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Tautomerase superfamily (TSF) members are constructed from a single β−α−β unit or two consecutively joined β−α−β units. This pattern prevails throughout the superfamily consisting of more than 11,000 members where homo- or heterohexamers are localized in the 4-oxalocrotonate tautomerase (4-OT) subgroup and trimers are found in the other four subgroups. One exception is a subset of sequences that are double the length of the short 4-OTs in the 4-OT subgroup, where the coded proteins form trimers. Characterization of two members revealed an interesting dichotomy. One is a symmetric trimer, whereas the other one is an asymmetric trimer. One monomer is flipped 180° relative to the other two monomers so that three unique protein-protein interfaces are created that are composed of different residues. A bioinformatics analysis of the fused 4-OT subset shows a further division into two clusters with a total of 133 sequences. The analysis showed that members of one cluster (86 sequences) have more salt bridges if the asymmetric trimer forms, whereas the members of the other cluster (47 sequences) have more salt bridges if the symmetric trimer forms. This hypothesis was examined by the kinetic and structural characterization of two proteins within each cluster. As predicted, all four proteins function as 4-OTs, where two assemble into asymmetric trimers (designated R7 and F6) and two form symmetric trimers (designated W0 and Q0). These findings can be extended to the other sequences in the two clusters in the fused 4-OT subset, thereby annotating their oligomer properties and activities.

Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification-amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two-Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure-Function Linkage Database, SFLD) self-identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self-identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well-curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP-identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F-measure and performance analysis on the enolase search results and comparison to GEMMA and SCI-PHY demonstrate that TuLIP avoids the over-division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results.

Determining the molecular function of enzymes discovered by genome sequencing represents a primary foundation for understanding many aspects of biology. Historically, classification of enzyme reactions has used the enzyme nomenclature system developed to describe the overall reactions performed by biochemically characterized enzymes, irrespective of their associated sequences. In contrast, functional classification and assignment for the millions of protein sequences of unknown function now available is largely done in two computational steps, first by similarity-based assignment of newly obtained sequences to homologous groups, followed by transferring to them the known functions of similar biochemically characterized homologs. Due to the fundamental differences in their etiologies and practice, `how’ these chemistry- and evolution-centric functional classification systems relate to each other has been difficult to explore on a large scale. To investigate this issue in a new way, we integrated two published ontologies that had previously described each of these classification systems independently. The resulting infrastructure was then used to compare the functional assignments obtained from each classification system for the well-studied and functionally diverse enolase superfamily. Mapping these function assignments to protein structure and reaction similarity networks shows a profound and complex disconnect between the homology- and chemistry-based classification systems. This conclusion mirrors previous observations suggesting that except for closely related sequences, facile annotation transfer from small numbers of characterized enzymes to the huge number uncharacterized homologs to which they are related is problematic. Our extension of these comparisons to large enzyme superfamilies in a computationally intelligent manner provides a foundation for new directions in protein function prediction for the huge proportion of sequences of unknown function represented in major databases. Interactive sequence, reaction, substrate and product similarity networks computed for this work for the enolase and two other superfamilies are freely available for download from the Structure Function Linkage Database Archive (http://sfld.rbvi.ucsf.edu).

A 4-oxalocrotonate tautomerase (4-OT) trimer has been isolated from Burkholderia lata, and a kinetic, mechanistic, and structural analysis has been performed. The enzyme is the third described oligomer state for 4-OT along with a homo- and heterohexamer. The 4-OT trimer is part of a small subset of sequences (133 sequences) within the 4-OT subgroup of the tautomerase superfamily (TSF). The TSF has two distinct features: members are composed of a single β-α-β unit (homo- and heterohexamer) or two consecutively joined β-α-β units (trimer) and generally have a catalytic amino-terminal proline. The enzyme, designated as fused 4-OT, functions as a 4-OT where the active site groups (Pro-1, Arg-39, Arg-76, Phe-115, Arg-127) mirror those in the canonical 4-OT from Pseudomonas putida mt-2. Inactivation by 2-oxo-3-pentynoate suggests that Pro-1 of fused 4-OT has a low p Ka enabling the prolyl nitrogen to function as a general base. A remarkable feature of the fused 4-OT is the absence of P3 rotational symmetry in the structure (1.5 A resolution). The asymmetric arrangement of the trimer is not due to the fusion of the two β-α-β building blocks because an engineered "unfused" variant that breaks the covalent bond between the two units (to generate a heterohexamer) assumes the same asymmetric oligomerization state. It remains unknown how the different active site configurations contribute to the observed overall activities and whether the asymmetry has a biological purpose or role in the evolution of TSF members.

The InterPro database (http://www.ebi.ac.uk/interpro/) classifies protein sequences into families and predicts the presence of functionally important domains and sites. Here, we report recent developments with InterPro (version 70.0) and its associated software, including an 18% growth in the size of the database in terms on new InterPro entries, updates to content, the inclusion of an additional entry type, refined modelling of discontinuous domains, and the development of a new programmatic interface and website. These developments extend and enrich the information provided by InterPro, and provide greater flexibility in terms of data access. We also show that InterPro's sequence coverage has kept pace with the growth of UniProtKB, and discuss how our evaluation of residue coverage may help guide future curation activities.

The radical SAM superfamily contains over 100,000 homologous enzymes that catalyze a remarkably broad range of reactions required for life, including metabolism, nucleic acid modification, and biogenesis of cofactors. While the highly conserved SAM-binding motif responsible for formation of the key 5′-deoxyadenosyl radical intermediate is a key structural feature that simplifies identification of superfamily members, our understanding of their structure–function relationships is complicated by the modular nature of their structures, which exhibit varied and complex domain architectures. To gain new insight about these relationships, we classified the entire set of sequences into similarity-based subgroups that could be visualized using sequence similarity networks. This superfamily-wide analysis reveals important features that had not previously been appreciated from studies focused on one or a few members. Functional information mapped to the networks indicates which members have been experimentally or structurally characterized, their known reaction types, and their phylogenetic distribution. Despite the biological importance of radical SAM chemistry, the vast majority of superfamily members have never been experimentally characterized in any way, suggesting that many new reactions remain to be discovered. In addition to 20 subgroups with at least one known function, we identified additional subgroups made up entirely of sequences of unknown function. Importantly, our results indicate that even general reaction types fail to track well with our sequence similarity-based subgroupings, raising major challenges for function prediction for currently identified and new members that continue to be discovered. Interactive similarity networks and other data from this analysis are available from the Structure-Function Linkage Database.

Enzyme-mediated modifications at the wobble position of tRNAs are essential for the translation of the genetic code. We report the genetic, biochemical and structural characterization of CmoB, the enzyme that recognizes the unique metabolite carboxy-S-adenosine-L-methionine (Cx-SAM) and catalyzes a carboxymethyl transfer reaction resulting in formation of 5-oxyacetyluridine at the wobble position of tRNAs. CmoB is distinctive in that it is the only known member of the SAM-dependent methyltransferase (SDMT) superfamily that utilizes a naturally occurring SAM analog as the alkyl donor to fulfill a biologically meaningful function. Biochemical and genetic studies define the in vitro and in vivo selectivity for Cx-SAM as alkyl donor over the vastly more abundant SAM. Complementary high-resolution structures of the apo- and Cx-SAM bound CmoB reveal the determinants responsible for this remarkable discrimination. Together, these studies provide mechanistic insight into the enzymatic and non-enzymatic feature of this alkyl transfer reaction which affords the broadened specificity required for tRNAs to recognize multiple synonymous codons.

Author(s): Holliday, Gemma L; Brown, Shoshana D; Akiva, Eyal; Mischel, David; Hicks, Michael A; Morris, John H; Huang, Conrad C; Meng, Elaine C; Pegg, Scott C-H; Ferrin, Thomas E; Babbitt, Patricia C | Abstract: With ever-increasing amounts of sequence data available in both the primary literature and sequence repositories, there is a bottleneck in annotating molecular function to a sequence. This article describes the biocuration process and methods used in the structure-function linkage database (SFLD) to help address some of the challenges. We discuss how the hierarchy within the SFLD allows us to infer detailed functional properties for functionally diverse enzyme superfamilies in which all members are homologous, conserve an aspect of their chemical function and have associated conserved structural features that enable the chemistry. Also presented is the Enzyme Structure-Function Ontology (ESFO), which has been designed to capture the relationships between enzyme sequence, structure and function that underlie the SFLD and is used to guide the biocuration processes within the SFLD.Database urlhttp://sfld.rbvi.ucsf.edu/.

Understanding how enzymes have evolved offers clues about their structure-function relationships and mechanisms. Here, we describe evolution of functionally diverse enzyme superfamilies, each representing a large set of sequences that evolved from a common ancestor and that retain conserved features of their structures and active sites. Using several examples, we describe the different structural strategies nature has used to evolve new reaction and substrate specificities in each unique superfamily. The results provide insight about enzyme evolution that is not easily obtained from studies of one or only a few enzymes.

Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification—amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two‐Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure‐Function Linkage Database, SFLD) self‐identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self‐identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well‐curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP‐identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F‐measure and performance analysis on the enolase search results and comparison to GEMMA and SCI‐PHY demonstrate that TuLIP avoids the over‐division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results.

The Structure-Function Linkage Database (SFLD, http://sfld.rbvi.ucsf.edu/) is a manually curated classification resource describing structure-function relationships for functionally diverse enzyme superfamilies. Members of such superfamilies are diverse in their overall reactions yet share a common ancestor and some conserved active site features associated with conserved functional attributes such as a partial reaction. Thus, despite their different functions, members of these superfamilies 'look alike', making them easy to misannotate. To address this complexity and enable rational transfer of functional features to unknowns only for those members for which we have sufficient functional information, we subdivide superfamily members into subgroups using sequence information, and lastly into families, sets of enzymes known to catalyze the same reaction using the same mechanistic strategy. Browsing and searching options in the SFLD provide access to all of these levels. The SFLD offers manually curated as well as automatically classified superfamily sets, both accompanied by search and download options for all hierarchical levels. Additional information includes multiple sequence alignments, tab-separated files of functional and other attributes, and sequence similarity networks. The latter provide a new and intuitively powerful way to visualize functional trends mapped to the context of sequence similarity. © 2013 The Author(s). Published by Oxford University Press.

Assigning valid functions to proteins identified in genome projects is challenging: overprediction and database annotation errors are the principal concerns. We and others are developing computation-guided strategies for functional discovery with 'metabolite docking' to experimentally derived or homology-based three-dimensional structures. Bacterial metabolic pathways often are encoded by 'genome neighbourhoods' (gene clusters and/or operons), which can provide important clues for functional assignment. We recently demonstrated the synergy of docking and pathway context by 'predicting' the intermediates in the glycolytic pathway in Escherichia coli. Metabolite docking to multiple binding proteins and enzymes in the same pathway increases the reliability of in silico predictions of substrate specificities because the pathway intermediates are structurally similar. Here we report that structure-guided approaches for predicting the substrate specificities of several enzymes encoded by a bacterial gene cluster allowed the correct prediction of the in vitro activity of a structurally characterized enzyme of unknown function (PDB 2PMQ), 2-epimerization of trans-4-hydroxy-L-proline betaine (tHyp-B) and cis-4-hydroxy-D-proline betaine (cHyp-B), and also the correct identification of the catabolic pathway in which Hyp-B 2-epimerase participates. The substrate-liganded pose predicted by virtual library screening (docking) was confirmed experimentally. The enzymatic activities in the predicted pathway were confirmed by in vitro assays and genetic analyses; the intermediates were identified by metabolomics; and repression of the genes encoding the pathway by high salt concentrations was established by transcriptomics, confirming the osmolyte role of tHyp-B. This study establishes the utility of structure-guided functional predictions to enable the discovery of new metabolic pathways.

Identifying novel metabolites and characterizing their biological functions are major challenges of the post-genomic era. X-ray crystallography can reveal unanticipated ligands which persist through purification and crystallization. These adventitious protein:ligand complexes provide insights into new activities, pathways and regulatory mechanisms. We describe a new metabolite, carboxy-S-adenosylmethionine (Cx-SAM), its biosynthetic pathway and its role in tRNA modification. The structure of CmoA, a member of the SAM-dependent methyltransferase superfamily, revealed a ligand in the catalytic site consistent with Cx-SAM. Mechanistic analyses demonstrated an unprecedented role for prephenate as the carboxyl donor and the involvement of a unique ylide intermediate as the carboxyl acceptor in the CmoA-mediated conversion of SAM to Cx-SAM. A second member of the SAM-dependent methyltransferase superfamily, CmoB, recognizes Cx-SAM and acts as a carboxymethyltransferase to convert 5-hydroxyuridine (ho5U) into 5-oxyacetyl uridine (cmo5U) at the wobble position of multiple tRNAs in Gram negative bacteria1, resulting in expanded codon-recognition properties2,3. CmoA and CmoB represent the first documented synthase and transferase for Cx-SAM. These findings reveal new functional diversity in the SAM-dependent methyltransferase superfamily and expand the metabolic and biological contributions of SAM-based biochemistry. These discoveries highlight the value of structural genomics approaches for identifying ligands in the context of their physiologically relevant macromolecular binding partners and for aiding in functional assignment.

To study the substrate specificity of enzymes, we use the amidohydrolase and enolase superfamilies as model systems; members of these superfamilies share a common TIM barrel fold and catalyze a wide range of chemical reactions. Here, we describe a collaboration between the Enzyme Specificity Consortium (ENSPEC) and the New York SGX Research Center for Structural Genomics (NYSGXRC) that aims to maximize the structural coverage of the amidohydrolase and enolase superfamilies. Using sequence- and structure-based protein comparisons, we first selected 535 target proteins from a variety of genomes for high-throughput structure determination by X-ray crystallography; 63 of these targets were not previously annotated as superfamily members. To date, 20 unique amidohydrolase and 41 unique enolase structures have been determined, increasing the fraction of sequences in the two superfamilies that can be modeled based on at least 30% sequence identity from 45% to 73%. We present case studies of proteins related to uronate isomerase (an amidohydrolase superfamily member) and mandelate racemase (an enolase superfamily member), to illustrate how this structure-focused approach can be used to generate hypotheses about sequence–structure–function relationships. Electronic supplementary material The online version of this article (doi:10.1007/s10969-008-9056-5) contains supplementary material, which is available to authorized users.

The mechanistically diverse enolase superfamily is a paradigm for elucidating Nature's strategies for divergent evolution of enzyme function. Each of the different reactions catalyzed by members of the superfamily is initiated by abstraction of the alpha-proton of a carboxylate substrate that is coordinated to an essential Mg(2+). The muconate lactonizing enzyme (MLE) from Pseudomonas putida, a member of a family that catalyzes the syn-cycloisomerization of cis,cis-muconate to (4S)-muconolactone in the beta-ketoadipate pathway, has provided critical insights into the structural bases for evolution of function within the superfamily. A second, divergent family of homologous MLEs that catalyzes anti-cycloisomerization has been identified. Structures of members of both families liganded with the common (4S)-muconolactone product (syn, Pseudomonas fluorescens, gi 70731221 ; anti, Mycobacterium smegmatis, gi 118470554 ) document that the conserved Lys at the end of the second beta-strand in the (beta/alpha)(7)beta-barrel domain serves as the acid catalyst in both reactions. The different stereochemical courses (syn and anti) result from different structural strategies for determining substrate specificity: although the distal carboxylate group of the cis,cis-muconate substrate attacks the same face of the proximal double bond, opposite faces of the resulting enolate anion intermediate are presented to the conserved Lys acid catalyst. The discovery of two families of homologous, but stereochemically distinct, MLEs likely provides an example of "pseudoconvergent" evolution of the same function from different homologous progenitors within the enolase superfamily, in which different spatial arrangements of active site functional groups and substrate specificity determinants support catalysis of the same reaction.

NagA catalyzes the hydrolysis of N-acetyl-D-glucosamine-6-phosphate to D-glucosamine-6-phosphate and acetate. X-ray crystal structures of NagA from Escherichia coli were determined to establish the number and ligation scheme for the binding of zinc to the active site and to elucidate the molecular interactions between the protein and substrate. The three-dimensional structures of the apo-NagA, Zn-NagA, and the D273N mutant enzyme in the presence of a tight-binding N-methylhydroxyphosphinyl-D-glucosamine-6-phosphate inhibitor were determined. The structure of the Zn-NagA confirms that this enzyme binds a single divalent cation at the beta-position in the active site via ligation to Glu-131, His-195, and His-216. A water molecule completes the ligation shell, which is also in position to be hydrogen bonded to Asp-273. In the structure of NagA bound to the tight binding inhibitor that mimics the tetrahedral intermediate, the methyl phosphonate moiety has displaced the hydrolytic water molecule and is directly coordinated to the zinc within the active site. The side chain of Asp-273 is positioned to activate the hydrolytic water molecule via general base catalysis and to deliver this proton to the amino group upon cleavage of the amide bond of the substrate. His-143 is positioned to help polarize the carbonyl group of the substrate inmore » conjunction with Lewis acid catalysis by the bound zinc. The inhibitor is bound in the {alpha}-configuration at the anomeric carbon through a hydrogen bonding interaction of the hydroxyl group at C-1 with the side chain of His-251. The phosphate group of the inhibitor attached to the hydroxyl at C-6 is ion paired with Arg-227 from the adjacent subunit. NagA from Thermotoga maritima was shown to require a single divalent cation for full catalytic activity.« less

A kinetic study of the reversible deprotonation of methylnitroacetate (4H) by primary aliphatic amines, secondary alicyclic amines, hydroxide ion, and water in water at 25 degrees C and in 50% DMSO/50% water (v/v) at 20 degrees C is reported. Intrinsic rate constants, k0, determined by extrapolation or interpolation of Brønsted plots have been determined. In comparison to proton transfers involving other nitroalkanes, the intrinsic rate constants for 4H are exceptionally high; for example, log k0 for the reaction of 4H with secondary alicyclic amines in water (1.22) is 1.81 log units higher than log k0 for nitromethane (-0.59), while in 50% DMSO/50% water, log k0 for 4H (2.44) is 1.71 log units higher than that for nitromethane (0.73). A general discussion of the factors affecting intrinsic rate constants of proton transfer from nitroalkanes is presented; it provides the context for an understanding as to why k0 is so high for the proton transfers from 4H. The correlation between intrinsic rate constants for the addition of nucleophiles to alkenes of the type R'R' 'C=CXY and the intrinsic rate constants of proton transfers from carbon acids of the type H2CXY is also discussed as a general proposition as well as with specific reference to the Ph(SMe)C=C(NO2)CO2Me/H2C(NO2)CO2Me pair.

A spectroscopic and kinetic study of the reaction of methyl beta-methylthio-alpha-nitrocinnamate (4-SMe) with morpholine, piperidine, and hydroxide ion in 50% DMSO/50% water (v/v) at 20 degrees C is reported. The reactions of 4-SMe with piperidine in a pH range from 10.12 to 11.66 and those with morpholine at pH 12.0 are characterized by two kinetic processes when monitored at lambdamax (364 nm) of the substrate, but by only one process when monitored at lambdamax (388) nm of the product. The rate constants obtained at 388 nm were the same as those determined for the slower of the two processes at 364 nm. These rate constants refer to product formation, whereas the faster process observed at 364 nm is associated with the loss of reactant to form an intermediate. In contrast, for the reaction of 4-SMe with morpholine at pH 8.62 the rates of product formation and disappearance of the substrate were the same, i.e., there is no accumulation of an intermediate. Likewise, the reaction of 4-SMe with OH- did not yield a detectable intermediate. The factors that allow the accumulation of intermediates in certain SNV reactions but not in others are discussed in detail, and structure-reactivity comparisons are made with reactions of piperidine and morpholine with other highly activated vinylic substrates.

The study of mechanistically diverse enzyme superfamilies-collections of enzymes that perform different overall reactions but share both a common fold and a distinct mechanistic step performed by key conserved residues-helps elucidate the structure-function relationships of enzymes. We have developed a resource, the structure-function linkage database (SFLD), to analyze these structure-function relationships. Unique to the SFLD is its hierarchical classification scheme based on linking the specific partial reactions (or other chemical capabilities) that are conserved at the superfamily, subgroup, and family levels with the conserved structural elements that mediate them. We present the results of analyses using the SFLD in correcting misannotations, guiding protein engineering experiments, and elucidating the function of recently solved enzyme structures from the structural genomics initiative. The SFLD is freely accessible at http://sfld.rbvi.ucsf.edu.

Enzyme function prediction remains an important open problem. Though structure-based modeling, such as metabolite docking, can identify substrates of some enzymes, it is ill-suited to reactions that progress through a covalent intermediate. Here we investigated the ability of covalent docking to identify substrates that pass through such a covalent intermediate, focusing particularly on the haloalkanoate dehalogenase superfamily. In retrospective assessments, covalent docking recapitulated substrate binding modes of known cocrystal structures and identified experimental substrates from a set of putative phosphorylated metabolites. In comparison, noncovalent docking of high-energy intermediates yielded nonproductive poses. In prospective predictions against seven enzymes, a substrate was identified for five. For one of those cases, a covalent docking prediction, confirmed by empirical screening, and combined with genomic context analysis, suggested the identity of the enzyme that catalyzes the orphan phosphatase reaction in the riboflavin biosynthetic pathway of Bacteroides.

Identification and functional characterization of the genes in the human genome remain a major challenge. A principal source of publicly available information used for this purpose is the National Center for Biotechnology Information database of expressed sequence tags (dbEST), which contains over 4 million human ESTs. To extract the information buried in this data more effectively, we have developed a semiautomated method to mine dbEST for uncharacterized human genes. Starting with a single protein input sequence, a family of related proteins from all species is compiled. This entire family is then used to mine the human EST database for new gene candidates. Evaluation of putative new gene candidates in the context of a family of characterized proteins provides a framework for inference of the structure and function of the new genes. When applied to a test data set of 28 families within the major facilitator superfamily (MFS) of membrane transporters, our protocol found 73 previously characterized human MFS genes and 43 new MFS gene candidates. Development of this approach provided insights into the problems and pitfalls of automated data mining using public databases.

Metabolic pathways in eubacteria and archaea often are encoded by operons and/or gene clusters (genome neighborhoods) that provide important clues for assignment of both enzyme functions and metabolic pathways. We describe a bioinformatic approach (genome neighborhood network; GNN) that enables large scale prediction of the in vitro enzymatic activities and in vivo physiological functions (metabolic pathways) of uncharacterized enzymes in protein families. We demonstrate the utility of the GNN approach by predicting in vitro activities and in vivo functions in the proline racemase superfamily (PRS; InterPro IPR008794). The predictions were verified by measuring in vitro activities for 51 proteins in 12 families in the PRS that represent ∼85% of the sequences; in vitro activities of pathway enzymes, carbon/nitrogen source phenotypes, and/or transcriptomic studies confirmed the predicted pathways. The synergistic use of sequence similarity networks3 and GNNs will facilitate the discovery of the components of novel, uncharacterized metabolic pathways in sequenced genomes. DOI: http://dx.doi.org/10.7554/eLife.03275.001, eLife digest DNA molecules are polymers in which four nucleotides—guanine, adenine, thymine, and cytosine—are arranged along a sugar backbone. The sequence of these four nucleotides along the DNA strand determines the genetic code of the organism, and can be deciphered using various genome sequencing techniques. Microbial genomes are particularly easy to sequence as they contain fewer than several million nucleotides, compared with the 3 billion or so nucleotides that are present in the human genome. Reading a genome sequence is straight forward, but predicting the physiological functions of the proteins encoded by the genes in the sequence can be challenging. In a process called genome annotation, the function of protein is predicted by comparing the relevant gene to the genes of proteins with known functions. However, microbial genomes and proteins are hugely diverse and over 50% of the microbial genomes that have been sequenced have not yet been related to any physiological function. With thousands of microbial genomes waiting to be deciphered, large scale approaches are needed. Zhao et al. take advantage of a particular characteristic of microbial genomes. DNA sequences that code for two proteins required for the same task tend to be closer to each other in the genome than two sequences that code for unrelated functions. Operons are an extreme example; an operon is a unit of DNA that contains several genes that are expressed as proteins at the same time. Zhao et al. have developed a bioinformatic method called the genome neighbourhood network approach to work out the function of proteins based on their position relative to other proteins in the genome. When applied to the proline racemase superfamily (PRS), which contains enzymes with similar sequences that can catalyze three distinct chemical reactions, the new approach was able to assign a function to the majority of proteins in a public database of PRS enzymes, and also revealed new members of the PRS family. Experiments confirmed that the proteins behaved as predicted. The next challenge is to develop the genome neighbourhood network approach so that it can be applied to more complex systems. DOI: http://dx.doi.org/10.7554/eLife.03275.002

A kinetic study of the acid-catalyzed loss of alkoxide and thiolate ions from alkoxide and thiolate ion adducts, respectively, of benzylidene Meldrum's acid (1-H), methoxybenzylidene Meldrum's acid (1-OMe), and thiomethoxybenzylidene Meldrum's acid (1-SMe) is reported. The reactions appear to be subject to general acid catalysis, although the catalytic effect of buffers is weak and the bulk of the reported data refers to H(+)-catalysis. alpha-Carbon protonation and, in some cases, protonation of one of the carbonyl oxygens to form an enol compete with alkoxide or thiolate ion expulsion. This rendered the kinetic analysis more complex but allowed the determination of pK(a) values and of proton-transfer rate constants at the alpha-carbon. In conjunction with previously reported data on the nucleophilic addition of alkoxide and thiolate ions to the same Meldrum's acid derivatives, rate constants for nucleophilic addition by the respective neutral alcohols and thiols could also be calculated. Various structure-reactivity relationships are discussed that help define transition-state structures. Comparisons with similar reactions of alkoxide ion adducts of beta-alkoxy-alpha-nitrostilbenes provide additional insights.

Marchantia polymorpha is a basal terrestrial land plant, which like most liverworts accumulates structurally diverse terpenes believed to serve in deterring disease and herbivory. Previous studies have suggested that the mevalonate and methylerythritol phosphate pathways, present in evolutionarily diverged plants, are also operative in liverworts. However, the genes and enzymes responsible for the chemical diversity of terpenes have yet to be described. In this study, we resorted to a HMMER search tool to identify 17 putative terpene synthase genes from M. polymorpha transcriptomes. Functional characterization identified four diterpene synthase genes phylogenetically related to those found in diverged plants and nine rather unusual monoterpene and sesquiterpene synthase-like genes. The presence of separate monofunctional diterpene synthases for ent-copalyl diphosphate and ent-kaurene biosynthesis is similar to orthologs found in vascular plants, pushing the date of the underlying gene duplication and neofunctionalization of the ancestral diterpene synthase gene family to >400 million years ago. By contrast, the mono- and sesquiterpene synthases represent a distinct class of enzymes, not related to previously described plant terpene synthases and only distantly so to microbial-type terpene synthases. The absence of a Mg2+ binding, aspartate-rich, DDXXD motif places these enzymes in a noncanonical family of terpene synthases.

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.

As increasingly large amounts of data from genome and other sequencing projects become available, new approaches are needed to determine the functions of the proteins these genes encode. We show how large-scale computational analysis can help to address this challenge by linking functional information to sequence and structural similarities using protein similarity networks. Network analyses using three functionally diverse enzyme superfamilies illustrate the use of these approaches for facile updating and comparison of available structures for a large superfamily, for creation of functional hypotheses for metagenomic sequences, and to summarize the limits of our functional knowledge about even well studied superfamilies.

The catalytic activities of three members of the amidohydrolase superfamily were discovered using amino acid substrate libraries. Bb3285 from Bordetella bronchiseptica, Gox1177 from Gluconobacter oxidans, and Sco4986 from Streptomyces coelicolor are currently annotated as d-aminoacylases or N-acetyl-d-glutamate deacetylases. These three enzymes are 22-34% identical to one another in amino acid sequence. Substrate libraries containing nearly all combinations of N-formyl-d-Xaa, N-acetyl-d-Xaa, N-succinyl-d-Xaa, and l-Xaa-d-Xaa were used to establish the substrate profiles for these enzymes. It was demonstrated that Bb3285 is restricted to the hydrolysis of N-acyl-substituted derivatives of d-glutamate. The best substrates for this enzyme are N-formyl-d-glutamate (k(cat)/K(m) = 5.8 x 10(6) M(-1) s(-1)), N-acetyl-d-glutamate (k(cat)/K(m) = 5.2 x 10(6) M(-1) s(-1)), and l-methionine-d-glutamate (k(cat)/K(m) = 3.4 x 10(5) M(-1) s(-1)). Gox1177 and Sco4986 preferentially hydrolyze N-acyl-substituted derivatives of hydrophobic d-amino acids. The best substrates for Gox1177 are N-acetyl-d-leucine (k(cat)/K(m) = 3.2 x 10(4) M(-1) s(-1)), N-acetyl-d-tryptophan (k(cat)/K(m) = 4.1 x 10(4) M(-1) s(-1)), and l-tyrosine-d-leucine (k(cat)/K(m) = 1.5 x 10(4) M(-1) s(-1)). A fourth protein, Bb2785 from B. bronchiseptica, did not have d-aminoacylase activity. The best substrates for Sco4986 are N-acetyl-d-phenylalanine and N-acetyl-d-tryptophan. The three-dimensional structures of Bb3285 in the presence of the product acetate or a potent mimic of the tetrahedral intermediate were determined by X-ray diffraction methods. The side chain of the d-glutamate moiety of the inhibitor is ion-paired to Arg-295, while the alpha-carboxylate is ion-paired with Lys-250 and Arg-376. These results have revealed the chemical and structural determinants for substrate specificity in this protein. Bioinformatic analyses of an additional approximately 250 sequences identified as members of this group suggest that there are no simple motifs that allow prediction of substrate specificity for most of these unknowns, highlighting the challenges for computational annotation of some groups of homologous proteins.

The amidohydrolase superfamily is a functionally diverse set of enzymes that catalyzes predominantly hydrolysis reactions involving sugars, nucleic acids, amino acids, and organophosphate esters. One of the most divergent members of this superfamily, uronate isomerase from Escherichia coli, catalyzes the isomerization of d-glucuronate to d-fructuronate and d-galacturonate to d-tagaturonate and is the only uronate isomerase in this organism. A gene encoding a putative uronate isomerase in Bacillus halodurans (Bh0705) was identified based on sequence similarity to uronate isomerases from other organisms. Kinetic evidence indicates that Bh0705 is relatively specific for the isomerization of d-glucuronate to d-fructuronate, confirming this functional assignment. Despite a low sequence identity to all other characterized uronate isomerases, phylogenetic and network-based analysis suggests that a second gene in this organism, Bh0493, is also a uronate isomerase, although it is an outlier in the group, with

The rates of hydrolysis of alpha-R-alpha-(methylthio)methylene Meldrum's acids (8-R with R = H, Me, Et, s-Bu, and t-Bu) were determined in basic and acidic solution in 50% DMSO-50% water (v/v) at 20 degrees C. In basic solution (KOH), nucleophilic attack to form a tetrahedral intermediate (T(OH)-) is rate limiting for all substrates (k1(OH)). In acidic solution (HCl) and at intermediate pH values (acetate buffers), water attack (k1(H2O) is rate limiting for 8-Me, 8-Et, and 8-s-Bu; the same is presumably the case for 8-t-Bu, but rates were too slow for accurate measurements at low pH. For 8-H, water attack is rate limiting at intermediate pH but at pH4.5 MeS- departure from the tetrahedral intermediate becomes rate limiting. Our interpretation of these results is based on a reaction scheme that involves three pathways for the conversion of T(OH)- to products, two of which being unique to hydrolysis reactions and taking advantage of the acidic nature of the OH group in T(OH)-. This scheme provides an explanation why even at high [KOH] T(OH)- does not accumulate to detectable levels even though the equilibrium for OH- addition to 8-R is expected to favor T(OH)-, and why at low pH water attack is rate limiting for R = Me, Et, s-Bu, and t-Bu but leaving group departure becomes rate limiting with the sterically small R = H. The trend in the k1(OH) and k1(H2O) indicates increasing steric crowding at the transition state with increasing size of R, but this effect is partially offset by a sterically induced twisting of the C=C double bond in 8-R which leads to its elongation and makes the substrate less stable and hence more reactive. Our computational results suggest that this effect becomes particularly pronounced for R = t-Bu and explains why k1(OH) for 8-t-Bu is somewhat higher than for the less crowded 8-s-Bu.

The Structure-Function Linkage Database (SFLD) is a web-accessible database designed to link enzyme sequence, structure and molecular function (Akiva et al., 2014; Pegg et al., 2006). Within the database, enzyme sequences are classified hierarchically into superfamilies, subgroups, and families (Figure 2.10.1). At the top of the hierarchy, distantly related enzymes within the same superfamily catalyze different overall reactions but are linked by a pattern of conserved amino acid residues in the active site that mediate a common chemical capability such as a partial reaction (Gerlt and Babbitt, 2001). At the bottom of the hierarchy, enzymes within the same family exhibit more sequence and structural similarities than proteins at the superfamily or subgroup level, and catalyze the same overall reaction via the same mechanism, mediated by a common set of catalytic residues. Figure 2.10.1 SFLD classification hierarchy. Sequences of unknown function are classified at a given level of the hierarchy only if sufficient evidence exists to support that classification. A sequence can be a member of a superfamily or subgroup even if its specific ... The SFLD also provides sequence similarity networks, useful for providing large-scale summaries of the relationships within large groups of related enzymes, and for making hypotheses regarding the function of uncharacterized proteins. Such hypotheses can be further investigated using SFLD data and tools, for example, the mapping of specific chemical capabilities to specific sequence and structural motifs. (See Basic Protocol.) Queries are currently limited to twelve superfamilies in the core SFLD (networks and detailed curation information available) and thirty-five additional superfamilies in the extended SFLD (networks and light curation information available). Additional superfamilies will be added as they can be curated.

The prediction of protein function from structure or sequence data remains a problem best addressed by leveraging information available from previously determined structure-function relationships. In the case of enzymes, the study of mechanistically diverse superfamilies can provide a rich source of structure-function information useful in functional determination and enzyme engineering. To access these relationships using a computational resource, several issues must be addressed regarding the representation of enzyme function, the organization of structure-function relationships in the superfamily context, the handling of misannotations, and reliability of classifications and evidence. We discuss here our approaches to solving these problems in the development of a Structure-Function Linkage Database (SFLD) (online at http://sfld.rbvi.ucsf.edu).

Superfamily and family analyses provide an effective tool for the functional classification of proteins, but must be automated for use on large datasets. We describe a 'gold standard' set of enzyme superfamilies, clustered according to specific sequence, structure, and functional criteria, for use in the validation of family and superfamily clustering methods. The gold standard set represents four fold classes and differing clustering difficulties, and includes five superfamilies, 91 families, 4,887 sequences and 282 structures.