Discovery of a Dipeptide Epimerase Enzymatic Function Guided by Homology Modeling and Virtual Screening

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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.computational biology | enzymology | protein function

Section: Resultsmentioning

confidence: 96%

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confidence: 99%

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

Lukk

Sakai

Kalyanaraman

et al. 2012

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“…S1). Like most other members of the enolase superfamily, the five enzymes from the NSAR/OSBS subfamily are multimers (21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40). The three previously characterized NSAR/OSBS subfamily enzymes are (53).…”

Section: Resultsmentioning

confidence: 97%

Loss of quaternary structure is associated with rapid sequence divergence in the OSBS family

Odokonyero

Sakai

Patskovsky³

et al. 2014

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The rate of protein evolution is determined by a combination of selective pressure on protein function and biophysical constraints on protein folding and structure. Determining the relative contributions of these properties is an unsolved problem in molecular evolution with broad implications for protein engineering and function prediction. As a case study, we examined the structural divergence of the rapidly evolving o-succinylbenzoate synthase (OSBS) family, which catalyzes a step in menaquinone synthesis in diverse microorganisms and plants. On average, the OSBS family is much more divergent than other protein families from the same set of species, with the most divergent family members sharing <15% sequence identity. Comparing 11 representative structures revealed that loss of quaternary structure and large deletions or insertions are associated with the family's rapid evolution. Neither of these properties has been investigated in previous studies to identify factors that affect the rate of protein evolution. Intriguingly, one subfamily retained a multimeric quaternary structure and has small insertions and deletions compared with related enzymes that catalyze diverse reactions. Many proteins in this subfamily catalyze both OSBS and N-succinylamino acid racemization (NSAR). Retention of ancestral structural characteristics in the NSAR/OSBS subfamily suggests that the rate of protein evolution is not proportional to the capacity to evolve new protein functions. Instead, structural features that are conserved among proteins with diverse functions might contribute to the evolution of new functions.enolase superfamily | protein structure | protein structure-function relationships I nvestigating the causes and effects of protein sequence divergence is the key to identifying properties that enable proteins to evolve new functions. Previous studies found that constraints imposed by biophysical properties such as protein folding and stability, translational accuracy, and interactions with other proteins make a large contribution to the rate of protein evolution (1-11). However, the relative contributions of biophysical properties versus functional constraints is an open question (2). Given that the rate of protein evolution varies over several orders of magnitude, the evolutionary rate of each protein is probably determined by a unique blend of biophysical and functional constraints (12-15). Thus, the evolutionary simulations and statistical analyses of large protein datasets that comprise the primary focus of this field need to be supplemented with case studies.Here, we present the extraordinarily diverse o-succinylbenzoate synthase (OSBS) family as such a case study. The OSBS family belongs to the enolase superfamily, a group of evolutionarily related protein families that have a common fold but catalyze diverse reactions (16). The rate of sequence divergence in the OSBS family is much faster than other families in the enolase superfamily. For example, the average pairwise amino acid sequence identity of OSBSs fr...

“…To visualize relationships between members of the subgroup, we generated sequence similarity networks using Pythoscape (16), where nodes represent sequences, and edges represent pairwise local alignments with BLAST e-values more significant than a specified cutoff, allowing a dynamic view of clustering patterns and sequence annotations. Sequence-similarity networks can handle thousands of sequences, are quick to compute and robust to missing data (17,18), and have been shown to correlate well with phylogenetic trees (19,20). Fig.…”

Section: Resultsmentioning

confidence: 99%

Prediction of function for the polyprenyl transferase subgroup in the isoprenoid synthase superfamily

Wallrapp

Pan

Ramamoorthy

et al. 2013

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The number of available protein sequences has increased exponentially with the advent of high-throughput genomic sequencing, creating a significant challenge for functional annotation. Here, we describe a large-scale study on assigning function to unknown members of the trans-polyprenyl transferase (E-PTS) subgroup in the isoprenoid synthase superfamily, which provides substrates for the biosynthesis of the more than 55,000 isoprenoid metabolites. Although the mechanism for determining the product chain length for these enzymes is known, there is no simple relationship between function and primary sequence, so that assigning function is challenging. We addressed this challenge through large-scale bioinformatics analysis of >5,000 putative polyprenyl transferases; experimental characterization of the chain-length specificity of 79 diverse members of this group; determination of 27 structures of 19 of these enzymes, including seven cocrystallized with substrate analogs or products; and the development and successful application of a computational approach to predict function that leverages available structural data through homology modeling and docking of possible products into the active site. The crystallographic structures and computational structural models of the enzyme-ligand complexes elucidate the structural basis of specificity. As a result of this study, the percentage of E-PTS sequences similar to functionally annotated ones (BLAST e-value ≤ 1e −70 ) increased from 40.6 to 68.8%, and the percentage of sequences similar to available crystal structures increased from 28.9 to 47.4%. The high accuracy of our blind prediction of newly characterized enzymes indicates the potential to predict function to the complete polyprenyl transferase subgroup of the isoprenoid synthase superfamily computationally.chain-elongation | prenyltransferase T he five-carbon molecules isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP) are the fundamental building blocks for isoprenoid compounds. Beginning with DMAPP, a series of polyprenyl diphosphates with C 10 (geranyl diphosphate, GPP), C 15 (farnesyl diphosphate, FPP), C 20 (geranylgeranyl diphosphate, GGPP), C 25 (farnesylgeranyl diphosphate, FGPP), and higher molecular weight isoprenoid chains are synthesized by polyprenyl transferases (PTSs). With only a few exceptions, PTSs provide substrates for all but a few branch point enzymes for the biosynthesis of the more than 55,000 known isoprenoid metabolites, including monoterpenes, sesquiterpenes, diterpenes, sterols, carotenoids, ubiquinones, and prenylated proteins and peptides fulfilling essential roles in cells (Fig. S1) (1, 2).There are two distinct classes of PTSs, E-PTS forming trans bonds and Z-PTS forming cis bonds throughout chain elongation. The carbon skeletons of the great majority of isoprenoid metabolites are derived from products of E-PTSs, which share a common protein fold and two functionally important Asp-rich (DDXXD) motifs (1, 3, 4). E-PTSs synthesize linear allylic diphosphates ranging f...