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.     

SMoS: a database of structural motifs of protein superfamilies

The Structural Motifs of Superfamilies (SMoS) database provides information about the structural motifs of aligned protein domain superfamilies. Such motifs among structurally aligned multiple members of protein superfamilies are recognized by the conservation of amino acid preference and solvent inaccessibility and are examined for the conservation of other features like secondary structural content, hydrogen bonding, non-polar interaction and residue packing. These motifs, along with their sequence and spatial orientation, represent the conserved core structure of each superfamily and also provide the minimal requirement of sequence and structural information to retain each superfamily fold.     

Sequence landmark patterns identify and characterize protein families

The three-dimensional structures of homologous proteins are usually conserved during evolution, as are critical residues in a few short sequence motifs that often constitute the active site in enzymes. The precise spatial organization of such sites depends on the lengths and positions of the secondary structural elements connecting the motifs. We show how members of protein superfamilies, such as kinesins, myosins, and G(alpha) subunits of trimeric G proteins, are identified and classed by simply counting the number of amino acid residues between important sequence motifs in their nucleotide triphosphate-hydrolyzing domains. Subfamily-specific landmark patterns (motif to motif scores) are principally due to inserts and gaps in surface loops. Unusual protein sequences and possible sequence prediction errors are detected.     

ProClass protein family database

ProClass is a protein family database that organizes non-redundant sequence entries into families defined collectively by PIR superfamilies and PROSITE patterns. By combining global similarities and functional motifs into a single classification scheme, ProClass helps to reveal domain and family relationships and classify multi-domain proteins. The database currently consists of >155 000 sequence entries retrieved from both PIR-International and SWISS-PROT databases. Approximately 92 000 or 60% of the ProClass entries are classified into approximately 6000 families, including a large number of new members detected by our GeneFIND family identification system. The ProClass motif collection contains approximately 72 000 motif sequences and >1300 multiple alignments for all PROSITE patterns, including >21 000 matches not listed in PROSITE and mostly detected from unique PIR sequences. To maximize family information retrieval, the database provides links to various protein family, domain, alignment and structural class databases. With its high classification rate and comprehensive family relationships, ProClass can be used to support full-scale genomic annotation. The database, now being implemented in an object-relational database management system, is available for online sequence search and record retrieval from our WWW server at http://pir.georgetown.edu/gfserver/proclass.html     

Molego-based definition of the architecture and specificity of metal-binding sites

Decomposing proteins into "molegos," building blocks that are conserved in sequence and 3D-structure, can identify functional elements. To demonstrate the specificity of the decomposition method, the PCPMer program suite was used to numerically define physical chemical property motifs corresponding to the molegos that make up the metal-containing active sites of three distinct enzyme families, from the dimetallic phosphatases, DNase 1 related nucleases/phosphatases, and dioxygenases. All three superfamilies bind metal ions in a beta-strand core region but differ in the number and type of ions needed for activity. The motifs were then used to automatically identify proteins in the ASTRAL40 database that contained similar motifs. The proteins with the highest PCPMer score in the database were primarily metal-binding enzymes that were related in function to those in the alignment used to generate the PCPMer motif lists. The proteins that contained motifs similar to the dioxygenases differed from those found with PCP-motifs for phosphatases and nucleases. Relatively few metal-binding enzymes were detected when the search was done with PCP-motifs defined for interleukin-1 related proteins, which have a beta-strand core but do not bind metal ions. While the box architecture was constant in each superfamily, the specificity for the metal ion preferred for enzymatic activity is determined by the pattern of carbonyl, hydroxyl or imadazole groups in key positions in the molegos. These results have implications for the design of metal-binding enzymes, and illustrate the ability of the PCPMer approach to distinguish, at the sequence level, structural and functional elements.     

Genetic isolation of transport signals directing cell surface expression

Membrane proteins represent approximately 30% of the proteome in both prokaryotes and eukaryotes. The spatial localization of membrane-bound proteins is often determined by specific sequence motifs that may be regulated in response to physiological changes, such as protein interactions and receptor signalling. Identification of signalling motifs is therefore important for understanding membrane protein expression, function and transport mechanisms. We report a genetic isolation of novel motifs that confer surface expression. Further characterization showed that SWTY, one class of these isolated motifs with homology to previously reported forward transport motifs, has the ability to both override the RKR endoplasmic reticulum localization signal and potentiate steady-state surface expression. The genetically isolated SWTY motif is functionally interchangeable with a known motif in cardiac potassium channels and an identified motif in an HIV coreceptor, and operates by recruiting 14-3-3 proteins. This study expands the repertoire of and enables a screening method for membrane trafficking signals.     

iProClass: an integrated, comprehensive and annotated protein classification database

The iProClass database is an integrated resource that provides comprehensive family relationships and structural and functional features of proteins, with rich links to various databases. It is extended from ProClass, a protein family database that integrates PIR superfamilies and PROSITE motifs. The iProClass currently consists of more than 200,000 non-redundant PIR and SWISS-PROT proteins organized with more than 28,000 superfamilies, 2600 domains, 1300 motifs, 280 post-translational modification sites and links to more than 30 databases of protein families, structures, functions, genes, genomes, literature and taxonomy. Protein and family summary reports provide rich annotations, including membership information with length, taxonomy and keyword statistics, full family relationships, comprehensive enzyme and PDB cross-references and graphical feature display. The database facilitates classification-driven annotation for protein sequence databases and complete genomes, and supports structural and functional genomic research. The iProClass is implemented in Oracle 8i object-relational system and available for sequence search and report retrieval at http://pir.georgetown.edu/iproclass/.     

3MATRIX and 3MOTIF: a protein structure visualization system for conserved sequence motifs

Computational methods such as sequence alignment and motif construction are useful in grouping related proteins into families, as well as helping to annotate new proteins of unknown function. These methods identify conserved amino acids in protein sequences, but cannot determine the specific functional or structural roles of conserved amino acids without additional study. In this work, we present 3MATRIX (http://3matrix.stanford.edu) and 3MOTIF (http://3motif.stanford.edu), a web-based sequence motif visualization system that displays sequence motif information in its appropriate three-dimensional (3D) context. This system is flexible in that users can enter sequences, keywords, structures or sequence motifs to generate visualizations. In 3MOTIF, users can search using discrete sequence motifs such as PROSITE patterns, eMOTIFs, or any other regular expression-like motif. Similarly, 3MATRIX accepts an eMATRIX position-specific scoring matrix, or will convert a multiple sequence alignment block into an eMATRIX for visualization. Each query motif is used to search the protein structure database for matches, in which the motif is then visually highlighted in three dimensions. Important properties of motifs such as sequence conservation and solvent accessible surface area are also displayed in the visualizations, using carefully chosen color shading schemes.     

TOPDOM: database of domains and motifs with conservative location in transmembrane proteins

The TOPDOM database is a collection of domains and sequence motifs located consistently on the same side of the membrane in alpha-helical transmembrane proteins. The database was created by scanning well-annotated transmembrane protein sequences in the UniProt database by specific domain or motif detecting algorithms. The identified domains or motifs were added to the database if they were uniformly annotated on the same side of the membrane of the various proteins in the UniProt database. The information about the location of the collected domains and motifs can be incorporated into constrained topology prediction algorithms, like HMMTOP, increasing the prediction accuracy. AVAILABILITY: The TOPDOM database and the constrained HMMTOP prediction server are available on the page http://topdom.enzim.hu CONTACT: tusi@enzim.hu; lkalmar@enzim.hu.     

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.     

The EMOTIF database

The EMOTIF database is a collection of more than 170 000 highly specific and sensitive protein sequence motifs representing conserved biochemical properties and biological functions. These protein motifs are derived from 7697 sequence alignments in the BLOCKS+ database (released on June 23, 2000) and all 8244 protein sequence alignments in the PRINTS database (version 27.0) using the emotif-maker algorithm developed by Nevill-Manning et al. (Nevill-Manning,C.G., Wu,T.D. and Brutlag,D.L. (1998) Proc. Natl Acad. Sci. USA, 95, 5865-5871; Nevill-Manning,C.G., Sethi,K.S., Wu,T. D. and Brutlag,D.L. (1997) ISMB-97, 5, 202-209). Since the amino acids and the groups of amino acids in these sequence motifs represent critical positions conserved in evolution, search algorithms employing the EMOTIF patterns can identify and classify more widely divergent sequences than methods based on global sequence similarity. The emotif protein pattern database is available at http://motif.stanford.edu/emotif/.     

PROMOT: a FORTRAN program to scan protein sequences against a library of known motifs

Information about the three-dimensional structure or functionof a newly determined protein sequence can be obtained if theprotein is found to contain a characterized motif or patternof residues. Recently a database (PROSITE) has been establishedthat contains 337 known motifs encoded as a list of allowedresidue types at specific positions along the sequence. PROMOTis a FORTRAN computer program that takes a protein sequenceand examines if it contains any of the motifs in PROSITE. Theprogram also extends the definitions of patterns beyond thoseused in PROSITE to provide a simple, yet flexible, method toscan either a PROSITE or a user-defined pattern against a proteinsequence database. Received on October 17, 1990; accepted on November 15, 1990     

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).     

PASS2: a semi-automated database of Protein Alignments Organised as Structural Superfamilies

PASS2 is a nearly automated version of CAMPASS and contains sequence alignments of proteins grouped at the level of superfamilies. This database has been created to fall in correspondence with SCOP database (1.53 release) and currently consists of 110 multi-member superfamilies and 613 superfamilies corresponding to single members. In multi-member superfamilies, protein chains with no more than 25% sequence identity have been considered for the alignment and hence the database aims to address sequence alignments which represent 26 219 protein domains under the SCOP 1.53 release. Structure-based sequence alignments have been obtained by COMPARER and the initial equivalences are provided automatically from a MALIGN alignment and subsequently augmented using STAMP4.0. The final sequence alignments have been annotated for the structural features using JOY4.0. Several interesting links are provided to other related databases and genome sequence relatives. Availability of reliable sequence alignments of distantly related proteins, despite poor sequence identity and single-member superfamilies, permit better sampling of structures in libraries for fold recognition of new sequences and for the understanding of protein structure–function relationships of individual superfamilies. The database can be queried by keywords and also by sequence search, interfaced by PSI-BLAST methods. Structure-annotated sequence alignments and several structural accessory files can be retrieved for all the superfamilies including the user-input sequence. The database can be accessed from http://www.ncbs.res.in/%7Efaculty/mini/campass/pass.html.     

Construction and analysis of a profile library characterizing groups of structurally known proteins.

A new sequence motif library StrProf was constructed characterizing the groups of related proteins in the PDB three-dimensional structure database. For a representative member of each protein family, which was identified by cross-referencing the PDB with the PIR superfamily classification, a group of related sequences was collected by the BLAST search against the nonredundant protein sequence database. For every group, the motifs were identified automatically according to the criteria of conservation and uniqueness of pentapeptide patterns and with a dual dynamic programming algorithm. In the StrProf library, motifs are represented by profile matrices rather than consensus patterns to allow more flexible search capabilities. Another dynamic programming algorithm was then developed to search this motif library. When the computationally derived StrProf was compared with PROSITE, which is a manually derived motif library in the best consensus pattern representation, the numbers of identified patterns were comparable. StrProf missed about one third of the PROSITE motifs, but there were also new motifs lacking in PROSITE. The new library was incorporated in SMART (Sequence Motif Analysis and Retrieval Tool), a computer tool designed to help search and annotate biologically important sites in an unknown protein sequence. The client program is available free of charge through the Internet.     

PRINTS--a database of protein motif fingerprints.

PRINTS is a compendium of protein motif 'fingerprints'. A fingerprint is defined as a group of motifs excised from conserved regions of a sequence alignment, whose diagnostic power or potency is refined by iterative databasescanning (in this case the OWL composite sequence database). Generally, the motifs do not overlap, but are separated along a sequence, though they may be contiguous in 3D-space. The use of groups of independent, linearly- or spatially-distinct motifs allows protein folds and functionalities to be characterised more flexibly and powerfully than conventional single-component patterns or regular expressions. The current version of the database contains 200 entries (encoding 950 motifs), covering a wide range of globular and membrane proteins, modular polypeptides, and so on. The growth of the databaseis influenced by a number of factors; e.g. the use of multiple motifs; the maximisation of sequence information through iterative database scanning; and the fact that the database searched is a large composite. The information contained within PRINTS is distinct from, but complementary to the consensus expressions stored in the widely-used PROSITE dictionary of patterns.     

Predicting protein functional sites with phylogenetic motifs

In this report, we demonstrate that phylogenetic motifs, sequence regions conserving the overall familial phylogeny, represent a promising approach to protein functional site prediction. Across our structurally and functionally heterogeneous data set, phylogenetic motifs consistently correspond to functional sites defined by both surface loops and active site clefts. Additionally, the partially buried prosthetic group regions of cytochrome P450 and succinate dehydrogenase are identified as phylogenetic motifs. In nearly all instances, phylogenetic motifs are structurally clustered, despite little overall sequence proximity, around key functional site features. Based on calculated false-positive expectations and standard motif identification methods, we show that phylogenetic motifs are generally conserved in sequence. This result implies that they can be considered motifs in the traditional sense as well. However, there are instances where phylogenetic motifs are not (overall) well conserved in sequence. This point is enticing, because it implies that phylogenetic motifs are able to identify key sequence regions that traditional motif-based approaches would not. Further, phylogenetic motif results are also shown to be consistent with evolutionary trace results, and bootstrapping is used to demonstrate tree significance.