InterPro in 2019: improving coverage, classification and access to protein sequence annotations.

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.

Structural Basis for the Asymmetry of a 4-Oxalocrotonate Tautomerase Trimer.

Tautomerase superfamily (TSF) members are constructed from a single ß-α-ß unit or two consecutively joined ß-α-ß units. This pattern prevails throughout the superfamily consisting of more than 11000 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 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.

Structural, Kinetic, and Mechanistic Analysis of an Asymmetric 4-Oxalocrotonate Tautomerase Trimer.

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 ß-α-ß unit (homo- and heterohexamer) or two consecutively joined ß-α-ß 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 Å resolution). The asymmetric arrangement of the trimer is not due to the fusion of the two ß-α-ß 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.

Molecular Diversity of Terpene Synthases in the Liverwort Marchantia polymorpha.

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.

Covalent docking predicts substrates for haloalkanoate dehalogenase superfamily phosphatases.

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.

New insights about enzyme evolution from large scale studies of sequence and structure relationships.

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.

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.

Inference of functional properties from large-scale analysis of enzyme superfamilies.

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.

Annotation error in public databases: misannotation of molecular function in enzyme superfamilies.

Due to the rapid release of new data from genome sequencing projects, the majority of protein sequences in public databases have not been experimentally characterized; rather, sequences are annotated using computational analysis. The level of misannotation and the types of misannotation in large public databases are currently unknown and have not been analyzed in depth. We have investigated the misannotation levels for molecular function in four public protein sequence databases (UniProtKB/Swiss-Prot, GenBank NR, UniProtKB/TrEMBL, and KEGG) for a model set of 37 enzyme families for which extensive experimental information is available. The manually curated database Swiss-Prot shows the lowest annotation error levels (close to 0% for most families); the two other protein sequence databases (GenBank NR and TrEMBL) and the protein sequences in the KEGG pathways database exhibit similar and surprisingly high levels of misannotation that average 5%-63% across the six superfamilies studied. For 10 of the 37 families examined, the level of misannotation in one or more of these databases is >80%. Examination of the NR database over time shows that misannotation has increased from 1993 to 2005. The types of misannotation that were found fall into several categories, most associated with "overprediction" of molecular function. These results suggest that misannotation in enzyme superfamilies containing multiple families that catalyze different reactions is a larger problem than has been recognized. Strategies are suggested for addressing some of the systematic problems contributing to these high levels of misannotation.

A strategy for large-scale comparison of evolutionary- and reaction-based classifications of enzyme function.

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).

Target selection and annotation for the structural genomics of the amidohydrolase and enolase superfamilies.

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.

Atlas of the Radical SAM Superfamily: Divergent Evolution of Function Using a "Plug and Play" Domain.

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.

Biocuration in the structure-function linkage database: the anatomy of a superfamily.

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 URL: http://sfld.rbvi.ucsf.edu/.

An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.

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.

Acid-Catalyzed Breakdown of Alkoxide and Thiolate Ion Adducts of Benzylidene Meldrum's Acid, Methoxybenzylidene Meldrum's Acid and Thiomethoxybenzylidene Meldrum's Acid.

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.

Spectroscopic and kinetic evidence for an accumulating intermediate in an SNV reaction with amine nucleophiles. Reaction of methyl beta-methylthio-alpha-nitrocinnamate with piperidine and morpholine.

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.

Kinetics of the deprotonation of methylnitroacetate by amines: unusually high intrinsic rate constants for a nitroalkane.

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 gold standard set of mechanistically diverse enzyme superfamilies.

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.

Hydrolysis of alpha-alkyl-alpha-(methylthio)methylene Meldrum's acids. A kinetic and computational investigation of steric effects.

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 pH < 4.5 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.