Identification of cross-linked peptides from large sequence databases

We describe a method to identify cross-linked peptides from complex samples and large protein sequence databases by combining isotopically tagged cross-linkers, chromatographic enrichment, targeted proteomics and a new search engine called xQuest. This software reduces the search space by an upstream candidate-peptide search before the recombination step. We showed that xQuest can identify cross-linked peptides from a total Escherichia coli lysate with an unrestricted database search.     

'Harvester': a fast meta search engine of human protein resources

SUMMARY: We have developed a Web-based tool named 'Harvester' that bulk-collects bioinformatic data on human proteins from various databases and prediction servers. The information on every single protein is assembled on a single HTML page as a combination of database screen-shots and plain text. A full text meta search engine, similar to Google trade mark, allows screening of the whole genome proteome for current protein functions and predictions in a few seconds. With Harvester it is now possible to compare and check the quality of different database entries and prediction algorithms on a single page. A feedback forum allows users to comment on Harvester and to report database inconsistencies. AVAILABILITY: The service is freely available to the academic community at http://harvester.embl.de.     

The homeodomain resource: a prototype database for a large protein family

The Homeodomain Resource is an annotated collection of non-redundant protein sequences, three-dimensional structures and genomic information for the homeodomain protein family. Release 2.0 contains 765 full-length homeodomain-containing sequences, 29 experimentally derived structures and 116 homeobox loci implicated in human genetic disorders. Entries are fully hyperlinked to facilitate easy retrieval of the original records from source databases. A simple search engine with a graphical user interface is provided to query the component databases and assemble customized data sets. A new feature for this release is the addition of more automated methods for database searching, maintenance and implementation of efficient data management. The Homeodomain Resource is freely available through the WWW at http://genome.nhgri.nih.gov/homeodomain     

基于WWW的生物信息集成检索系统的研制

生物信息检索和获取成为当前非常重要而紧迫的研究课题,我们采用元搜索引擎技术、JAVA和HTML编程语言研制开发了基于WWW生物信息集成检索系统,该系统提供了统一的检索界面,对15分子生物学数据库和3个通用搜索引擎实现多功能、复合型、全开放的集成检索。该系统为广大从事医学、分子生物学、分子肿瘤学、分子遗传学以度人类基因组的科研人员准确、及时、综合获取多种生物信息资源,具有极为重要而深远的意义。     

A Dynamic Workflow Approach for the Integration of Bioinformatics Services

Modern biological and chemical studies rely on life science databases as well as sophisticated software tools (e.g., homology search tools, modeling and visualization tools). These tools often have to be combined and integrated in order to support a given study. SIBIOS (System for the Integration of Bioinformatics Services) serves this purpose. The services are both life science database search services and software tools. The task engine is the core component of SIBIOS. It supports the execution of dynamic workflows that incorporate multiple bioinformatics services. The architecture of SIBIOS, the approaches to addressing the heterogeneity as well as interoperability of bioinformatics services, including data integration are presented in this paper.     

iGNM: a database of protein functional motions based on Gaussian Network Model

MOTIVATION: The knowledge of protein structure is not sufficient for understanding and controlling its function. Function is a dynamic property. Although protein structural information has been rapidly accumulating in databases, little effort has been invested to date toward systematically characterizing protein dynamics. The recent success of analytical methods based on elastic network models, and in particular the Gaussian Network Model (GNM), permits us to perform a high-throughput analysis of the collective dynamics of proteins. RESULTS: We computed the GNM dynamics for 20 058 structures from the Protein Data Bank, and generated information on the equilibrium dynamics at the level of individual residues. The results are stored on a web-based system called iGNM and configured so as to permit the users to visualize or download the results through a standard web browser using a simple search engine. Static and animated images for describing the conformational mobility of proteins over a broad range of normal modes are accessible, along with an online calculation engine available for newly deposited structures. A case study of the dynamics of 20 non-homologous hydrolases is presented to illustrate the utility of the iGNM database for identifying key residues that control the cooperative motions and revealing the connection between collective dynamics and catalytic activity.     

A reliability measure of protein–protein interactions and a reliability measure-based search engine

Many methods developed for estimating the reliability of protein–protein interactions are based on the topology of protein–protein interaction networks. This paper describes a new reliability measure for protein–protein interactions, which does not rely on the topology of protein interaction networks, but expresses biological information on functional roles, sub-cellular localisations and protein classes as a scoring schema. The new measure is useful for filtering many spurious interactions, as well as for estimating the reliability of protein interaction data. In particular, the reliability measure can be used to search protein–protein interactions with the desired reliability in databases. The reliability-based search engine is available at http://yeast.hpid.org. We believe this is the first search engine for interacting proteins, which is made available to public. The search engine and the reliability measure of protein interactions should provide useful information for determining proteins to focus on.     

Improving sensitivity in proteome studies by analysis of false discovery rates for multiple search engines

LC‐MS experiments can generate large quantities of data, for which a variety of database search engines are available to make peptide and protein identifications. Decoy databases are becoming widely used to place statistical confidence in result sets, allowing the false discovery rate (FDR) to be estimated. Different search engines produce different identification sets so employing more than one search engine could result in an increased number of peptides (and proteins) being identified, if an appropriate mechanism for combining data can be defined. We have developed a search engine independent score, based on FDR, which allows peptide identifications from different search engines to be combined, called the FDR Score. The results demonstrate that the observed FDR is significantly different when analysing the set of identifications made by all three search engines, by each pair of search engines or by a single search engine. Our algorithm assigns identifications to groups according to the set of search engines that have made the identification, and re‐assigns the score (combined FDR Score). The combined FDR Score can differentiate between correct and incorrect peptide identifications with high accuracy, allowing on average 35% more peptide identifications to be made at a fixed FDR than using a single search engine.     

MMDB: Entrez's 3D-structure database

Three-dimensional structures are now known within most protein families and it is likely, when searching a sequence database, that one will identify a homolog of known structure. The goal of Entrez's 3D-structure database is to make structure information and the functional annotation it can provide easily accessible to molecular biologists. To this end, Entrez's search engine provides several powerful features: (i) links between databases, for example between a protein's sequence and structure; (ii) pre-computed sequence and structure neighbors; and (iii) structure and sequence/structure alignment visualization. Here, we focus on a new feature of Entrez's Molecular Modeling Database (MMDB): Graphical summaries of the biological annotation available for each 3D structure, based on the results of automated comparative analysis. MMDB is available at: http://www.ncbi.nlm.nih.gov/Entrez/structure.html.     

MMDB: 3D structure data in Entrez

Three-dimensional structures are now known for roughly half of all protein families. It is thus quite likely, in searching sequence databases, that one will encounter a homolog with known structure and be able to use this information to infer structure-function properties. The goal of Entrez's 3D structure database is to make this information accessible and useful to molecular biologists. To this end, Entrez's search engine provides three powerful features: (i) Links between databases; one may search by term matching in Medline((R)), for example, and link to 3D structures reported in these articles. (ii) Sequence and structure neighbors; one may select all sequences similar to one of interest, for example, and link to any known 3D structures. (iii) Sequence and structure visualization; identifying a homolog with known structure, one may view a combined molecular-graphic and alignment display, to infer approximate 3D structure. Entrez's MMDB (Molecular Modeling DataBase) may be accessed at: http://www.ncbi.nlm.nih.gov/Entrez/structure.html     

PATMAT: a searching and extraction program for sequence, pattern and block queries and databases

A program has been developed that provides molecular biologistswith multiple tools for searching databases, yet uses a verysimple interface. PATMATcan use protein or (translated) DNAsequences, patterns or blocks of aligned proteins as queriesof databases consisting of amino acid or nucleotide sequences,patterns or blocks. The ability to search databases of blocksby ‘on-the-fly’ conversion to scoring matrices providesa new tool for detection and evaluation of distant relationships.PATMAT uses a pull-down, menu-driven interface to carry outits multiple searching, extraction and viewing functions. Eachquery or database type is recognized, reported, and the appropriatesearch carried out, with matches and alignments reported inwindows as they occur. Any of the high scoring matches can beexported to a file, viewed and recalled as a query using onlya few keystrokes or mouse selections. Searches of multiple databasefiles are carried out by user selection within a window. PATMATruns under DOS; the searching engine also runs under UNIX.     

PSST-2.0

PSST-2.0 (Protein Data Bank [PDB] Sequence Search Tool) is an updated version of the earlier PSST (Protein Sequence Search Tool), and the philosophy behind the search engine has remained unchanged. PSST-2.0 is a Web-based, interactive search engine developed to retrieve required protein or nucleic acid sequence information and some of its related details, primarily from sequences derived from the structures deposited in the PDB (the database of 3-dimensional [3-D] protein and nucleic acid structures). Additionally, the search engine works for a selected subset of 25% or 90% non-homologous protein chains. For some of the selected options, the search engine produces a detailed output for the user-uploaded, 3-D atomic coordinates of the protein structure (PDB file format) from the client machine through the Web browser. The search engine works on a locally maintained PDB, which is updated every week from the parent server at the Research Collaboratory for Structural Bioinformatics, and hence the search results are up to date at any given time. AVAILABILITY: PSST-2.0 is freely accessible via http://pranag.physics.iisc.ernet.in/psst/ or http://144.16.71.10/psst/.     

MPtopo: A database of membrane protein topology

The reliability of the transmembrane (TM) sequence assignments for membrane proteins (MPs) in standard sequence databases is uncertain because the vast majority are based on hydropathy plots. A database of MPs with dependable assignments is necessary for developing new computational tools for the prediction of MP structure. We have therefore created MPtopo, a database of MPs whose topologies have been verified experimentally by means of crystallography, gene fusion, and other methods. Tests using MPtopo strongly validated four existing MP topology-prediction algorithms. MPtopo is freely available over the internet and can be queried by means of an SQL-based search engine.     

UniProt archive

UniProt Archive (UniParc) is the most comprehensive, non-redundant protein sequence database available. Its protein sequences are retrieved from predominant, publicly accessible resources. All new and updated protein sequences are collected and loaded daily into UniParc for full coverage. To avoid redundancy, each unique sequence is stored only once with a stable protein identifier, which can be used later in UniParc to identify the same protein in all source databases. When proteins are loaded into the database, database cross-references are created to link them to the origins of the sequences. As a result, performing a sequence search against UniParc is equivalent to performing the same search against all databases cross-referenced by UniParc. UniParc contains only protein sequences and database cross-references; all other information must be retrieved from the source databases.     

Incremental generation of summarized clustering hierarchy for protein family analysis

MOTIVATION: Protein sequence clustering has been widely exploited to facilitate in-depth analysis of protein functions and families. For some applications of protein sequence clustering, it is highly desirable that a hierarchical structure, also referred to as dendrogram, which shows how proteins are clustered at various levels, is generated. However, as the sizes of contemporary protein databases continue to grow at rapid rates, it is of great interest to develop some summarization mechanisms so that the users can browse the dendrogram and/or search for the desired information more effectively. RESULTS: In this paper, the design of a novel incremental clustering algorithm aimed at generating summarized dendrograms for analysis of protein databases is described. The proposed incremental clustering algorithm employs a statistics-based model to summarize the distributions of the similarity scores among the proteins in the database and to control formation of clusters. Experimental results reveal that, due to the summarization mechanism incorporated, the proposed incremental clustering algorithm offers the users highly concise dendrograms for analysis of protein clusters with biological significance. Another distinction of the proposed algorithm is its incremental nature. As the sizes of the contemporary protein databases continue to grow at fast rates, due to the concern of efficiency, it is desirable that cluster analysis of a protein database can be carried out incrementally, when the protein database is updated. Experimental results with the Swiss-Prot protein database reveal that the time complexity for carrying out incremental clustering with k new proteins added into the database containing n proteins is O(n2betalogn), where beta congruent with 0.865, provided that k < n. AVAILABILITY: The Linux executable is available on the following supplementary page.     

The protein information resource (PIR)

The Protein Information Resource (PIR) produces the largest, most comprehensive, annotated protein sequence database in the public domain, the PIR-International Protein Sequence Database, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Sequence Database (JIPID). The expanded PIR WWW site allows sequence similarity and text searching of the Protein Sequence Database and auxiliary databases. Several new web-based search engines combine searches of sequence similarity and database annotation to facilitate the analysis and functional identification of proteins. New capabilities for searching the PIR sequence databases include annotation-sorted search, domain search, combined global and domain search, and interactive text searches. The PIR-International databases and search tools are accessible on the PIR WWW site at http://pir.georgetown.edu and at the MIPS WWW site at http://www. mips.biochem.mpg.de. The PIR-International Protein Sequence Database and other files are also available by FTP.     

Automated genome sequence analysis and annotation.

MOTIVATION: Large-scale genome projects generate a rapidly increasing number of sequences, most of them biochemically uncharacterized. Research in bioinformatics contributes to the development of methods for the computational characterization of these sequences. However, the installation and application of these methods require experience and are time consuming. RESULTS: We present here an automatic system for preliminary functional annotation of protein sequences that has been applied to the analysis of sets of sequences from complete genomes, both to refine overall performance and to make new discoveries comparable to those made by human experts. The GeneQuiz system includes a Web-based browser that allows examination of the evidence leading to an automatic annotation and offers additional information, views of the results, and links to biological databases that complement the automatic analysis. System structure and operating principles concerning the use of multiple sequence databases, underlying sequence analysis tools, lexical analyses of database annotations and decision criteria for functional assignments are detailed. The system makes automatic quality assessments of results based on prior experience with the underlying sequence analysis tools; overall error rates in functional assignment are estimated at 2.5-5% for cases annotated with highest reliability ('clear' cases). Sources of over-interpretation of results are discussed with proposals for improvement. A conservative definition for reporting 'new findings' that takes account of database maturity is presented along with examples of possible kinds of discoveries (new function, family and superfamily) made by the system. System performance in relation to sequence database coverage, database dynamics and database search methods is analysed, demonstrating the inherent advantages of an integrated automatic approach using multiple databases and search methods applied in an objective and repeatable manner. AVAILABILITY: The GeneQuiz system is publicly available for analysis of protein sequences through a Web server at http://www.sander.ebi.ac. uk/gqsrv/submit     

HOMSTRAD: a database of protein structure alignments for homologous families.

We describe a database of protein structure alignments for homologous families. The database HOMSTRAD presently contains 130 protein families and 590 aligned structures, which have been selected on the basis of quality of the X-ray analysis and accuracy of the structure. For each family, the database provides a structure-based alignment derived using COMPARER and annotated with JOY in a special format that represents the local structural environment of each amino acid residue. HOMSTRAD also provides a set of superposed atomic coordinates obtained using MNYFIT, which can be viewed with a graphical user interface or used for comparative modeling studies. The database is freely available on the World Wide Web at: http://www-cryst.bioc.cam. ac.uk/-homstrad/, with search facilities and links to other databases.