The RESID Database of protein structure modifications.

Because the number of post-translational modifications requiring standardized annotation in the PIR-International Protein Sequence Database was large and steadily increasing, a database of protein structure modifications was constructed in 1993 to assist in producing appropriate feature annotations for covalent binding sites, modified sites and cross-links. In 1995 RESID was publicly released as a PIR-International text database distributed on CD-ROM and accessible through the ATLAS program. In 1998 it was made available on the PIR Web site at http://www-nbrf.georgetown.edu/pir/searchdb++ +.html . The RESID Database includes such information as: systematic and frequently observed alternate names; Chemical s Service registry numbers; atomic formulas and weights; enzyme activities; indicators forN-terminal, C-terminal or peptide chain cross-link modifications; keywords; and literature citations with database cross-references. The RESID Database can be used to predict atomic masses for peptides, and is being enhanced to provide molecular structures for graphical presentation on the PIR Web site using widely available molecular viewing programs.     

The RESID Database of protein structure modifications and the NRL-3D Sequence-Structure Database

The RESID Database is a comprehensive collection of annotations and structures for protein post-translational modifications including N-terminal, C-terminal and peptide chain cross-link modifications. The RESID Database includes systematic and frequently observed alternate names, Chemical Abstracts Service registry numbers, atomic formulas and weights, enzyme activities, taxonomic range, keywords, literature citations with database cross-references, structural diagrams and molecular models. The NRL-3D Sequence-Structure Database is derived from the three-dimensional structure of proteins deposited with the Research Collaboratory for Structural Bioinformatics Protein Data Bank. The NRL-3D Database includes standardized and frequently observed alternate names, sources, keywords, literature citations, experimental conditions and searchable sequences from model coordinates. These databases are freely accessible through the National Cancer Institute-Frederick Advanced Biomedical Computing Center at these web sites: http://www. ncifcrf.gov/RESID, http://www.ncifcrf.gov/NRL-3D; or at these National Biomedical Research Foundation Protein Information Resource web sites: http://pir.georgetown.edu/pirwww/dbinfo/resid .html, http://pir.georgetown.edu/pirwww/dbinfo/nrl3d .html     

PTMD: A Database of Human Disease-associated Post-translational Modifications

Various posttranslational modifications(PTMs) participate in nearly all aspects of biological processes by regulating protein functions, and aberrant states of PTMs are frequently implicated in human diseases. Therefore, an integral resource of PTM–disease associations(PDAs)would be a great help for both academic research and clinical use. In this work, we reported PTMD,a well-curated database containing PTMs that are associated with human diseases. We manually collected 1950 known PDAs in 749 proteins for 23 types of PTMs and 275 types of diseases from the literature. Database analyses show that phosphorylation has the largest number of disease associations, whereas neurologic diseases have the largest number of PTM associations. We classified all known PDAs into six classes according to the PTM status in diseases and demonstrated that the upregulation and presence of PTM events account for a predominant proportion of diseaseassociated PTM events. By reconstructing a disease–gene network, we observed that breast cancershave the largest number of associated PTMs and AKT1 has the largest number of PTMs connected to diseases. Finally, the PTMD database was developed with detailed annotations and can be a useful resource for further analyzing the relations between PTMs and human diseases. PTMD is freely accessible at http://ptmd.biocuckoo.org.     

The Protein Mutant Database.

Currently the protein mutant database (PMD) contains over 81 000 mutants, including artificial as well as natural mutants of various proteins extracted from about 10 000 articles. We recently developed a powerful viewing and retrieving system (http://pmd.ddbj.nig.ac.jp), which is integrated with the sequence and tertiary structure databases. The system has the following features: (i) mutated sequences are displayed after being automatically generated from the information described in the entry together with the sequence data of wild-type proteins integrated. This is a convenient feature because it allows one to see the position of altered amino acids (shown in a different color) in the entire sequence of a wild-type protein; (ii) for those proteins whose 3D structures have been experimentally determined, a 3D structure is displayed to show mutation sites in a different color; (iii) a sequence homology search against PMD can be carried out with any query sequence; (iv) a summary of mutations of homologous sequences can be displayed, which shows all the mutations at a certain site of a protein, recorded throughout the PMD.     

The Pfam Protein Families Database

Pfam is a large collection of protein multiple sequence alignments and profile hidden Markov models. Pfam is available on the World Wide Web in the UK at http://www.sanger.ac.uk/Software/Pfam/, in Sweden at http://www.cgb.ki.se/Pfam/, in France at http://pfam.jouy.inra.fr/ and in the US at http://pfam.wustl.edu/. The latest version (6.6) of Pfam contains 3071 families, which match 69% of proteins in SWISS-PROT 39 and TrEMBL 14. Structural data, where available, have been utilised to ensure that Pfam families correspond with structural domains, and to improve domain-based annotation. Predictions of non-domain regions are now also included. In addition to secondary structure, Pfam multiple sequence alignments now contain active site residue mark-up. New search tools, including taxonomy search and domain query, greatly add to the functionality and usability of the Pfam resource.     

The PIR-International Protein Sequence Database.

From its origin the Protein Sequence Database has been designed to support research and has focused on comprehensive coverage, quality control and organization of the data in accordance with biological principles. Since 1988 the database has been maintained collaboratively within the framework of PIR-International, an association of macromolecular sequence data collection centers dedicated to fostering international cooperation as an essential element in the development of scientific databases. The database is widely distributed and is available on the World Wide Web, via ftp, email server, on CD-ROM and magnetic media. It is widely redistributed and incorporated into many other protein sequence data compilations, including SWISS-PROT and the Entrez system of the NCBI.     

The PIR-International Protein Sequence Database.

PIR-International is an association of macromolecular sequence data collection centers dedicated to fostering international cooperation as an essential element in the development of scientific databases. A major objective of PIR-International is to continue the development of the Protein Sequence Database as an essential public resource for protein sequence information. This paper briefly describes the architecture of the Protein Sequence Database and how it and associated data sets are distributed and can be accessed electronically.     

The RESID database of protein structure modifications: 2000 update

The RESID Database contains supplemental information on post-translational modifications for the standardized annotations appearing in the PIR-International Protein Sequence Database. The RESID Database includes: systematic and frequently observed alternate names, Chemical s Service registry numbers, atomic formulas and weights, enzyme activities, indicators for N-terminal, C-terminal or peptide chain cross-link modifications, keywords, literature citations with database cross-references, structural diagrams and molecular models. Since 1995 updates of the RESID Database have appeared as often as weekly, and full releases appear quarterly. The database is freely accessible through the PIR Web site http://pir.georgetown.edu/pirwww/dbinfo/resid.html and by FTP.     

蛋白质翻译后修饰研究进展

翻译后修饰在蛋白质加工、成熟的过程中发挥着重要的作用,它可以改变蛋白质的物理、化学性质,影响蛋白质的空间构象、立体位阻及其稳定性,进而对蛋白质的生物学活性产生作用,引起蛋白质的功能改变。修饰基团自身的结构特性对蛋白质的性质、功能也会产生深远的影响。在已有的研究基础上,综述蛋白质翻译后修饰的主要类型以及各修饰作用潜在的生物学功能。     

PSPDB: Plant Stress Protein Database

Plants produce various proteins to overcome biotic and abiotic stresses. Current plant stress databases report plant genes without protein annotations specific to these stresses. To date, according to our findings, a unique plant stress protein database for both biotic and abiotic stresses is not available explicitly for plant biologists that describe linking out to other related databases. This need initiated us to formulate a distinctive database that includes important resources for stress-based factors. We developed the Plant Stress Protein Database (PSPDB), a web-accessible resource that covers 2,064 manually curated plant stress proteins from a wide array of 134 plant species with 30 different types of biotic and abiotic stresses. Functional and experimental validation of proteins associated with biotic and abiotic stresses has been employed as the sole criterion for inclusion in the database. The database is available at http://www.bioclues.org/pspdb/.     

The Essential Role of Mass Spectrometry in Characterizing Protein Structure: Mapping Posttranslational Modifications

Over the last few years we have developed mass spectrometry-based approaches for selective identification of a variety of posttranslational modifications, and for sequencing the modified peptides. These methods do not involve radiolabeling or derivatization. Instead, modification-specific fragment ions are produced by collision-induced dissociation (CID) during analysis of peptides by ESMS. The formation and detection of these marker ions on-the-fly during the LC-ESMS analysis of a protein digest is a powerful technique for identifying posttranslationally modified peptides. Using the marker ion strategy in an orthogonal fashion, a precursor ion scan can detect peptides which give rise to a diagnostic fragment ion, even in an unfractionated protein digest. Once the modified peptide has been located, the appropriate precursor ion can be sequenced by tandem MS. The utility and interplay of this approach to mapping PTM is illustrated with examples that involve protein glycosylation and phosphorylation.     

HPID: the Human Protein Interaction Database

The Human Protein Interaction Database (http://www.hpid.org) was designed (1) to provide human protein interaction information pre-computed from existing structural and experimental data, (2) to predict potential interactions between proteins submitted by users and (3) to provide a depository for new human protein interaction data from users. Two types of interaction are available from the pre-computed data: (1) interactions at the protein superfamily level and (2) those transferred from the interactions of yeast proteins. Interactions at the superfamily level were obtained by locating known structural interactions of the PDB in the SCOP domains and identifying homologs of the domains in the human proteins. Interactions transferred from yeast proteins were obtained by identifying homologs of the yeast proteins in the human proteins. For each human protein in the database and each query submitted by users, the protein superfamilies and yeast proteins assigned to the protein are shown, along with their interacting partners. We have also developed a set of web-based programs so that users can visualize and analyze protein interaction networks in order to explore the networks further. AVAILABILITY: http://www.hpid.org.     

Focus on Metabolism: Posttranslational Protein Modifications in Plant Metabolism

Posttranslational modifications (PTMs) of proteins greatly expand proteome diversity, increase functionality, and allow for rapid responses, all at relatively low costs for the cell. PTMs play key roles in plants through their impact on signaling, gene expression, protein stability and interactions, and enzyme kinetics. Following a brief discussion of the experimental and bioinformatics challenges of PTM identification, localization, and quantification (occupancy), a concise overview is provided of the major PTMs and their (potential) functional consequences in plants, with emphasis on plant metabolism. Classic examples that illustrate the regulation of plant metabolic enzymes and pathways by PTMs and their cross talk are summarized. Recent large-scale proteomics studies mapped many PTMs to a wide range of metabolic functions. Unraveling of the PTM code, i.e. a predictive understanding of the (combinatorial) consequences of PTMs, is needed to convert this growing wealth of data into an understanding of plant metabolic regulation.The primary amino acid sequence of proteins is defined by the translated mRNA, often followed by N- or C-terminal cleavages for preprocessing, maturation, and/or activation. Proteins can undergo further reversible or irreversible posttranslational modifications (PTMs) of specific amino acid residues. Proteins are directly responsible for the production of plant metabolites because they act as enzymes or as regulators of enzymes. Ultimately, most proteins in a plant cell can affect plant metabolism (e.g. through effects on plant gene expression, cell fate and development, structural support, transport, etc.). Many metabolic enzymes and their regulators undergo a variety of PTMs, possibly resulting in changes in oligomeric state, stabilization/degradation, and (de)activation (Huber and Hardin, 2004), and PTMs can facilitate the optimization of metabolic flux. However, the direct in vivo consequence of a PTM on a metabolic enzyme or pathway is frequently not very clear, in part because it requires measurements of input and output of the reactions, including flux through the enzyme or pathway. This Update will start out with a short overview on the major PTMs observed for each amino acid residue (PTMs, including determination of the localization within proteins (i.e. the specific residues) and occupancy. Challenges in dealing with multiple PTMs per protein and cross talk between PTMs will be briefly outlined. We then describe the major physiological PTMs observed in plants as well as PTMs that are nonenzymatically induced during sample preparation (PTMs, in particular for enzymes in primary metabolism (Calvin cycle, glycolysis, and respiration) and the C4 shuttle accommodating photosynthesis in C4 plants (PTMs observed in plants

Negative Example Selection for Protein Function Prediction: The NoGO Database

Negative examples – genes that are known not to carry out a given protein function – are rarely recorded in genome and proteome annotation databases, such as the Gene Ontology database. Negative examples are required, however, for several of the most powerful machine learning methods for integrative protein function prediction. Most protein function prediction efforts have relied on a variety of heuristics for the choice of negative examples. Determining the accuracy of methods for negative example prediction is itself a non-trivial task, given that the Open World Assumption as applied to gene annotations rules out many traditional validation metrics. We present a rigorous comparison of these heuristics, utilizing a temporal holdout, and a novel evaluation strategy for negative examples. We add to this comparison several algorithms adapted from Positive-Unlabeled learning scenarios in text-classification, which are the current state of the art methods for generating negative examples in low-density annotation contexts. Lastly, we present two novel algorithms of our own construction, one based on empirical conditional probability, and the other using topic modeling applied to genes and annotations. We demonstrate that our algorithms achieve significantly fewer incorrect negative example predictions than the current state of the art, using multiple benchmarks covering multiple organisms. Our methods may be applied to generate negative examples for any type of method that deals with protein function, and to this end we provide a database of negative examples in several well-studied organisms, for general use (The NoGO database, available at: bonneaulab.bio.nyu.edu/nogo.html).