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The distribution of all peptidase homologues across all phyla of organisms was analysed to determine within which kingdom each of the 271 families originated. No family was found to be ubiquitous and even peptidases thought to be essential for life, such as signal peptidase and methionyl aminopeptides are missing from some clades. There are 33 peptidase families common to archaea, bacteria and eukaryotes and are assumed to have originated in the last universal common ancestor (LUCA). These include peptidases with different catalytic types, exo- and endopeptidases, peptidases with different tertiary structures and peptidases from different families but with similar structures. This implies that the different catalytic types and structures pre-date LUCA. Other families have had their origins in the ancestors of viruses, archaea, bacteria, fungi, plants and animals, and a number of families have had their origins in the ancestors of particular phyla. The evolution of peptidases is compared to recent hypotheses about the evolution of organisms., Highlights • Sequences of proteolytic enzymes can be clustered into 271 families. • No family is present in all organisms. • Only 33 families are predicted to originate in the last universal common ancestor. • Different structures and activities predate the last universal common ancestor. • Other families have originated in organism kingdoms, phyla or even families.

Proteolytic enzymes and their homologues have been classified into clans by comparing the tertiary structures of the peptidase domains, into families by comparing the protein sequences of the peptidase domains, and into protein-species by comparing various attributes including domain architecture, substrate preference, inhibitor interactions, subcellular location, and phylogeny. The results are compared with the earlier classification (Rawlings and Barrett, 1993 [1]). The numbers of sequences, protein-species, families, clans and even catalytic type have substantially increased during the intervening 26 years. The alternative classifications by catalytic type and/or activity are shown not to reflect evolutionary relationships.

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

The MEROPS database (http://merops.sanger.ac.uk) is an integrated source of information about peptidases, their substrates and inhibitors, which are of great relevance to biology, medicine and biotechnology. The hierarchical classification of the database is as follows: homologous sets of sequences are grouped into a protein species; protein species are grouped into a family; families are grouped into clans. There is a type example for each protein species (known as a 'holotype'), family and clan, and each protein species, family and clan has its own unique identifier. Pages to show the involvement of peptidases and peptidase inhibitors in biological pathways have been created. Each page shows the peptidases and peptidase inhibitors involved in the pathway, along with the known substrate cleavages and peptidase-inhibitor interactions, and a link to the KEGG database of biological pathways. Links have also been established with the IUPHAR Guide to Pharmacology. A new service has been set up to allow the submission of identified substrate cleavages so that conservation of the cleavage site can be assessed. This should help establish whether or not a cleavage site is physiologically relevant on the basis that such a cleavage site is likely to be conserved.

The Gene Ontology resource (GO; http://geneontology.org) provides structured, computable knowledge regarding the functions of genes and gene products. Founded in 1998, GO has become widely adopted in the life sciences, and its contents are under continual improvement, both in quantity and in quality. Here, we report the major developments of the GO resource during the past two years. Each monthly release of the GO resource is now packaged and given a unique identifier (DOI), enabling GO-based analyses on a specific release to be reproduced in the future. The molecular function ontology has been refactored to better represent the overall activities of gene products, with a focus on transcription regulator activities. Quality assurance efforts have been ramped up to address potentially out-of-date or inaccurate annotations. New evidence codes for high-throughput experiments now enable users to filter out annotations obtained from these sources. GO-CAM, a new framework for representing gene function that is more expressive than standard GO annotations, has been released, and users can now explore the growing repository of these models. We also provide the ‘GO ribbon’ widget for visualizing GO annotations to a gene; the widget can be easily embedded in any web page. This is an open access article distributed under the terms of the Creative Commons CC BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

This chapter describes how to retrieve data on lysosomal peptidases from the MEROPS database for proteolytic enzymes, their substrates and inhibitors ( http://merops.sanger.ac.uk ). Features described in this chapter include the summary page, pages for structure, interactions with inhibitors, substrates, literature and involvement in physiological pathways, and how to download data from the MEROPS FTP site. The lysosomal peptidase legumain is used as an example.

Global production of chickens has trebled in the past two decades and they are now the most important source of dietary animal protein worldwide. Chickens are subject to many infectious diseases that reduce their performance and productivity. Coccidiosis, caused by apicomplexan protozoa of the genus Eimeria, is one of the most important poultry diseases. Understanding the biology of Eimeria parasites underpins development of new drugs and vaccines needed to improve global food security. We have produced annotated genome sequences of all seven species of Eimeria that infect domestic chickens, which reveal the full extent of previously described repeat-rich and repeat-poor regions and show that these parasites possess the most repeat-rich proteomes ever described. Furthermore, while no other apicomplexan has been found to possess retrotransposons, Eimeria is home to a family of chromoviruses. Analysis of Eimeria genes involved in basic biology and host-parasite interaction highlights adaptations to a relatively simple developmental life cycle and a complex array of co-expressed surface proteins involved in host cell binding.

Africa's Bane Tsetse are blood-feeding, fast-flying flies that transmit a range of Trypanosoma spp. protozoan pathogens, which cause sleeping sickness in humans and their nagana in their livestock. The International Glossina Genome Initiative (p. 380 ) sequenced the genome of Glossina morsitans and identified the genes for many attributes of the tsetse's remarkable biology, including viviparity and the expression of analogs of mammalian milk proteins. Tsetse are host to several specific symbionts that appear to synthesize essential nutrients for the fly and also to hitherto undiscovered parasitoid-derived viruses. Deeper exploration of this genome will reveal what makes these fly species so host- and trypanosome specific.

Zinc metallopeptidases that contain the His-Glu-Xaa-Xaa-His (HEXXH) motif generally have a third ligand of the metal ion that may be either a Glu residue (in clan MA) or a His residue (in clan MB) (Rawlings and Barrett (1995) Methods Enzymol. 248, 183–228). Thimet oligopeptidase has not yet been assigned to either clan, and both Glu and His residues have been proposed as the third ligand. We mutated candidate ligand residues in the recombinant enzyme and identified Glu, His and Asp residues that are important for catalytic activity and/or stability of the protein. However, neither of the Glu and His residues close to the HEXXH motif that have previously been suggested to be ligands is required for the binding of zinc. We conclude that thimet oligopeptidase is not a member of clan MA or clan MB and it is likely that the enzyme possesses a catalytic site and protein fold different from those identified in any metallopeptidase to date. The definitive identification of the third zinc ligand may well require the determination of the crystallographic structure of thimet oligopeptidase or one of its homologues.

Protozoan parasites of the genus Giardia are one of the earliest lineages of eukaryotic cells. To initiate infection, trophozoites emerge from a cyst in the host. Excystation is blocked by specific cysteine protease inhibitors. Using a biotinylated inhibitor, the target protease was identified and its corresponding gene cloned. The protease was localized to vesicles that release their contents just prior to excystation. The Giardia protease is the earliest known branch of the cathepsin B family. Its phylogeny confirms that the cathepsin B lineage evolved in primitive eukaryotic cells, prior to the divergence of plant and animal kingdoms, and underscores the diversity of cellular functions that this enzyme family facilitates.

Legumain is a cysteine endopeptidase that shows strict specificity for hydrolysis of asparaginyl bonds. The enzyme belongs to peptidase family C13, and is thus unrelated to the better known cysteine peptidases of the papain family, C1 (Rawlings, N. D., and Barrett, A. J. (1994) Methods Enzymol. 244, 461-486). To date, legumain has been described only from plants and a blood fluke, Schistosoma mansoni We now show that legumain is present in mammals. We have cloned and sequenced human legumain and part of pig legumain. We have also purified legumain to homogeneity (2200-fold, 8% yield) from pig kidney. The mammalian sequences are clearly homologous with legumains from non-mammalian species. Pig legumain is a glycoprotein of about 34 kDa, decreasing to 31 kDa on deglycosylation. It is an asparaginyl endopeptidase, hydrolyzing Z-Ala-Ala-Asn-7-(4-methyl)coumarylamide and benzoyl-Asn-p-nitroanilide. Maximal activity is seen at pH 5.8 under normal assay conditions, and the enzyme is irreversibly denatured at pH 7 and above. Mammalian legumain is a cysteine endopeptidase, inhibited by iodoacetamide and maleimides, but unaffected by compound E64 (trans-epoxysuccinyl-L-leucylamido-(4-guanidino)butane). It is inhibited by ovocystatin (cystatin from chicken egg white) and human cystatin C with Ki values < 5 nM. We discuss the significance of the discovery of a cysteine endopeptidase of a new family and distinctive specificity in man and other mammals.

Genome sequencing projects are generating enormous amounts of biological data that require analysis, which in turn identifies genes and proteins that require characterization. Enzymes that act on proteins are especially difficult to characterize because of the time required to distinguish one from another. This is particularly true of peptidases, the enzymes that activate, inactivate and degrade proteins. This article aims to identify clusters of sequences each of which represents the species variants of a single putative peptidase that is widely distributed and is thus merits biochemical characterization. The MEROPS database maintains large collections of sequences, references, substrate cleavage positions and inhibitor interactions of peptidases and their homologues. MEROPS also maintains a hierarchical classification of peptidase homologues, in which sequences are clustered as species variants of a single peptidase; homologous sequences are assembled into a family; and families are clustered into a clan. For each family, an alignment and a phylogenetic tree are generated. By assigning an identifier to a peptidase that has been biochemically characterized from a particular species (called a holotype), the identifier can be automatically extended to sequences from other species that cluster with the holotype. This permits transference of annotation from the holotype to other members of the cluster. By extending this concept to all peptidase homologues (including those of unknown function that have not been characterized) from model organisms representing all the major divisions of cellular life, clusters of sequences representing putative peptidases can also be identified. The 42 most widely distributed of these putative peptidases have been identified and discussed here and are prioritized as ideal candidates for biochemical characterization. Database URL: http://merops.sanger.ac.uk

It has become clear that the proteolytic enzymes that depend upon a serine residue for their catalytic activity belong to many different families of proteins. We have attempted to group these families in "clans." A clan is defined as a group of families the members of which have a common ancestor. That is to say, they are homologous, although some of the similarities are in the "twilight zone" and the relationships cannot be proven by rigorous statistical methods. We believe we can recognize five, or perhaps six, clans of serine peptidases. In view of the separate evolutionary origins of the serine peptidases in different clans, it is not surprising to find that they may differ greatly and that indeed there are few generalizations that can be applied to all serine peptidases. In contrast, the members of a clan commonly have marked similarities.

Peptidases, their substrates and inhibitors are of great relevance to biology, medicine and biotechnology. The MEROPS database (http://merops.sanger.ac.uk) aims to fulfil the need for an integrated source of information about these. The database has hierarchical classifications in which homologous sets of peptidases and protein inhibitors are grouped into protein species, which are grouped into families, which are in turn grouped into clans. The database has been expanded to include proteolytic enzymes other than peptidases. Special identifiers for peptidases from a variety of model organisms have been established so that orthologues can be detected in other species. A table of predicted active-site residue and metal ligand positions and the residue ranges of the peptidase domains in orthologues has been added to each peptidase summary. New displays of tertiary structures, which can be rotated or have the surfaces displayed, have been added to the structure pages. New indexes for gene names and peptidase substrates have been made available. Among the enhancements to existing features are the inclusion of small-molecule inhibitors in the tables of peptidase–inhibitor interactions, a table of known cleavage sites for each protein substrate, and tables showing the substrate-binding preferences of peptidases derived from combinatorial peptide substrate libraries.

In metazoan organisms protein inhibitors of peptidases are important factors essential for regulation of proteolytic activity. In vertebrates genes encoding peptidase inhibitors constitute up to 1% of genes reflecting a need for tight and specific control of proteolysis especially in extracellular body fluids. In stark contrast unicellular organisms, both prokaryotic and eukaryotic consistently contain only few, if any, genes coding for putative peptidase inhibitors. This may seem perplexing in the light of the fact that these organisms produce large numbers of proteases of different catalytic classes with the genes constituting up to 6% of the total gene count with the average being about 3%. Apparently, however, a unicellular life-style is fully compatible with other mechanisms of regulation of proteolysis and does not require protein inhibitors to control their intracellular and extracellular proteolytic activity. So in prokaryotes occurrence of genes encoding different types of peptidase inhibitors is infrequent and often scattered among phylogenetically distinct orders or even phyla of microbiota. Genes encoding proteins homologous to alpha-2-macroglobulin (family I39), serine carboxypeptidase Y inhibitor (family I51), alpha-1-peptidase inhibitor (family I4) and ecotin (family I11) are the most frequently represented in Bacteria. Although several of these gene products were shown to possess inhibitory activity, with an exception of ecotin and staphostatins, the biological function of microbial inhibitors is unclear. In this review we present distribution of protein inhibitors from different families among prokaryotes, describe their mode of action and hypothesize on their role in microbial physiology and interactions with hosts and environment.

The MEROPS website (http://merops.sanger.ac.uk) includes information on peptidase inhibitors as well as on peptidases and their substrates. Displays have been put in place to link peptidases and inhibitors together. The classification of protein peptidase inhibitors is continually being revised, and currently inhibitors are grouped into 67 families based on comparisons of protein sequences. These families can be further grouped into 38 clans based on comparisons of tertiary structure. Small molecule inhibitors are important reagents for peptidase characterization and, with the increasing importance of peptidases as drug targets, they are also important to the pharmaceutical industry. Small molecule inhibitors are now included in MEROPS and over 160 summaries have been written.

Oligopeptidases are endopeptidases that are not proteinases in the strict sense, since they do not hydrolyse peptide bonds in proteins, but act only on smaller polypeptides or oligopeptides. These enzymes apparently perform important, specialized biological functions that include the modification or destruction of peptide messenger molecules. Oligopeptidases have few naturally occurring inhibitors, and their distinctive specificity prevents them from interacting with alpha 2-macroglobulin, unlike the great majority of endopeptidases. The specificity of these specialized endopeptidases doubtless depends upon the three-dimensional structure of the active site, but no crystallographic structure is yet available for an oligopeptidase. Study of the primary structure of prolyl oligopeptidase has recently shown that it is a member of a new family of serine-type peptidases most of which are exopeptidases. The alignment of the sequences leads to the identification of some catalytic triad residues that have not yet been elucidated experimentally.

In rodents, the formation of ovarian follicles occurs after birth. In recent years, several factors required for follicular assembly and the growth of the newly formed follicles have been identified. We now describe a novel gene, Fxna, identified by differential display in the neonatal rat ovary. Fxna encodes an mRNA of 5.4 kb, and a protein of 898 amino acids. Fxna is a transmembrane metallopeptidase from family M28, localized to the endoplasmic reticulum. In the ovary, Fxna mRNA is expressed in granulosa cells; its abundance is maximal 48 hours after birth, i.e. during the initiation of follicular assembly. Reducing Fxna mRNA levels via lentiviral-mediated delivery of short hairpin RNAs to neonatal ovaries resulted in substantial loss of primordial, primary and secondary follicles,and structural disorganization of the ovary, with many abnormal follicles containing more than one oocyte and clusters of somatic cells not associated with any oocytes. These abnormalities were not attributable to either increased apoptosis or decreased proliferation of granulosa cells. The results indicate that Fxna is required for the organization of somatic cells and oocytes into discrete follicular structures. As an endoplasmic reticulum-bound peptidase, Fxna may facilitate follicular organization by processing precursor proteins required for intraovarian cell-to-cell communication.

Peptidases, their substrates and inhibitors are of great relevance to biology, medicine and biotechnology. The MEROPS database (http://merops.sanger.ac.uk) aims to fulfil the need for an integrated source of information about these. The database has a hierarchical classification in which homologous sets of peptidases and protein inhibitors are grouped into protein species, which are grouped into families, which are in turn grouped into clans. The classification framework is used for attaching information at each level. An important focus of the database has become distinguishing one peptidase from another through identifying the specificity of the peptidase in terms of where it will cleave substrates and with which inhibitors it will interact. We have collected over 39 000 known cleavage sites in proteins, peptides and synthetic substrates. These allow us to display peptidase specificity and alignments of protein substrates to give an indication of how well a cleavage site is conserved, and thus its probable physiological relevance. While the number of new peptidase families and clans has only grown slowly the number of complete genomes has greatly increased. This has allowed us to add an analysis tool to the relevant species pages to show significant gains and losses of peptidase genes relative to related species.

The N-terminal amino-acid sequence of pig dipeptidyl-peptidase II (EC 3.4.14.2; DPP II) recently published (Huang, K., Takagaki, M., Kani, K. and Ohkubo, I. (1996) Biochim. Biophys. Acta 1290, 149-156) proves that the enzyme is homologous with lysosomal Pro-X carboxypeptidase (EC 3.4.16.2), and belongs to peptidase family S28 in clan SC. This is consistent with a number of biochemical similarities between these two prolyl bond-cleaving serine peptidases. DPP II is not related to granzymes, as was suggested by Huang et al.

The enzymes that hydrolyse peptide bonds, called peptidases or proteases, are very important to mankind and are also very numerous. The many scientists working on these enzymes are rapidly acquiring new data, and they need good methods to store it and retrieve it. The storage and retrieval require effective systems of classification and nomenclature, and it is the design and implementation of these that we mean by 'managing' peptidases. Ten years ago Rawlings and Barrett proposed the first comprehensive system for the classification of peptidases, which included a set of simple names for the families. In the present article we describe how the system has developed since then. The peptidase classification has now been adopted for use by many other databases, and provides the structure around which the MEROPS protease database (http://merops.sanger.ac.uk) is built.

The MEROPS database (http://www.merops.ac.uk) has been redesigned to accommodate increased amounts of information still in pages of moderate size that load rapidly. The information on each PepCard, FamCard or ClanCard has been divided between several sub-pages that can be reached by use of navigation buttons in a frame at the top of the screen. Several important additions have also been made to the database. Amongst these are CGI searches that allow the user to find a peptidase by name, its MEROPS identifier or its human or mouse chromosome location. The user may also list all published tertiary structures for a peptidase clan or family, and search for peptidase specificity data by entering either a peptidase name, substrate or bond cleaved. The PepCards, FamCards and ClanCards now have literature pages listing about 10 000 key papers in total, mostly with links to MEDLINE. Many PepCards now include a protein sequence alignment and data table for matching human, mouse or rat expressed sequence tags. FamCards and ClanCards contain Structure pages showing diagrammatic representations of known secondary structures of member peptidases or family type examples, respectively. Many novel peptidases have been added to the database after being discovered in complete genomes, libraries of expressed sequence tags or data from high-throughput genomic sequencing, and we describe the methods by which these were found.

Peptidases (often termed proteases) are of great relevance to biology, medicine, and biotechnology. This practical importance creates a need for an integrated source of information about peptidases. In the MEROPS database (www.merops.ac.uk), peptidases are classified by structural similarities in the parts of the molecules responsible for their enzymatic activity. They are grouped into families on the basis of amino acid sequence homology, and the families are assembled into clans in light of evidence that they share common ancestry. The evidence for clan-level relationships usually comes from similarities in tertiary structure, but we suggest that secondary structure profiles may also be useful in the future. The classification forms a framework around which a wealth of supplementary information about the peptidases is organized. This includes images of three-dimensional structures, alignments of matching human and mouse ESTs, comments on biomedical relevance, human and other gene symbols, and literature references linked to PubMed. For each family, there is an amino acid sequence alignment and a dendrogram. There is a list of all peptidases known from each of over 1000 species, together with summary data for the distributions of the families and clans throughout the major groups of organisms. A set of online searches provides access to information about the location of peptidases on human chromosomes and peptidase substrate specificity.

The deduced amino acid sequence of pig liver soluble angiotensin II-binding protein [Sugiura, Hagiwara and Hirose (1992) J. Biol. Chem. 267, 18067-18072] is similar over most of its length to that reported for rat testis thimet oligopeptidase (EC 3.4.24.15) by Pierotti, Dong, Glucksman, Orlowski and Roberts [(1990) (Biochemistry 29, 10323-10329]. We have found that homogeneous rat testis thimet oligopeptidase binds angiotensin II with the same distinctive characteristics as the pig liver protein. Analysis of the nucleotide sequences reported for the two proteins pointed to the likelihood that sequencing errors had caused two segments of the amino acid sequence of the rat protein to be translated out of frame, and re-sequencing of selected parts of the clone (kindly provided by the previous authors) confirmed this. The revised deduced amino acid sequence of rat thimet oligopeptidase contains 687 residues, representing a protein of 78,308 Da, and is more closely related to those of the pig liver protein and other known homologues of thimet oligopeptidase than that described previously.

The available amino acid sequences of peptidases have been examined, and the enzymes have been allocated to evolutionary families. Some of the families can be grouped together in ‘clans’ that show signs of distant relationship, but nevertheless, it appears that there may be as many as 60 evolutionary lines of peptidases with separate origins. Some of these contain members with quite diverse peptidase activities, and yet there are some striking examples of convergence. We suggest that the classification by families could be used as an extension of the current classification by catalytic type.

We have examined the amino acid sequences of a number of proteins that have been suggested to be related to chicken cystatin, a protein from chicken egg white that inhibits cysteine proteinases. On the basis of statistical analysis, the following proteins were found to be members of the cystatin superfamily: human cystatin A, rat cystatin A(alpha), human cystatin B, rat cystatin B(beta), rice cystatin, human cystatin C, ox colostrum cystatin, human cystatin S, human cystatin SA, human cystatin SN, chicken cystatin, puff adder cystatin, human kininogen, ox kininogen, rat kininogen, rat T-kininogens 1 and 2, human alpha 2HS-glycoprotein, and human histidine-rich glycoprotein. Fibronectin is shown not to be a member of this superfamily, and the c-Ha-ras oncogene protein p21 (Val-12) probably is not a member also. It was convenient to divide members of the superfamily into four types on the basis of the presence of one, two, or three copies of cystatin-like segments and the presence or absence of disulfide bonds. Evolutionary dendrograms were calculated by three methods, and from these we have constructed a scheme depicting the sequence of events in the evolution of these proteins. We suggest that about 1000 million years ago a precursor containing disulfide loops appeared, and that all disulfide-containing cystatins are derived from this. We follow the evolution of the proteins of the superfamily along four main lineages, with special attention to the part that duplication of segments has played in the development of the more complex molecules.

A DEC-SYSTEM 10 FORTRAN computer program to carry out secondary structure prediction of proteins, according to the algorithm of Chou & Fasman (1, 2), is described. Program results are compared with predictions made by Chou & Fasman.