 5-keto-4-deoxy-D-glucarate under reducing conditions and in the presence of iron. Thus, GarD is an unusual enolase with a novel protein fold never previously seen in this class of enzymes.

Molecular modeling of phosphorylation sites in proteins using a database of local structure segments.

A new bioinformatics tool for molecular modeling of the local structure around phosphorylation sites in proteins has been developed. Our method is based on a library of short sequence and structure motifs. The basic structural elements to be predicted are local structure segments (LSSs). This enables us to avoid the problem of non-exact local description of structures, caused by either diversity in the structural context, or uncertainties in prediction methods. We have developed a library of LSSs and a profile--profile-matching algorithm that predicts local structures of proteins from their sequence information. Our fragment library prediction method is publicly available on a server (FRAGlib), at http://ffas.ljcrf.edu/Servers/frag.html . The algorithm has been applied successfully to the characterization of local structure around phosphorylation sites in proteins. Our computational predictions of sequence and structure preferences around phosphorylated residues have been confirmed by phosphorylation experiments for PKA and PKC kinases. The quality of predictions has been evaluated with several independent statistical tests. We have observed a significant improvement in the accuracy of predictions by incorporating structural information into the description of the neighborhood of the phosphorylated site. Our results strongly suggest that sequence information ought to be supplemented with additional structural context information (predicted with our segment similarity method) for more successful predictions of phosphorylation sites in proteins.