Top Level Name
⌊ Superfamily (core) Enolase
⌊ Subgroup muconate cycloisomerase
⌊ Family dipeptide epimerase
|Functional domains of this family were last updated on Feb. 14, 2017|
|New functional domains were last added to this family on May 7, 2015|
Enzymes in the dipeptide epimerase family catalyze the epimerization of dipeptides, with the preferred substrate often L-Ala-D/L-Glu. Based on genomic context and substrate specificity, these enzymes may be involved in metabolism of the murein peptide, of which L-Ala-D-Glu is a component.
Kalyanaraman C, Imker HJ, Fedorov AA, Fedorov EV, Glasner ME, Babbitt PC, Almo SC, Gerlt JA, Jacobson MP
Discovery of a dipeptide epimerase enzymatic function guided by homology modeling and virtual screening
We have developed a computational approach to aid the assignment of enzymatic function for uncharacterized proteins that uses homology modeling to predict the structure of the binding site and in silico docking to identify potential substrates. We apply this method to proteins in the functionally diverse enolase superfamily that are homologous to the characterized L-Ala-D/L-Glu epimerase from Bacillus subtilis. In particular, a protein from Thermotoga martima was predicted to have different substrate specificity, which suggests that it has a different, but as yet unknown, biological function. This prediction was experimentally confirmed, resulting in the assignment of epimerase activity for L-Ala-D/L-Phe, L-Ala-D/L-Tyr, and L-Ala-D/L-His, whereas the enzyme is annotated incorrectly in GenBank as muconate cycloisomerase. Subsequently, crystal structures of the enzyme were determined in complex with three substrates, showing close agreement with the computational models and revealing the structural basis for the observed substrate selectivity.
Lukk T, Sakai A, Kalyanaraman C, Brown SD, Imker HJ, Song L, Fedorov AA, Fedorov EV, Toro R, Hillerich B, Seidel R, Patskovsky Y, Vetting MW, Nair SK, Babbitt PC, Almo SC, Gerlt JA, Jacobson MP
Homology models guide discovery of diverse enzyme specificities among dipeptide epimerases in the enolase superfamily
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.
Sequence Similarity Networks
Download a Sequence Similarity Network of this family (XGMML format ).
Network downloads are XGMML files that are readable by program such as Cytoscape. In these networks, nodes represent proteins and edges represent pairwise similarities better than a given E-value cutoff. Additionally, these networks contain several attributes with data from the SFLD.
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Repnet: 50% ID (9-Oct-2015)
Multiple Sequence Alignment
Multiple Sequence Alignment
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The maximum E-value at which pairwise similarities are included in the network.
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Full length sequences in FASTA format.
Sequences of the Functional Domain in FASTA format.
Download complete annotation of sequences sets of this superfamily as a ͟Tab ͟Separated ͟Value (TSV) file. This file has all data but cell size can exceed the maximum supported by spreadsheet programs (such as Microsoft Excel ®).
Annotation of sequences sets of this superfamily in a ͟Tab ͟Separated ͟Value (TSV) file. This file can be imported into a spreadsheet application. Cells which exceed the allowed spreadsheet maximum (32.5K) are preceded by the word "Truncated" and clipped short.