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. 2012 Mar 13;109(11):4122-7.
doi: 10.1073/pnas.1112081109. Epub 2012 Mar 5.

Homology models guide discovery of diverse enzyme specificities among dipeptide epimerases in the enolase superfamily

Affiliations

Homology models guide discovery of diverse enzyme specificities among dipeptide epimerases in the enolase superfamily

Tiit Lukk et al. Proc Natl Acad Sci U S A. .

Abstract

The rapid advance in genome sequencing presents substantial challenges for protein functional assignment, with half or more of new protein sequences inferred from these genomes having uncertain assignments. The assignment of enzyme function in functionally diverse superfamilies represents a particular challenge, which we address through a combination of computational predictions, enzymology, and structural biology. Here we describe the results of a focused investigation of a group of enzymes in the enolase superfamily that are involved in epimerizing dipeptides. The first members of this group to be functionally characterized were Ala-Glu epimerases in Eschericiha coli and Bacillus subtilis, based on the operon context and enzymological studies; these enzymes are presumed to be involved in peptidoglycan recycling. We have subsequently studied more than 65 related enzymes by computational methods, including homology modeling and metabolite docking, which suggested that many would have divergent specificities;, i.e., they are likely to have different (unknown) biological roles. In addition to the Ala-Phe epimerase specificity reported previously, we describe the prediction and experimental verification of: (i) a new group of presumed Ala-Glu epimerases; (ii) several enzymes with specificity for hydrophobic dipeptides, including one from Cytophaga hutchinsonii that epimerizes D-Ala-D-Ala; and (iii) a small group of enzymes that epimerize cationic dipeptides. Crystal structures for certain of these enzymes further elucidate the structural basis of the specificities. The results highlight the potential of computational methods to guide experimental characterization of enzymes in an automated, large-scale fashion.

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Conflict of interest statement

The authors declare a conflict of interest. M.P.J. is a consultant to Schrodinger LLC, which developed or licensed some of the software used in this study.

Figures

Fig. 1.
Fig. 1.
Sequence similarity network for the putative dipeptide epimerases in the enolase superfamily. Each node represents a single sequence; edges represents connections with BLAST e-value better than the cutoff value shown in each panel. Enzymes whose sequences were available in 2006 are colored according to their computationally predicted specificity, using homology models and ligand docking (larger nodes). The previously characterized Ala-Glu epimerases from E. coli and B. subtilis are labeled.
Fig. 2.
Fig. 2.
Sequence similarity network with experimentally characterized enzyme specificities labeled. Larger nodes represent sequences that have been experimentally characterized in this or earlier studies. Circles represent sequences for which crystal structures have been determined. Node border colors represent the type of experiment used to establish substrate specificity (red, kinetics; blue, mass spectrometry). In cases where there is no clear specificity for a single amino acid, “Pos” refers to specificity for positively charged amino acids (Lys, Arg, and His), “Hyd” refers to specificity for hydrophobic amino acids, and “Xxx” refers to no significant specificity observed.
Fig. 3.
Fig. 3.
Comparison of the active sites of the dipeptide epimerases from (A) B. thetaiotamicron (3IJQ) and (B) B. subtilis (1TKK). The dipeptide substrates and key residues in the catalytic site are shown in stick representation, and the Mg2+ is shown as a sphere.
Fig. 4.
Fig. 4.
Binding sites of the dipeptide epimerases from (A) E. faecalis (3JW7), (B) C. hutchinsoni (3Q4D), (C) M. capsulatus (3RIT) and (D) F. philomiragia (3R1Z).

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