Genome3D: exploiting structure to help users understand their sequences.

Genome3D (http://www.genome3d.eu) is a collaborative resource that provides predicted domain annotations and structural models for key sequences. Since introducing Genome3D in a previous NAR paper, we have substantially extended and improved the resource. We have annotated representatives from Pfam families to improve coverage of diverse sequences and added a fast sequence search to the website to allow users to find Genome3D-annotated sequences similar to their own. We have improved and extended the Genome3D data, enlarging the source data set from three model organisms to 10, and adding VIVACE, a resource new to Genome3D. We have analysed and updated Genome3D's SCOP/CATH mapping. Finally, we have improved the superposition tools, which now give users a more powerful interface for investigating similarities and differences between structural models.

SCOP2 prototype: a new approach to protein structure mining.

We present a prototype of a new structural classification of proteins, SCOP2 (http://scop2.mrc-lmb.cam.ac.uk/), that we have developed recently. SCOP2 is a successor to the Structural Classification of Proteins (SCOP, http://scop.mrc-lmb.cam.ac.uk/scop/) database. Similarly to SCOP, the main focus of SCOP2 is to organize structurally characterized proteins according to their structural and evolutionary relationships. SCOP2 was designed to provide a more advanced framework for protein structure annotation and classification. It defines a new approach to the classification of proteins that is essentially different from SCOP, but retains its best features. The SCOP2 classification is described in terms of a directed acyclic graph in which nodes form a complex network of many-to-many relationships and are represented by a region of protein structure and sequence. The new classification project is expected to ensure new advances in the field and open new areas of research.

Genome3D: a UK collaborative project to annotate genomic sequences with predicted 3D structures based on SCOP and CATH domains.

Genome3D, available at http://www.genome3d.eu, is a new collaborative project that integrates UK-based structural resources to provide a unique perspective on sequence-structure-function relationships. Leading structure prediction resources (DomSerf, FUGUE, Gene3D, pDomTHREADER, Phyre and SUPERFAMILY) provide annotations for UniProt sequences to indicate the locations of structural domains (structural annotations) and their 3D structures (structural models). Structural annotations and 3D model predictions are currently available for three model genomes (Homo sapiens, E. coli and baker's yeast), and the project will extend to other genomes in the near future. As these resources exploit different strategies for predicting structures, the main aim of Genome3D is to enable comparisons between all the resources so that biologists can see where predictions agree and are therefore more trusted. Furthermore, as these methods differ in whether they build their predictions using CATH or SCOP, Genome3D also contains the first official mapping between these two databases. This has identified pairs of similar superfamilies from the two resources at various degrees of consensus (532 bronze pairs, 527 silver pairs and 370 gold pairs).

Evolution of oligomeric state through geometric coupling of protein interfaces.

Oligomerization plays an important role in the function of many proteins. Thus, understanding, predicting, and, ultimately, engineering oligomerization presents a long-standing interest. From the perspective of structural biology, protein-protein interactions have mainly been analyzed in terms of the biophysical nature and evolution of protein interfaces. Here, our aim is to quantify the importance of the larger structural context of protein interfaces in protein interaction evolution. Specifically, we ask to what extent intersubunit geometry affects oligomerization state. We define a set of structural parameters describing the overall geometry and relative positions of interfaces of homomeric complexes with different oligomeric states. This allows us to quantify the contribution of direct sequence changes in interfaces versus indirect changes outside the interface that affect intersubunit geometry. We find that such indirect, or allosteric mutations affecting intersubunit geometry via indirect mechanisms are as important as interface sequence changes for evolution of oligomeric states.

SUPERFAMILY 1.75 including a domain-centric gene ontology method.

The SUPERFAMILY resource provides protein domain assignments at the structural classification of protein (SCOP) superfamily level for over 1400 completely sequenced genomes, over 120 metagenomes and other gene collections such as UniProt. All models and assignments are available to browse and download at http://supfam.org. A new hidden Markov model library based on SCOP 1.75 has been created and a previously ignored class of SCOP, coiled coils, is now included. Our scoring component now uses HMMER3, which is in orders of magnitude faster and produces superior results. A cloud-based pipeline was implemented and is publicly available at Amazon web services elastic computer cloud. The SUPERFAMILY reference tree of life has been improved allowing the user to highlight a chosen superfamily, family or domain architecture on the tree of life. The most significant advance in SUPERFAMILY is that now it contains a domain-based gene ontology (GO) at the superfamily and family levels. A new methodology was developed to ensure a high quality GO annotation. The new methodology is general purpose and has been used to produce domain-based phenotypic ontologies in addition to GO.

SUPERFAMILY--sophisticated comparative genomics, data mining, visualization and phylogeny.

SUPERFAMILY provides structural, functional and evolutionary information for proteins from all completely sequenced genomes, and large sequence collections such as UniProt. Protein domain assignments for over 900 genomes are included in the database, which can be accessed at http://supfam.org/. Hidden Markov models based on Structural Classification of Proteins (SCOP) domain definitions at the superfamily level are used to provide structural annotation. We recently produced a new model library based on SCOP 1.73. Family level assignments are also available. From the web site users can submit sequences for SCOP domain classification; search for keywords such as superfamilies, families, organism names, models and sequence identifiers; find over- and underrepresented families or superfamilies within a genome relative to other genomes or groups of genomes; compare domain architectures across selections of genomes and finally build multiple sequence alignments between Protein Data Bank (PDB), genomic and custom sequences. Recent extensions to the database include InterPro abstracts and Gene Ontology terms for superfamiles, taxonomic visualization of the distribution of families across the tree of life, searches for functionally similar domain architectures and phylogenetic trees. The database, models and associated scripts are available for download from the ftp site.

Genomic and structural aspects of protein evolution.

It has been known for more than 35 years that, during evolution, new proteins are formed by gene duplications, sequence and structural divergence and, in many cases, gene combinations. The genome projects have produced complete, or almost complete, descriptions of the protein repertoires of over 600 distinct organisms. Analyses of these data have dramatically increased our understanding of the formation of new proteins. At the present time, we can accurately trace the evolutionary relationships of about half the proteins found in most genomes, and it is these proteins that we discuss in the present review. Usually, the units of evolution are protein domains that are duplicated, diverge and form combinations. Small proteins contain one domain, and large proteins contain combinations of two or more domains. Domains descended from a common ancestor are clustered into superfamilies. In most genomes, the net growth of superfamily members means that more than 90% of domains are duplicates. In a section on domain duplications, we discuss the number of currently known superfamilies, their size and distribution, and superfamily expansions related to biological complexity and to specific lineages. In a section on divergence, we describe how sequences and structures diverge, the changes in stability produced by acceptable mutations, and the nature of functional divergence and selection. In a section on domain combinations, we discuss their general nature, the sequential order of domains, how combinations modify function, and the extraordinary variety of the domain combinations found in different genomes. We conclude with a brief note on other forms of protein evolution and speculations of the origins of the duplication, divergence and combination processes.

Data growth and its impact on the SCOP database: new developments.

The Structural Classification of Proteins (SCOP) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. The SCOP hierarchy comprises the following levels: Species, Protein, Family, Superfamily, Fold and Class. While keeping the original classification scheme intact, we have changed the production of SCOP in order to cope with a rapid growth of new structural data and to facilitate the discovery of new protein relationships. We describe ongoing developments and new features implemented in SCOP. A new update protocol supports batch classification of new protein structures by their detected relationships at Family and Superfamily levels in contrast to our previous sequential handling of new structural data by release date. We introduce pre-SCOP, a preview of the SCOP developmental version that enables earlier access to the information on new relationships. We also discuss the impact of worldwide Structural Genomics initiatives, which are producing new protein structures at an increasing rate, on the rates of discovery and growth of protein families and superfamilies. SCOP can be accessed at http://scop.mrc-lmb.cam.ac.uk/scop.

The SUPERFAMILY database in 2007: families and functions.

The SUPERFAMILY database provides protein domain assignments, at the SCOP 'superfamily' level, for the predicted protein sequences in over 400 completed genomes. A superfamily groups together domains of different families which have a common evolutionary ancestor based on structural, functional and sequence data. SUPERFAMILY domain assignments are generated using an expert curated set of profile hidden Markov models. All models and structural assignments are available for browsing and download from http://supfam.org. The web interface includes services such as domain architectures and alignment details for all protein assignments, searchable domain combinations, domain occurrence network visualization, detection of over- or under-represented superfamilies for a given genome by comparison with other genomes, assignment of manually submitted sequences and keyword searches. In this update we describe the SUPERFAMILY database and outline two major developments: (i) incorporation of family level assignments and (ii) a superfamily-level functional annotation. The SUPERFAMILY database can be used for general protein evolution and superfamily-specific studies, genomic annotation, and structural genomics target suggestion and assessment.

The generation of new protein functions by the combination of domains.

During evolution, many new proteins have been formed by the process of gene duplication and combination. The genes involved in this process usually code for whole domains. Small proteins contain one domain; medium and large proteins contain two or more domains. We have compared homologous domains that occur in both one-domain proteins and multidomain proteins. We have determined (1) how the functions of the individual domains in the multidomain proteins combine to produce their overall functions and (2) the extent to which these functions are similar to those in the one-domain homologs. We describe how domain combinations increase the specificity of enzymes; act as links between domains that have functional roles; regulate activity; combine within one chain functions that can act either independently, in concert or in new contexts; and provide the structural framework for the evolution of entirely new functions.

Divergence of interdomain geometry in two-domain proteins.

For homologous protein chains composed of two domains, we have determined the extent to which they conserve (1) their interdomain geometry and (2) the molecular structure of the domain interface. This work was carried out on 128 unique two-domain architectures. Of the 128, we find 75 conserve their interdomain geometry and the structure of their domain interface; 5 conserve their interdomain geometry but not the structure of their interface; and 48 have variable geometries and divergent interface structure. We describe how different types of interface changes or the absence of an interface is responsible for these differences in geometry. Variable interdomain geometries can be found in homologous structures with high sequence identities (70%).

Protein family expansions and biological complexity.

During the course of evolution, new proteins are produced very largely as the result of gene duplication, divergence and, in many cases, combination. This means that proteins or protein domains belong to families or, in cases where their relationships can only be recognised on the basis of structure, superfamilies whose members descended from a common ancestor. The size of superfamilies can vary greatly. Also, during the course of evolution organisms of increasing complexity have arisen. In this paper we determine the identity of those superfamilies whose relative sizes in different organisms are highly correlated to the complexity of the organisms. As a measure of the complexity of 38 uni- and multicellular eukaryotes we took the number of different cell types of which they are composed. Of 1,219 superfamilies, there are 194 whose sizes in the 38 organisms are strongly correlated with the number of cell types in the organisms. We give outline descriptions of these superfamilies. Half are involved in extracellular processes or regulation and smaller proportions in other types of activity. Half of all superfamilies have no significant correlation with complexity. We also determined whether the expansions of large superfamilies correlate with each other. We found three large clusters of correlated expansions: one involves expansions in both vertebrates and plants, one just in vertebrates, and one just in plants. Our work identifies important protein families and provides one explanation of the discrepancy between the total number of genes and the apparent physiological complexity of eukaryotic organisms.

3D complex: a structural classification of protein complexes.

Most of the proteins in a cell assemble into complexes to carry out their function. It is therefore crucial to understand the physicochemical properties as well as the evolution of interactions between proteins. The Protein Data Bank represents an important source of information for such studies, because more than half of the structures are homo- or heteromeric protein complexes. Here we propose the first hierarchical classification of whole protein complexes of known 3-D structure, based on representing their fundamental structural features as a graph. This classification provides the first overview of all the complexes in the Protein Data Bank and allows nonredundant sets to be derived at different levels of detail. This reveals that between one-half and two-thirds of known structures are multimeric, depending on the level of redundancy accepted. We also analyse the structures in terms of the topological arrangement of their subunits and find that they form a small number of arrangements compared with all theoretically possible ones. This is because most complexes contain four subunits or less, and the large majority are homomeric. In addition, there is a strong tendency for symmetry in complexes, even for heteromeric complexes. Finally, through comparison of Biological Units in the Protein Data Bank with the Protein Quaternary Structure database, we identified many possible errors in quaternary structure assignments. Our classification, available as a database and Web server at http://www.3Dcomplex.org, will be a starting point for future work aimed at understanding the structure and evolution of protein complexes.

Structure, function and evolution of multidomain proteins.

Proteins are composed of evolutionary units called domains; the majority of proteins consist of at least two domains. These domains and nature of their interactions determine the function of the protein. The roles that combinations of domains play in the formation of the protein repertoire have been found by analysis of domain assignments to genome sequences. Additional findings on the geometry of domains have been gained from examination of three-dimensional protein structures. Future work will require a domain-centric functional classification scheme and efforts to determine structures of domain combinations.

SUPERFAMILY: HMMs representing all proteins of known structure. SCOP sequence searches, alignments and genome assignments.

The SUPERFAMILY database contains a library of hidden Markov models representing all proteins of known structure. The database is based on the SCOP 'superfamily' level of protein domain classification which groups together the most distantly related proteins which have a common evolutionary ancestor. There is a public server at http://supfam.org which provides three services: sequence searching, multiple alignments to sequences of known structure, and structural assignments to all complete genomes. Given an amino acid or nucleotide query sequence the server will return the domain architecture and SCOP classification. The server produces alignments of the query sequences with sequences of known structure, and includes multiple alignments of genome and PDB sequences. The structural assignments are carried out on all complete genomes (currently 59) covering approximately half of the soluble protein domains. The assignments, superfamily breakdown and statistics on them are available from the server. The database is currently used by this group and others for genome annotation, structural genomics, gene prediction and domain-based genomic studies.

Exegesis: a procedure to improve gene predictions and its use to find immunoglobulin superfamily proteins in the human and mouse genomes.

Exegesis is a procedure to refine the gene predictions that are produced for complex genomes, e.g. those of humans and mice. It uses the program Genewise, sequences determined by experiment, experimental maps of gene segment libraries and a new browser that allows the user to rapidly inspect and compare multiple gene maps to regions of genomic sequences. The procedure should be of general use. Here, we use the procedure to find members of the immunoglobulin superfamily in the human and mouse genomes. To do this, Exegesis was used to process the original gene predictions from the automated Ensembl annotation pipeline. Exegesis produced (i) many more complete genes and new transcripts and (ii) a mapping of the immunoglobulin and T cell receptor gene libraries to the genome, which are largely absent in the Ensembl set.

The SUPERFAMILY database in 2004: additions and improvements.

The SUPERFAMILY database provides structural assignments to protein sequences and a framework for analysis of the results. At the core of the database is a library of profile Hidden Markov Models that represent all proteins of known structure. The library is based on the SCOP classification of proteins: each model corresponds to a SCOP domain and aims to represent an entire superfamily. We have applied the library to predicted proteins from all completely sequenced genomes (currently 154), the Swiss-Prot and TrEMBL databases and other sequence collections. Close to 60% of all proteins have at least one match, and one half of all residues are covered by assignments. All models and full results are available for download and online browsing at http://supfam.org. Users can study the distribution of their superfamily of interest across all completely sequenced genomes, investigate with which other superfamilies it combines and retrieve proteins in which it occurs. Alternatively, concentrating on a particular genome as a whole, it is possible first, to find out its superfamily composition, and secondly, to compare it with that of other genomes to detect superfamilies that are over- or under-represented. In addition, the webserver provides the following standard services: sequence search; keyword search for genomes, superfamilies and sequence identifiers; and multiple alignment of genomic, PDB and custom sequences.

SCOP database in 2004: refinements integrate structure and sequence family data.

The Structural Classification of Proteins (SCOP) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. Protein domains in SCOP are hierarchically classified into families, superfamilies, folds and classes. The continual accumulation of sequence and structural data allows more rigorous analysis and provides important information for understanding the protein world and its evolutionary repertoire. SCOP participates in a project that aims to rationalize and integrate the data on proteins held in several sequence and structure databases. As part of this project, starting with release 1.63, we have initiated a refinement of the SCOP classification, which introduces a number of changes mostly at the levels below superfamily. The pending SCOP reclassification will be carried out gradually through a number of future releases. In addition to the expanded set of static links to external resources, available at the level of domain entries, we have started modernization of the interface capabilities of SCOP allowing more dynamic links with other databases. SCOP can be accessed at http://scop.mrc-lmb.cam.ac.uk/scop.

SCOP database in 2002: refinements accommodate structural genomics.

The SCOP (Structural Classification of Proteins) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. Protein domains in SCOP are grouped into species and hierarchically classified into families, superfamilies, folds and classes. Recently, we introduced a new set of features with the aim of standardizing access to the database, and providing a solid basis to manage the increasing number of experimental structures expected from structural genomics projects. These features include: a new set of identifiers, which uniquely identify each entry in the hierarchy; a compact representation of protein domain classification; a new set of parseable files, which fully describe all domains in SCOP and the hierarchy itself. These new features are reflected in the ASTRAL compendium. The SCOP search engine has also been updated, and a set of links to external resources added at the level of domain entries. SCOP can be accessed at http://scop.mrc-lmb.cam.ac.uk/scop.

The linked conservation of structure and function in a family of high diversity: the monomeric cupredoxins.

The monomeric cupredoxins are a highly divergent family of copper binding electron transport proteins that function in photosynthesis and respiration. To determine how function and structure are conserved in the context of large sequence differences, we have carried out a detailed analysis of the cupredoxins of known structure and their sequence homologs. The common structure of the cupredoxins is formed by a sandwich of two beta sheets which support a copper binding site. The structure of the deeply buried core is intimately coupled to the binding site on the surface of the protein; in each protein the conserved regions form one continuous substructure that extends from the surface active site and through the center of the molecule. Residues around the active site are conserved for functional reasons, while those deeper in the structure will be conserved for structural reasons. Together the two sets support each other.