Divergent evolution in enolase superfamily: strategies for assigning functions

Nature's strategies for evolving catalytic functions can be deciphered from the information contained in the rapidly expanding protein sequence databases. However, the functions of many proteins in the protein sequence and structure databases are either uncertain (too divergent to assign function based on homology) or unknown (no homologs), thereby limiting the utility of the databases. The mechanistically diverse enolase superfamily is a paradigm for understanding the structural bases for evolution of enzymatic function. We describe strategies for assigning functions to members of the enolase superfamily that should be applicable to other superfamilies.     

Functional site plasticity in domain superfamilies

We present, to our knowledge, the first quantitative analysis of functional site diversity in homologous domain superfamilies. Different types of functional sites are considered separately. Our results show that most diverse superfamilies are very plastic in terms of the spatial location of their functional sites. This is especially true for protein–protein interfaces. In contrast, we confirm that catalytic sites typically occupy only a very small number of topological locations. Small-ligand binding sites are more diverse than expected, although in a more limited manner than protein–protein interfaces. In spite of the observed diversity, our results also confirm the previously reported preferential location of functional sites. We identify a subset of homologous domain superfamilies where diversity is particularly extreme, and discuss possible reasons for such plasticity, i.e. structural diversity. Our results do not contradict previous reports of preferential co-location of sites among homologues, but rather point at the importance of not ignoring other sites, especially in large and diverse superfamilies. Data on sites exploited by different relatives, within each well annotated domain superfamily, has been made accessible from the CATH website in order to highlight versatile superfamilies or superfamilies with highly preferential sites. This information is valuable for system biology and knowledge of any constraints on protein interactions could help in understanding the dynamic control of networks in which these proteins participate. The novelty of our work lies in the comprehensive nature of the analysis – we have used a significantly larger dataset than previous studies – and the fact that in many superfamilies we show that different parts of the domain surface are exploited by different relatives for ligand/protein interactions, particularly in superfamilies which are diverse in sequence and structure, an observation not previously reported on such a large scale. This article is part of a Special Issue entitled: The emerging dynamic view of proteins: Protein plasticity in allostery, evolution and self-assembly.     

Exploring the evolution of novel enzyme functions within structurally defined protein superfamilies

In order to understand the evolution of enzyme reactions and to gain an overview of biological catalysis we have combined sequence and structural data to generate phylogenetic trees in an analysis of 276 structurally defined enzyme superfamilies, and used these to study how enzyme functions have evolved. We describe in detail the analysis of two superfamilies to illustrate different paradigms of enzyme evolution. Gathering together data from all the superfamilies supports and develops the observation that they have all evolved to act on a diverse set of substrates, whilst the evolution of new chemistry is much less common. Despite that, by bringing together so much data, we can provide a comprehensive overview of the most common and rare types of changes in function. Our analysis demonstrates on a larger scale than previously studied, that modifications in overall chemistry still occur, with all possible changes at the primary level of the Enzyme Commission (E.C.) classification observed to a greater or lesser extent. The phylogenetic trees map out the evolutionary route taken within a superfamily, as well as all the possible changes within a superfamily. This has been used to generate a matrix of observed exchanges from one enzyme function to another, revealing the scale and nature of enzyme evolution and that some types of exchanges between and within E.C. classes are more prevalent than others. Surprisingly a large proportion (71%) of all known enzyme functions are performed by this relatively small set of 276 superfamilies. This reinforces the hypothesis that relatively few ancient enzymatic domain superfamilies were progenitors for most of the chemistry required for life.     

Folding studies of immunoglobulin-like beta-sandwich proteins suggest that they share a common folding pathway.

BACKGROUND: Are folding pathways conserved in protein families? To test this explicitly and ask to what extent structure specifies folding pathways requires comparison of proteins with a common fold. Our strategy is to choose members of a highly diverse protein family with no conservation of function and little or no sequence identity, but with structures that are essentially the same. The immunoglobulin-like fold is one of the most common structural families, and is subdivided into superfamilies with no detectable evolutionary or functional relationship. RESULTS: We compared the folding of a number of immunoglobulin-like proteins that have a common structural core and found a strong correlation between folding rate and stability. The results suggest that the folding pathways of these immunoglobulin-like proteins share common features. CONCLUSIONS: This study is the first to compare the folding of structurally related proteins that are members of different superfamilies. The most likely explanation for the results is that interactions that are important in defining the structure of immunoglobulin-like proteins are also used to guide folding.     

Evolution of function in protein superfamilies, from a structural perspective

The recent growth in protein databases has revealed the functional diversity of many protein superfamilies. We have assessed the functional variation of homologous enzyme superfamilies containing two or more enzymes, as defined by the CATH protein structure classification, by way of the Enzyme Commission (EC) scheme. Combining sequence and structure information to identify relatives, the majority of superfamilies display variation in enzyme function, with 25 % of superfamilies in the PDB having members of different enzyme types. We determined the extent of functional similarity at different levels of sequence identity for 486,000 homologous pairs (enzyme/enzyme and enzyme/non-enzyme), with structural and sequence relatives included. For single and multi-domain proteins, variation in EC number is rare above 40 % sequence identity, and above 30 %, the first three digits may be predicted with an accuracy of at least 90 %. For more distantly related proteins sharing less than 30 % sequence identity, functional variation is significant, and below this threshold, structural data are essential for understanding the molecular basis of observed functional differences. To explore the mechanisms for generating functional diversity during evolution, we have studied in detail 31 diverse structural enzyme superfamilies for which structural data are available. A large number of variations and peculiarities are observed, at the atomic level through to gross structural rearrangements. Almost all superfamilies exhibit functional diversity generated by local sequence variation and domain shuffling. Commonly, substrate specificity is diverse across a superfamily, whilst the reaction chemistry is maintained. In many superfamilies, the position of catalytic residues may vary despite playing equivalent functional roles in related proteins. The implications of functional diversity within supefamilies for the structural genomics projects are discussed. More detailed information on these superfamilies is available at http://www.biochem.ucl.ac.uk/bsm/FAM-EC/.     

The Classification and Evolution of Enzyme Function

Enzymes are the proteins responsible for the catalysis of life. Enzymes sharing a common ancestor as defined by sequence and structure similarity are grouped into families and superfamilies. The molecular function of enzymes is defined as their ability to catalyze biochemical reactions; it is manually classified by the Enzyme Commission and robust approaches to quantitatively compare catalytic reactions are just beginning to appear. Here, we present an overview of studies at the interface of the evolution and function of enzymes.     

Evolutionary potential of (beta/alpha)8-barrels: functional promiscuity produced by single substitutions in the enolase superfamily

The members of the mechanistically diverse, (beta/alpha)(8)-barrel fold-containing enolase superfamily evolved from a common progenitor but catalyze different reactions using a conserved partial reaction. The molecular pathway for natural divergent evolution of function in the superfamily is unknown. We have identified single-site mutants of the (beta/alpha)(8)-barrel domains in both the l-Ala-d/l-Glu epimerase from Escherichia coli (AEE) and the muconate lactonizing enzyme II from Pseudomonas sp. P51 (MLE II) that catalyze the o-succinylbenzoate synthase (OSBS) reaction as well as the wild-type reaction. These enzymes are members of the MLE subgroup of the superfamily, share conserved lysines on opposite sides of their active sites, but catalyze acid- and base-mediated reactions with different mechanisms. A comparison of the structures of AEE and the OSBS from E. coli was used to design the D297G mutant of AEE; the E323G mutant of MLE II was isolated from directed evolution experiments. Although neither wild-type enzyme catalyzes the OSBS reaction, both mutants complement an E. coli OSBS auxotroph and have measurable levels of OSBS activity. The analogous mutations in the D297G mutant of AEE and the E323G mutant of MLE II are each located at the end of the eighth beta-strand of the (beta/alpha)(8)-barrel and alter the ability of AEE and MLE II to bind the substrate of the OSBS reaction. The substitutions relax the substrate specificity, thereby allowing catalysis of the mechanistically diverse OSBS reaction with the assistance of the active site lysines. The generation of functionally promiscuous and mechanistically diverse enzymes via single-amino acid substitutions likely mimics the natural divergent evolution of enzymatic activities and also highlights the utility of the (beta/alpha)(8)-barrel as a scaffold for new function.     

FLORA: A Novel Method to Predict Protein Function from Structure in Diverse Superfamilies

Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues. Here, we present a novel method (FLORA) that automatically generates structural motifs associated with different functional sub-families (FSGs) within functionally diverse domain superfamilies. Templates are created purely on the basis of their specificity for a given FSG, and the method makes no prior prediction of functional sites, nor assumes specific physico-chemical properties of residues. FLORA is able to accurately discriminate between homologous domains with different functions and substantially outperforms (a 2–3 fold increase in coverage at low error rates) popular structure comparison methods and a leading function prediction method. We benchmark FLORA on a large data set of enzyme superfamilies from all three major protein classes (α, β, αβ) and demonstrate the functional relevance of the motifs it identifies. We also provide novel predictions of enzymatic activity for a large number of structures solved by the Protein Structure Initiative. Overall, we show that FLORA is able to effectively detect functionally similar protein domain structures by purely using patterns of structural conservation of all residues.     

Zebra: a web server for bioinformatic analysis of diverse protein families

During evolution of proteins from a common ancestor, one functional property can be preserved while others can vary leading to functional diversity. A systematic study of the corresponding adaptive mutations provides a key to one of the most challenging problems of modern structural biology – understanding the impact of amino acid substitutions on protein function. The subfamily-specific positions (SSPs) are conserved within functional subfamilies but are different between them and, therefore, seem to be responsible for functional diversity in protein superfamilies. Consequently, a corresponding method to perform the bioinformatic analysis of sequence and structural data has to be implemented in the common laboratory practice to study the structure–function relationship in proteins and develop novel protein engineering strategies. This paper describes Zebra web server – a powerful remote platform that implements a novel bioinformatic analysis algorithm to study diverse protein families. It is the first application that provides specificity determinants at different levels of functional classification, therefore addressing complex functional diversity of large superfamilies. Statistical analysis is implemented to automatically select a set of highly significant SSPs to be used as hotspots for directed evolution or rational design experiments and analyzed studying the structure–function relationship. Zebra results are provided in two ways – (1) as a single all-in-one parsable text file and (2) as PyMol sessions with structural representation of SSPs. Zebra web server is available at http://biokinet.belozersky.msu.ru/zebra.     

Fragment peptide library for classification and functional prediction of proteins

From protein sequence comparison data found in the literature, a library was organized using peptide fragment sequences which are common to related proteins. Each of the fragments was then examined for its occurrence in all the protein superfamilies defined by the NBRF-PIR data base. We have selected those fragment peptides that appear exclusively in one or a few superfamilies, and thus made a library of fragment peptides that characterize specific superfamilies. Such characteristic peptides are, in general, five to seven residues long and contain unusually high proportions of glycine and cysteine. This collection is a useful resource for the classification and functional prediction of protein molecules.     

Superfamily active site templates

We show that three-dimensional signatures consisting of only a few functionally important residues can be diagnostic of membership in superfamilies of enzymes. Using the enolase superfamily as a model system, we demonstrate that such a signature, or template, can identify superfamily members in structural databases with high sensitivity and specificity. This is remarkable because superfamilies can be highly diverse, with members catalyzing many different overall reactions; the unifying principle can be a conserved partial reaction or chemical capability. Our definition of a superfamily thus hinges on the disposition of residues involved in a conserved function, rather than on fold similarity alone. A clear advantage of basing structure searches on such active site templates rather than on fold similarity is the specificity with which superfamilies with distinct functional characteristics can be identified within a large set of proteins with the same fold, such as the (beta/alpha)8 barrels. Preliminary results are presented for an additional group of enzymes with a different fold, the haloacid dehalogenase superfamily, suggesting that this approach may be generally useful for assigning reading frames of unknown function to specific superfamilies and thereby allowing inference of some of their functional properties.     

Mechanistic similarity and diversity among the guanidine-modifying members of the pentein superfamily

The pentein superfamily is a mechanistically diverse superfamily encompassing both noncatalytic proteins and enzymes that catalyze hydrolase, dihydrolase and amidinotransfer reactions on guanidine substrates. Despite generally low sequence identity, they possess a conserved structural fold and display common mechanistic themes in catalysis. The structurally characterized catalytic penteins possess a conserved core of residues that include a Cys, His and two polar, guanidine-binding residues. All known catalytic penteins use the core Cys to attack the substrate's guanidine moiety to form a covalent thiouronium adduct and all cleave one or more of the guanidine C―N bonds. The mechanistic information compiled to date supports the hypothesis that this superfamily may have evolved divergently from a catalytically promiscuous ancestor.     

Structural motif of phosphate-binding site common to various protein superfamilies: all-against-all structural comparison of protein-mononucleotide complexes

In order to search for a common structural motif in the phosphate-binding sites of protein-mononucleotide complexes, we investigated the structural variety of phosphate-binding schemes by an all-against-all comparison of 491 binding sites found in the Protein Data Bank. We found four frequently occurring structural motifs composed of protein atoms interacting with phosphate groups, each of which appears in different protein superfamilies with different folds. The most frequently occurring motif, which we call the structural P-loop, is shared by 13 superfamilies and is characterized by a four-residue fragment, GXXX, interacting with a phosphate group through the backbone atoms. Various sequence motifs, including Walker's A motif or the P-loop, turn out to be a structural P-loop found in a few specific superfamilies. The other three motifs are found in pairs of superfamilies: protein kinase and glutathione synthetase ATPase domain like, actin-like ATPase domain and nucleotidyltransferase, and FMN-linked oxidoreductase and PRTase.     

GeMMA: functional subfamily classification within superfamilies of predicted protein structural domains

GeMMA (Genome Modelling and Model Annotation) is a new approach to automatic functional subfamily classification within families and superfamilies of protein sequences. A major advantage of GeMMA is its ability to subclassify very large and diverse superfamilies with tens of thousands of members, without the need for an initial multiple sequence alignment. Its performance is shown to be comparable to the established high-performance method SCI-PHY. GeMMA follows an agglomerative clustering protocol that uses existing software for sensitive and accurate multiple sequence alignment and profile–profile comparison. The produced subfamilies are shown to be equivalent in quality whether whole protein sequences are used or just the sequences of component predicted structural domains. A faster, heuristic version of GeMMA that also uses distributed computing is shown to maintain the performance levels of the original implementation. The use of GeMMA to increase the functional annotation coverage of functionally diverse Pfam families is demonstrated. It is further shown how GeMMA clusters can help to predict the impact of experimentally determining a protein domain structure on comparative protein modelling coverage, in the context of structural genomics.     

Conformational characterization of disulfide bonds: A tool for protein classification

Background

Throughout evolution, mutations in particular regions of some protein structures have resulted in extra covalent bonds that increase the overall robustness of the fold: disulfide bonds. The two strategically placed cysteines can also have a more direct role in protein function, either by assisting thiol or disulfide exchange, or through allosteric effects. In this work, we verified how the structural similarities between disulfides can reflect functional and evolutionary relationships between different proteins. We analyzed the conformational patterns of the disulfide bonds in a set of disulfide-rich proteins that included twelve SCOP superfamilies: thioredoxin-like and eleven superfamilies containing small disulfide-rich proteins (SDP).

Results

The twenty conformations considered in the present study were characterized by both structural and energetic parameters. The corresponding frequencies present diverse patterns for the different superfamilies. The least-strained conformations are more abundant for the SDP superfamilies, while the “catalytic” +/−RHook is dominant for the thioredoxin-like superfamily. The “allosteric” -RHSaple is moderately abundant for BBI, Crisp and Thioredoxin-like superfamilies and less frequent for the remaining superfamilies. Using a hierarchical clustering analysis we found that the twelve superfamilies were grouped in biologically significant clusters.

Conclusions

In this work, we carried out an extensive statistical analysis of the conformational motifs for the disulfide bonds present in a set of disulfide-rich proteins. We show that the conformational patterns observed in disulfide bonds are sufficient to group proteins that share both functional and structural patterns and can therefore be used as a criterion for protein classification.     

Structural diversity of domain superfamilies in the CATH database

The CATH database of domain structures has been used to explore the structural variation of homologous domains in 294 well populated domain structure superfamilies, each containing at least three sequence diverse relatives. Our analyses confirm some previously detected trends relating sequence divergence to structural variation but for a much larger dataset and in some superfamilies the new data reveal exceptional structural variation. Use of a new algorithm (2DSEC) to analyse variability in secondary structure compositions across a superfamily sheds new light on how structures evolve. 2DSEC detects inserted secondary structures that embellish the core of conserved secondary structures found throughout the superfamily. Analysis showed that for 56% of highly populated superfamilies (>9 sequence diverse relatives), there are twofold or more increases in the numbers of secondary structures in some relatives. In some families fivefold increases occur, sometimes modifying the fold of the domain. Manual inspection of secondary structure insertions or embellishments in 48 particularly variable superfamilies revealed that although these insertions were usually discontiguous in the sequence they were often co-located in 3D resulting in a larger structural motif that often modified the geometry of the active site or the surface conformation promoting diverse domain partnerships and protein interactions. These observations, supported by automatic analysis of all well populated CATH families, suggest that accretion of small secondary structure insertions may provide a simple mechanism for evolving new functions in diverse relatives. Some layered domain architectures (e.g. mainly-beta and alpha-beta sandwiches) that recur highly in the genomes more frequently exploit these types of embellishments to modify function. In these architectures, aggregation occurs most often at the edges, top or bottom of the beta-sheets. Information on structural variability across domain superfamilies has been made available through the CATH Dictionary of Homologous Structures (DHS).     

Evolution of function in (beta/alpha)8-barrel enzymes

The (beta/alpha)(8)-barrel is the most common fold in structurally characterized enzymes. Whether the functionally diverse enzymes that share this fold are the products of either divergent or convergent evolution (or both) is an unresolved question that will probably be answered as the sequence databases continue to expand. Recent work has examined natural, designed, and directed evolution of function in several superfamilies of (beta/alpha)(8)-barrel containing enzymes.     

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.