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/.     

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).     

Interaction interfaces of protein domains are not topologically equivalent across families within superfamilies: Implications for metabolic and signaling pathways

Using a data set of aligned protein domain superfamilies of known three-dimensional structure, we compared the location of interdomain interfaces on the tertiary folds between members of distantly related protein domain superfamilies. The data set analyzed is comprised of interdomain interfaces, with domains occurring within a polypeptide chain and those between two polypeptide chains. We observe that, in general, the interfaces between protein domains are formed entirely in different locations on the tertiary folds in such pairs. This variation in the location of interface happens in protein domains involved in a wide range of functions, such as enzymes, adapters, and domains that bind protein ligands, or cofactors. While basic biochemical functionality is preserved at the domain superfamily level, the effect of biochemical function on protein assemblies is different in these protein domains related by superfamily. The divergence between proteins, in most cases, is coupled with domain recruitment, with different modes of interaction with the recruited domain. This is in complete contrast to the observation that in closely related homologous protein domains, almost always the interaction interfaces are topologically equivalent. In a small subset of interacting domains within proteins related by remote homology, we observe that the relative positioning of domains with respect to one another is preserved. Based on the analysis of multidomain proteins of known or unknown structure, we suggest that variation in protein-protein interactions in members within a superfamily could serve as diverging points in otherwise parallel metabolic or signaling pathways. We discuss a few representative cases of diverging pathways involving domains in a superfamily.     

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.     

Evolution of enzyme superfamilies

Enzyme evolution is often constrained by aspects of catalysis. Sets of homologous proteins that catalyze different overall reactions but share an aspect of catalysis, such as a common partial reaction, are called mechanistically diverse superfamilies. The common mechanistic steps and structural characteristics of several of these superfamilies, including the enolase, Nudix, amidohydrolase, and haloacid dehalogenase superfamilies have been characterized. In addition, studies of mechanistically diverse superfamilies are helping to elucidate mechanisms of functional diversification, such as catalytic promiscuity. Understanding how enzyme superfamilies evolve is vital for accurate genome annotation, predicting protein functions, and protein engineering.     

Functional recycling of C2 domains throughout evolution: a comparative study of synaptotagmin, protein kinase C and phospholipase C by sequence, structural and modelling approaches

The C2 domain is one of the most frequent and widely distributed calcium-binding motifs. Its structure comprises an eight-stranded beta-sandwich with two structural types as if the result of a circular permutation. Combining sequence, structural and modelling information, we have explored, at different levels of granularity, the functional characteristics of several families of C2 domains. At the coarsest level, the similarity correlates with key structural determinants of the C2 domain fold and, at the finest level, with the domain architecture of the proteins containing them, highlighting the functional diversity between the various sub-families. The functional diversity appears as different conserved surface patches throughout this common fold. In some cases, these patches are related to substrate-binding sites whereas in others they correspond to interfaces of presumably permanent interaction between other domains within the same polypeptide chain. For those related to substrate-binding sites, the predictions overlap with biochemical data in addition to providing some novel observations. For those acting as protein-protein interfaces, our modelling analysis suggests that slight variations between families are a result of not only complementary adaptations in the interfaces involved but also different domain architecture. In the light of the sequence and structural genomic projects, the work presented here shows that modelling approaches along with careful sub-typing of protein families will be a powerful combination for a broader coverage in proteomics.     

Detailed analysis of function divergence in a large and diverse domain superfamily: toward a refined protocol of function classification

Some superfamilies contain large numbers of protein domains with very different functions. The ability to refine the functional classification of domains within these superfamilies is necessary for better understanding the evolution of functions and to guide function prediction of new relatives. To achieve this, a suitable starting point is the detailed analysis of functional divisions and mechanisms of functional divergence in a single superfamily. Here, we present such a detailed analysis in the superfamily of HUP domains. A biologically meaningful functional classification of HUP domains is obtained manually. Mechanisms of function diversification are investigated in detail using this classification. We observe that structural motifs play an important role in shaping broad functional divergence, whereas residue-level changes shape diversity at a more specific level. In parallel we examine the ability of an automated protocol to capture the biologically meaningful classification, with a view to automatically extending this classification in the future.     

Assigning genomic sequences to CATH

We report the latest release (version 1.6) of the CATH protein domains database (http://www.biochem.ucl. ac.uk/bsm/cath ). This is a hierarchical classification of 18 577 domains into evolutionary families and structural groupings. We have identified 1028 homo-logous superfamilies in which the proteins have both structural, and sequence or functional similarity. These can be further clustered into 672 fold groups and 35 distinct architectures. Recent developments of the database include the generation of 3D templates for recognising structural relatives in each fold group, which has led to significant improvements in the speed and accuracy of updating the database and also means that less manual validation is required. We also report the establishment of the CATH-PFDB (Protein Family Database), which associates 1D sequences with the 3D homologous superfamilies. Sequences showing identifiable homology to entries in CATH have been extracted from GenBank using PSI-BLAST. A CATH-PSIBLAST server has been established, which allows you to scan a new sequence against the database. The CATH Dictionary of Homologous Superfamilies (DHS), which contains validated multiple structural alignments annotated with consensus functional information for evolutionary protein superfamilies, has been updated to include annotations associated with sequence relatives identified in GenBank. The DHS is a powerful tool for considering the variation of functional properties within a given CATH superfamily and in deciding what functional properties may be reliably inherited by a newly identified relative.     

Exploring functional roles of multibinding protein interfaces

Cellular processes are highly interconnected and many proteins are shared in different pathways. Some of these shared proteins or protein families may interact with diverse partners using the same interface regions; such multibinding proteins are the subject of our study. The main goal of our study is to attempt to decipher the mechanisms of specific molecular recognition of multiple diverse partners by promiscuous protein regions. To address this, we attempt to analyze the physicochemical properties of multibinding interfaces and highlight the major mechanisms of functional switches realized through multibinding. We find that only 5% of protein families in the structure database have multibinding interfaces, and multibinding interfaces do not show any higher sequence conservation compared with the background interface sites. We highlight several important functional mechanisms utilized by multibinding families. (a) Overlap between different functional pathways can be prevented by the switches involving nearby residues of the same interfacial region. (b) Interfaces can be reused in pathways where the substrate should be passed from one protein to another sequentially. (c) The same protein family can develop different specificities toward different binding partners reusing the same interface; and finally, (d) inhibitors can attach to substrate binding sites as substrate mimicry and thereby prevent substrate binding.     

The cadherin superfamily database

The cadherin superfamily is a large protein family with diverse structures and functions. Because of this diversity and the growing biological interest in cell adhesion and signaling processes, in which many members of the cadherin superfamily play a crucial role, it is becoming increasingly important to develop tools to manage, distribute and analyze sequences in this protein family. Current profile and motif databases classify protein sequences into a broad spectrum of protein superfamilies, however to provide a more specific functional annotation, the next step should include classification of subfamilies of these protein superfamilies. Here, we present a tool that classified greater than 90% of the proteins belonging to the cadherin superfamily found in the SWISS PROT database. Therefore, for most members of the cadherin superfamily, this tool can assist in adding more specific functional annotations than can be achieved with current profile and motif databases. Finally, the classification tool and the results of our analysis were integrated into a web-accessible database (http://calcium.uhnres. utoronto.ca/cadherin).     

Emerging structure of the nicotinic acetylcholine receptors

The conversion of acetylcholine binding into ion conduction across the membrane is becoming more clearly understood in terms of the structure of the receptor and its transitions. A high-resolution structure of a protein that is homologous to the extracellular domain of the receptor has revealed the binding sites and subunit interfaces in great detail. Although the structures of the membrane and cytoplasmic domains are less well determined, the channel lining and the determinants of selectivity have been mapped. The location and structure of the gates, and the coupling between binding sites and gates, remain to be established.     

Accurate prediction of interfacial residues in two‐domain proteins using evolutionary information: Implications for three‐dimensional modeling

With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure–function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two‐domain proteins. We also use information from the three‐dimensional structures of individual domains of two‐domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (～85%) and specific (～95%) to the domain–domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain–domain interaction, rigid‐body docking was able to provide us with accurate full‐length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. Proteins 2014; 82:1219–1234. © 2013 Wiley Periodicals, Inc.     

Relationships between functional subclasses and information contained in active‐site and ligand‐binding residues in diverse superfamilies

To investigate the relationships between functional subclasses and sequence and structural information contained in the active‐site and ligand‐binding residues (LBRs), we performed a detailed analysis of seven diverse enzyme superfamilies: aldolase class I, TIM‐barrel glycosidases, α/β‐hydrolases, P‐loop containing nucleotide triphosphate hydrolases, collagenase, Zn peptidases, and glutamine phosphoribosylpyrophosphate, subunit 1, domain 1. These homologous superfamilies, as defined in CATH, were selected from the enzyme catalytic‐mechanism database. We defined active‐site and LBRs based solely on the literature information and complex structures in the Protein Data Bank. From a structure‐based multiple sequence alignment for each CATH homologous superfamily, we extracted subsequences consisting of the aligned positions that were used as an active‐site or a ligand‐binding site by at least one sequence. Using both the subsequences and full‐length alignments, we performed cluster analysis with three sequence distance measures. We showed that the cluster analysis using the subsequences was able to detect functional subclasses more accurately than the clustering using the full‐length alignments. The subsequences determined by only the literature information and complex structures, thus, had sufficient information to detect the functional subclasses. Detailed examination of the clustering results provided new insights into the mechanism of functional diversification for these superfamilies. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

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.     

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.     

The database of epoxide hydrolases and haloalkane dehalogenases: one structure, many functions

The epoxide hydrolases and haloalkane dehalogenases database (EH/HD) integrates sequence and structure of a highly diverse protein family, including mainly the Asp-hydrolases of EHs and HDs but also proteins, such as Ser-hydrolases non-heme peroxidases, prolyl iminopetidases and 2-hydroxymuconic semialdehyde hydrolases. These proteins have a highly conserved structure, but display a remarkable diversity in sequence and function. A total of 305 protein entries were assigned to 14 homologous families, forming two superfamilies. Annotated multisequence alignments and phylogenetic trees are provided for each homologous family and superfamily. Experimentally derived structures of 19 proteins are superposed and consistently annotated. Sequence and structure of all 305 proteins were systematically analysed. Thus, deeper insight is gained into the role of a highly conserved sequence motifs and structural elements. AVAILABILITY: The EH/HD database is available at http://www.led.uni-stuttgart.de     

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.     

Functional diversity of protein C-termini: more than zipcoding?

The carboxylated (C)-terminus of proteins, which includes the single terminal alpha-carboxyl group and preceding residues, is uniquely positioned to serve as a recognition signature for a variety of cell-biological processes, including protein targeting, subcellular anchoring and the static and dynamic formation of macromolecular complexes. The terminal sequence motifs can be processed by posttranslational modifications, thereby providing a means to increase sequence diversity and to regulate interactions. Several classes of protein domains have been identified that are either designed for or are capable of interacting with protein C-termini - these include PDZ and TPR domains. The interactions between these protein domains and various terminal epitopes play an important role in specifying cell-biological functions. The combination of diversity and the plasticity of the chemistry of C-termini provides mechanisms for spatial and temporal specificity that are exploited by a variety of biological processes, ranging from specifying prokaryotic protein degradation to nucleating mammalian neuronal signaling complexes. Understanding the diverse functions of protein C-termini might also provide an important indexing criterion for functional proteomics.