Computation-facilitated assignment of the function in the enolase superfamily: a regiochemically distinct galactarate dehydratase from Oceanobacillus iheyensis .

Members of the enolase superfamily catalyze mechanistically diverse reactions, each initiated by abstraction of the α-proton of a carboxylate substrate by an active site base to form an enolate intermediate (1, 2). The active sites are located at the interface between an N-terminal α+β capping domain and a C-terminal (β/α)7β-barrel domain (modified (β/α)8- or TIM-barrel2). Residues responsible for binding the essential Mg2+ and the acid/base catalysts are located at the C-terminal ends of the β-strands of the barrel domain or in the loops that connect the β-strands with the following α-helices; loops in the capping domain contain residues that provide shape and polarity determinants for the active site, thereby determining the identity of the substrate. A conserved strategy is used to stabilize the enolate intermediate: one or both carboxylate oxygens of the substrate is coordinated to a Mg2+ so that the increased negative charge in the enolate can be stabilized. The superfamily is divided into subgroups on the basis of the identities of the ligands for the Mg2+ (located at the ends of the third, fourth, and fifth β-strands of the barrel domain) and the acid/base catalysts (located at the ends of the second, third, sixth, and/or seventh β-strands of the barrel domain). Six subgroups currently are recognized (designated by the name of the paradigm enzyme/structure): enolase, mandelate racemase (MR), cis,cis-muconate lactonizing enzyme (MLE), D-glucarate dehydratase (GlucD), D-mannonate dehydratase (ManD), and β-methylaspartate ammonia lyase (3). To date, nineteen distinct chemical reactions are catalyzed by members of the enolase superfamily, with these involving elimination of water or ammonia, intramolecular β-elimination (cycloisomerization), and 1,1-proton transfer (epimerization or racemization). As illustrated in the sequence similarity network (4) shown in Figure 1, the enolase superfamily can be partitioned into sequence “clusters” that aid identification of isofunctional families. In Figure 1 the members of each of the separate clusters share a BLASTP e-value of 35% sequence identity). The sequences in this network are color-coded by function, with grey sequences having unknown or uncertain function. The results of these and other bioinformatic analyses indicate that at least 50% of the currently known members of the enolase superfamily have unknown, uncertain, or incorrect functional assigments. If the structural bases for divergent evolution of function in the superfamily are to be understood and, perhaps, utilized for rational (re)design of enzymatic activities, the functions of all members of the superfamily must be assigned. Figure 1 Sequence similarity network for the enolase superfamily. Sequences are shown schematically as nodes (dots); BLASTP connections with E-values ≤ 10−80 are shown as edges (lines). At this E-value (sequence identities > ~35%), most ... Our goal is to use the sequences and/or structures of functionally uncharacterized members to enable computation-directed prediction of their substrate specificities, thereby focusing experimental efforts to accomplish their in vitro functional assignments. In the enolase superfamily, we have used comparative protein structure modeling and docking to guide discovery of a novel N-succinylamino acid racemase (5) and dipeptide epimerases with novel substrate specificities (6) in the absence of X-ray structures. In the mechanistically diverse amidohydrolase superfamily, Shoichet, Raushel, and coworkers have used in silico docking of “high-energy intermediates” to X-ray structures of an uncharacterized member to direct discovery of the 5-methylthioadenosine/S-adenosyl-homocysteine deaminase function for an uncharacterized protein from Thermotoga maritima (7). These examples establish the utility of an integrated sequence/structure-based computational strategy to direct experimental assignment of function. Herein we describe computation-facilitated assignment of the galactarate dehydratase function to a divergent member of the enolase superfamily from Oceanobacillus iheyensis (GI:23100298; IMG locus tag Ob2843). In the sequence similarity network in Figure 1, Ob2843 is “clustered” (highlighted with red circle) with one additional presumed orthologue from Bacillus clausii KSM-K16 (GI:56964777). The structure of Ob2843 (PDB Code 2OQY) was determined in the presence of Mg2+, but the absence of an organic ligand, by the New York SGX Research Center for Structural Genomics (NYSGXRC; PSI-2) as one of their community-nominated targets. In silico screening of a virtual library of acid sugars to the active site of Ob2843 predicted that a diacid sugar was a plausible substrate; activity screening with a physical library of acid sugars identified galactarate as the substrate. Dehydration of galactarate (as well as of L-talarate) was previously assigned as the enzymatic function of a divergent family by physical library screening (GalrD/TalrD; highlighted with blue circle in Figure 1) (8). However, the “old” (GalrD/TalrD) and “new” (GalrD-II) galactarate dehydratases differ in regioselectivity so the products obtained from (meso-)galactarate are enantiomers. The structure of the catalytically impaired Y90F mutant of GalrD-II was determined in the presence of galactarate and Mg2+, thereby allowing identification of novel active site residues: 1) an Arg-x-Tyr dyad at the end of the second β-strand of the barrel domain is the base that initiates the reaction, 2) a Tyr in the capping domain is the acid that facilitates departure of the 3-OH leaving group, and 3) a His (not Asp, Glu, or Asn as in other characterized members of the superfamily) located at the end of the fifth β-strand as a ligand for the essential Mg2+. This active site motif defines the seventh subgroup in the enolase superfamily (GalrD-II). The assignment of the GalrD-II function to Ob2843 provides additional evidence that an integrated sequence/structure-based strategy to direct functional assignment (using computational prediction to focus experimental activity measurements) is a viable approach for enabling nontrivial functional assignments.