MIPS: a database for protein sequences and complete genomes.

Science.gov (United States)

Mewes, H W; Hani, J; Pfeiffer, F; Frishman, D

1998-01-01

The MIPS group [Munich Information Center for Protein Sequences of the German National Center for Environment and Health (GSF)] at the Max-Planck-Institute for Biochemistry, Martinsried near Munich, Germany, is involved in a number of data collection activities, including a comprehensive database of the yeast genome, a database reflecting the progress in sequencing the Arabidopsis thaliana genome, the systematic analysis of other small genomes and the collection of protein sequence data within the framework of the PIR-International Protein Sequence Database (described elsewhere in this volume). Through its WWW server (http://www.mips.biochem.mpg.de ) MIPS provides access to a variety of generic databases, including a database of protein families as well as automatically generated data by the systematic application of sequence analysis algorithms. The yeast genome sequence and its related information was also compiled on CD-ROM to provide dynamic interactive access to the 16 chromosomes of the first eukaryotic genome unraveled. PMID:9399795

TOPDOM: database of conservatively located domains and motifs in proteins.

Science.gov (United States)

Varga, Julia; Dobson, László; Tusnády, Gábor E

2016-09-01

The TOPDOM database-originally created as a collection of domains and motifs located consistently on the same side of the membranes in α-helical transmembrane proteins-has been updated and extended by taking into consideration consistently localized domains and motifs in globular proteins, too. By taking advantage of the recently developed CCTOP algorithm to determine the type of a protein and predict topology in case of transmembrane proteins, and by applying a thorough search for domains and motifs as well as utilizing the most up-to-date version of all source databases, we managed to reach a 6-fold increase in the size of the whole database and a 2-fold increase in the number of transmembrane proteins. TOPDOM database is available at http://topdom.enzim.hu The webpage utilizes the common Apache, PHP5 and MySQL software to provide the user interface for accessing and searching the database. The database itself is generated on a high performance computer. tusnady.gabor@ttk.mta.hu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

MultitaskProtDB: a database of multitasking proteins.

Science.gov (United States)

Hernández, Sergio; Ferragut, Gabriela; Amela, Isaac; Perez-Pons, JosepAntoni; Piñol, Jaume; Mozo-Villarias, Angel; Cedano, Juan; Querol, Enrique

2014-01-01

We have compiled MultitaskProtDB, available online at http://wallace.uab.es/multitask, to provide a repository where the many multitasking proteins found in the literature can be stored. Multitasking or moonlighting is the capability of some proteins to execute two or more biological functions. Usually, multitasking proteins are experimentally revealed by serendipity. This ability of proteins to perform multitasking functions helps us to understand one of the ways used by cells to perform many complex functions with a limited number of genes. Even so, the study of this phenomenon is complex because, among other things, there is no database of moonlighting proteins. The existence of such a tool facilitates the collection and dissemination of these important data. This work reports the database, MultitaskProtDB, which is designed as a friendly user web page containing >288 multitasking proteins with their NCBI and UniProt accession numbers, canonical and additional biological functions, monomeric/oligomeric states, PDB codes when available and bibliographic references. This database also serves to gain insight into some characteristics of multitasking proteins such as frequencies of the different pairs of functions, phylogenetic conservation and so forth.

Proteomics: Protein Identification Using Online Databases

Science.gov (United States)

Eurich, Chris; Fields, Peter A.; Rice, Elizabeth

2012-01-01

Proteomics is an emerging area of systems biology that allows simultaneous study of thousands of proteins expressed in cells, tissues, or whole organisms. We have developed this activity to enable high school or college students to explore proteomic databases using mass spectrometry data files generated from yeast proteins in a college laboratory…

Protein structure database search and evolutionary classification.

Science.gov (United States)

Yang, Jinn-Moon; Tung, Chi-Hua

2006-01-01

As more protein structures become available and structural genomics efforts provide structural models in a genome-wide strategy, there is a growing need for fast and accurate methods for discovering homologous proteins and evolutionary classifications of newly determined structures. We have developed 3D-BLAST, in part, to address these issues. 3D-BLAST is as fast as BLAST and calculates the statistical significance (E-value) of an alignment to indicate the reliability of the prediction. Using this method, we first identified 23 states of the structural alphabet that represent pattern profiles of the backbone fragments and then used them to represent protein structure databases as structural alphabet sequence databases (SADB). Our method enhanced BLAST as a search method, using a new structural alphabet substitution matrix (SASM) to find the longest common substructures with high-scoring structured segment pairs from an SADB database. Using personal computers with Intel Pentium4 (2.8 GHz) processors, our method searched more than 10 000 protein structures in 1.3 s and achieved a good agreement with search results from detailed structure alignment methods. [3D-BLAST is available at http://3d-blast.life.nctu.edu.tw].

Role of the ubiquitin system and tumor viruses in AIDS-related cancer

Directory of Open Access Journals (Sweden)

Pagano Joseph S

2007-11-01

Full Text Available Abstract Tumor viruses are linked to approximately 20% of human malignancies worldwide. This review focuses on examples of human oncogenic viruses that manipulate the ubiquitin system in a subset of viral malignancies; those associated with AIDS. The viruses include Kaposi's sarcoma herpesvirus, Epstein-Barr virus and human papilloma virus, which are causally linked to Kaposi's sarcoma, certain B-cell lymphomas and cervical cancer, respectively. We discuss the molecular mechanisms by which these viruses subvert the ubiquitin system and potential viral targets for anti-cancer therapy from the perspective of this system. Publication history: Republished from Current BioData's Targeted Proteins database (TPdb; http://www.targetedproteinsdb.com.

MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions.

Science.gov (United States)

Hayashi, Takanori; Matsuzaki, Yuri; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka

2018-05-08

Protein-protein interactions (PPIs) play several roles in living cells, and computational PPI prediction is a major focus of many researchers. The three-dimensional (3D) structure and binding surface are important for the design of PPI inhibitors. Therefore, rigid body protein-protein docking calculations for two protein structures are expected to allow elucidation of PPIs different from known complexes in terms of 3D structures because known PPI information is not explicitly required. We have developed rapid PPI prediction software based on protein-protein docking, called MEGADOCK. In order to fully utilize the benefits of computational PPI predictions, it is necessary to construct a comprehensive database to gather prediction results and their predicted 3D complex structures and to make them easily accessible. Although several databases exist that provide predicted PPIs, the previous databases do not contain a sufficient number of entries for the purpose of discovering novel PPIs. In this study, we constructed an integrated database of MEGADOCK PPI predictions, named MEGADOCK-Web. MEGADOCK-Web provides more than 10 times the number of PPI predictions than previous databases and enables users to conduct PPI predictions that cannot be found in conventional PPI prediction databases. In MEGADOCK-Web, there are 7528 protein chains and 28,331,628 predicted PPIs from all possible combinations of those proteins. Each protein structure is annotated with PDB ID, chain ID, UniProt AC, related KEGG pathway IDs, and known PPI pairs. Additionally, MEGADOCK-Web provides four powerful functions: 1) searching precalculated PPI predictions, 2) providing annotations for each predicted protein pair with an experimentally known PPI, 3) visualizing candidates that may interact with the query protein on biochemical pathways, and 4) visualizing predicted complex structures through a 3D molecular viewer. MEGADOCK-Web provides a huge amount of comprehensive PPI predictions based on

Protein - AT Atlas | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data ..._protein.zip File URL: ftp://ftp.biosciencedbc.jp/archive/at_atlas/LATEST/at_atla...About This Database Database Description Download License Update History of This Database Site Policy | Contact Us Protein - AT Atlas | LSDB Archive ...

cuticleDB: a relational database of Arthropod cuticular proteins

Directory of Open Access Journals (Sweden)

Willis Judith H

2004-09-01

Full Text Available Abstract Background The insect exoskeleton or cuticle is a bi-partite composite of proteins and chitin that provides protective, skeletal and structural functions. Little information is available about the molecular structure of this important complex that exhibits a helicoidal architecture. Scores of sequences of cuticular proteins have been obtained from direct protein sequencing, from cDNAs, and from genomic analyses. Most of these cuticular protein sequences contain motifs found only in arthropod proteins. Description cuticleDB is a relational database containing all structural proteins of Arthropod cuticle identified to date. Many come from direct sequencing of proteins isolated from cuticle and from sequences from cDNAs that share common features with these authentic cuticular proteins. It also includes proteins from the Drosophila melanogaster and the Anopheles gambiae genomes, that have been predicted to be cuticular proteins, based on a Pfam motif (PF00379 responsible for chitin binding in Arthropod cuticle. The total number of the database entries is 445: 370 derive from insects, 60 from Crustacea and 15 from Chelicerata. The database can be accessed from our web server at http://bioinformatics.biol.uoa.gr/cuticleDB. Conclusions CuticleDB was primarily designed to contain correct and full annotation of cuticular protein data. The database will be of help to future genome annotators. Users will be able to test hypotheses for the existence of known and also of yet unknown motifs in cuticular proteins. An analysis of motifs may contribute to understanding how proteins contribute to the physical properties of cuticle as well as to the precise nature of their interaction with chitin.

DB-PABP: a database of polyanion-binding proteins.

Science.gov (United States)

Fang, Jianwen; Dong, Yinghua; Salamat-Miller, Nazila; Middaugh, C Russell

2008-01-01

The interactions between polyanions (PAs) and polyanion-binding proteins (PABPs) have been found to play significant roles in many essential biological processes including intracellular organization, transport and protein folding. Furthermore, many neurodegenerative disease-related proteins are PABPs. Thus, a better understanding of PA/PABP interactions may not only enhance our understandings of biological systems but also provide new clues to these deadly diseases. The literature in this field is widely scattered, suggesting the need for a comprehensive and searchable database of PABPs. The DB-PABP is a comprehensive, manually curated and searchable database of experimentally characterized PABPs. It is freely available and can be accessed online at http://pabp.bcf.ku.edu/DB_PABP/. The DB-PABP was implemented as a MySQL relational database. An interactive web interface was created using Java Server Pages (JSP). The search page of the database is organized into a main search form and a section for utilities. The main search form enables custom searches via four menus: protein names, polyanion names, the source species of the proteins and the methods used to discover the interactions. Available utilities include a commonality matrix, a function of listing PABPs by the number of interacting polyanions and a string search for author surnames. The DB-PABP is maintained at the University of Kansas. We encourage users to provide feedback and submit new data and references.

A protein relational database and protein family knowledge bases to facilitate structure-based design analyses.

Science.gov (United States)

Mobilio, Dominick; Walker, Gary; Brooijmans, Natasja; Nilakantan, Ramaswamy; Denny, R Aldrin; Dejoannis, Jason; Feyfant, Eric; Kowticwar, Rupesh K; Mankala, Jyoti; Palli, Satish; Punyamantula, Sairam; Tatipally, Maneesh; John, Reji K; Humblet, Christine

2010-08-01

The Protein Data Bank is the most comprehensive source of experimental macromolecular structures. It can, however, be difficult at times to locate relevant structures with the Protein Data Bank search interface. This is particularly true when searching for complexes containing specific interactions between protein and ligand atoms. Moreover, searching within a family of proteins can be tedious. For example, one cannot search for some conserved residue as residue numbers vary across structures. We describe herein three databases, Protein Relational Database, Kinase Knowledge Base, and Matrix Metalloproteinase Knowledge Base, containing protein structures from the Protein Data Bank. In Protein Relational Database, atom-atom distances between protein and ligand have been precalculated allowing for millisecond retrieval based on atom identity and distance constraints. Ring centroids, centroid-centroid and centroid-atom distances and angles have also been included permitting queries for pi-stacking interactions and other structural motifs involving rings. Other geometric features can be searched through the inclusion of residue pair and triplet distances. In Kinase Knowledge Base and Matrix Metalloproteinase Knowledge Base, the catalytic domains have been aligned into common residue numbering schemes. Thus, by searching across Protein Relational Database and Kinase Knowledge Base, one can easily retrieve structures wherein, for example, a ligand of interest is making contact with the gatekeeper residue.

SynechoNET: integrated protein-protein interaction database of a model cyanobacterium Synechocystis sp. PCC 6803

OpenAIRE

Kim, Woo-Yeon; Kang, Sungsoo; Kim, Byoung-Chul; Oh, Jeehyun; Cho, Seongwoong; Bhak, Jong; Choi, Jong-Soon

2008-01-01

Background Cyanobacteria are model organisms for studying photosynthesis, carbon and nitrogen assimilation, evolution of plant plastids, and adaptability to environmental stresses. Despite many studies on cyanobacteria, there is no web-based database of their regulatory and signaling protein-protein interaction networks to date. Description We report a database and website SynechoNET that provides predicted protein-protein interactions. SynechoNET shows cyanobacterial domain-domain interactio...

Protein (Cyanobacteria) - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available ut This Database Database Description Download License Update History of This Database Site Policy | Contact Us Protein (Cyanobacteria) - PGDBj - Ortholog DB | LSDB Archive ... ...List Contact us PGDBj - Ortholog DB Protein (Cyanobacteria) Data detail Data name Protein (Cyanobacteria) DO...switchLanguage; BLAST Search Image Search Home About Archive Update History Data

Applications of Protein Thermodynamic Database for Understanding Protein Mutant Stability and Designing Stable Mutants.

Science.gov (United States)

Gromiha, M Michael; Anoosha, P; Huang, Liang-Tsung

2016-01-01

Protein stability is the free energy difference between unfolded and folded states of a protein, which lies in the range of 5-25 kcal/mol. Experimentally, protein stability is measured with circular dichroism, differential scanning calorimetry, and fluorescence spectroscopy using thermal and denaturant denaturation methods. These experimental data have been accumulated in the form of a database, ProTherm, thermodynamic database for proteins and mutants. It also contains sequence and structure information of a protein, experimental methods and conditions, and literature information. Different features such as search, display, and sorting options and visualization tools have been incorporated in the database. ProTherm is a valuable resource for understanding/predicting the stability of proteins and it can be accessed at http://www.abren.net/protherm/ . ProTherm has been effectively used to examine the relationship among thermodynamics, structure, and function of proteins. We describe the recent progress on the development of methods for understanding/predicting protein stability, such as (1) general trends on mutational effects on stability, (2) relationship between the stability of protein mutants and amino acid properties, (3) applications of protein three-dimensional structures for predicting their stability upon point mutations, (4) prediction of protein stability upon single mutations from amino acid sequence, and (5) prediction methods for addressing double mutants. A list of online resources for predicting has also been provided.

SHEETSPAIR: A Database of Amino Acid Pairs in Protein Sheet Structures

Directory of Open Access Journals (Sweden)

Ning Zhang

2007-10-01

Full Text Available Within folded strands of a protein, amino acids (AAs on every adjacent two strands form a pair of AAs. To explore the interactions between strands in a protein sheet structure, we have established an Internet-accessible relational database named SheetsPairs based on SQL Server 2000. The database has collected AAs pairs in proteins with detailed information. Furthermore, it utilizes a non-freetext database structure to store protein sequences and a specific database table with a unique number to store strands, which provides more searching options and rapid and accurate access to data queries. An IIS web server has been set up for data retrieval through a custom web interface, which enables complex data queries. Also searchable are parallel or anti-parallel folded strands and the list of strands in a specified protein.

MIPS: a database for protein sequences, homology data and yeast genome information.

Science.gov (United States)

Mewes, H W; Albermann, K; Heumann, K; Liebl, S; Pfeiffer, F

1997-01-01

The MIPS group (Martinsried Institute for Protein Sequences) at the Max-Planck-Institute for Biochemistry, Martinsried near Munich, Germany, collects, processes and distributes protein sequence data within the framework of the tripartite association of the PIR-International Protein Sequence Database (,). MIPS contributes nearly 50% of the data input to the PIR-International Protein Sequence Database. The database is distributed on CD-ROM together with PATCHX, an exhaustive supplement of unique, unverified protein sequences from external sources compiled by MIPS. Through its WWW server (http://www.mips.biochem.mpg.de/ ) MIPS permits internet access to sequence databases, homology data and to yeast genome information. (i) Sequence similarity results from the FASTA program () are stored in the FASTA database for all proteins from PIR-International and PATCHX. The database is dynamically maintained and permits instant access to FASTA results. (ii) Starting with FASTA database queries, proteins have been classified into families and superfamilies (PROT-FAM). (iii) The HPT (hashed position tree) data structure () developed at MIPS is a new approach for rapid sequence and pattern searching. (iv) MIPS provides access to the sequence and annotation of the complete yeast genome (), the functional classification of yeast genes (FunCat) and its graphical display, the 'Genome Browser' (). A CD-ROM based on the JAVA programming language providing dynamic interactive access to the yeast genome and the related protein sequences has been compiled and is available on request. PMID:9016498

PROXiMATE: a database of mutant protein-protein complex thermodynamics and kinetics.

Science.gov (United States)

Jemimah, Sherlyn; Yugandhar, K; Michael Gromiha, M

2017-09-01

We have developed PROXiMATE, a database of thermodynamic data for more than 6000 missense mutations in 174 heterodimeric protein-protein complexes, supplemented with interaction network data from STRING database, solvent accessibility, sequence, structural and functional information, experimental conditions and literature information. Additional features include complex structure visualization, search and display options, download options and a provision for users to upload their data. The database is freely available at http://www.iitm.ac.in/bioinfo/PROXiMATE/ . The website is implemented in Python, and supports recent versions of major browsers such as IE10, Firefox, Chrome and Opera. gromiha@iitm.ac.in. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

ProDis-ContSHC: learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrieval.

Science.gov (United States)

Wang, Jingyan; Gao, Xin; Wang, Quanquan; Li, Yongping

2012-05-08

The need to retrieve or classify protein molecules using structure or sequence-based similarity measures underlies a wide range of biomedical applications. Traditional protein search methods rely on a pairwise dissimilarity/similarity measure for comparing a pair of proteins. This kind of pairwise measures suffer from the limitation of neglecting the distribution of other proteins and thus cannot satisfy the need for high accuracy of the retrieval systems. Recent work in the machine learning community has shown that exploiting the global structure of the database and learning the contextual dissimilarity/similarity measures can improve the retrieval performance significantly. However, most existing contextual dissimilarity/similarity learning algorithms work in an unsupervised manner, which does not utilize the information of the known class labels of proteins in the database. In this paper, we propose a novel protein-protein dissimilarity learning algorithm, ProDis-ContSHC. ProDis-ContSHC regularizes an existing dissimilarity measure dij by considering the contextual information of the proteins. The context of a protein is defined by its neighboring proteins. The basic idea is, for a pair of proteins (i, j), if their context N(i) and N(j) is similar to each other, the two proteins should also have a high similarity. We implement this idea by regularizing dij by a factor learned from the context N(i) and N(j).Moreover, we divide the context to hierarchial sub-context and get the contextual dissimilarity vector for each protein pair. Using the class label information of the proteins, we select the relevant (a pair of proteins that has the same class labels) and irrelevant (with different labels) protein pairs, and train an SVM model to distinguish between their contextual dissimilarity vectors. The SVM model is further used to learn a supervised regularizing factor. Finally, with the new Supervised learned Dissimilarity measure, we update the Protein Hierarchial

EKPD: a hierarchical database of eukaryotic protein kinases and protein phosphatases.

Science.gov (United States)

Wang, Yongbo; Liu, Zexian; Cheng, Han; Gao, Tianshun; Pan, Zhicheng; Yang, Qing; Guo, Anyuan; Xue, Yu

2014-01-01

We present here EKPD (http://ekpd.biocuckoo.org), a hierarchical database of eukaryotic protein kinases (PKs) and protein phosphatases (PPs), the key molecules responsible for the reversible phosphorylation of proteins that are involved in almost all aspects of biological processes. As extensive experimental and computational efforts have been carried out to identify PKs and PPs, an integrative resource with detailed classification and annotation information would be of great value for both experimentalists and computational biologists. In this work, we first collected 1855 PKs and 347 PPs from the scientific literature and various public databases. Based on previously established rationales, we classified all of the known PKs and PPs into a hierarchical structure with three levels, i.e. group, family and individual PK/PP. There are 10 groups with 149 families for the PKs and 10 groups with 33 families for the PPs. We constructed 139 and 27 Hidden Markov Model profiles for PK and PP families, respectively. Then we systematically characterized ∼50,000 PKs and >10,000 PPs in eukaryotes. In addition, >500 PKs and >400 PPs were computationally identified by ortholog search. Finally, the online service of the EKPD database was implemented in PHP + MySQL + JavaScript.

PARPs database: A LIMS systems for protein-protein interaction data mining or laboratory information management system

Directory of Open Access Journals (Sweden)

Picard-Cloutier Aude

2007-12-01

Full Text Available Abstract Background In the "post-genome" era, mass spectrometry (MS has become an important method for the analysis of proteins and the rapid advancement of this technique, in combination with other proteomics methods, results in an increasing amount of proteome data. This data must be archived and analysed using specialized bioinformatics tools. Description We herein describe "PARPs database," a data analysis and management pipeline for liquid chromatography tandem mass spectrometry (LC-MS/MS proteomics. PARPs database is a web-based tool whose features include experiment annotation, protein database searching, protein sequence management, as well as data-mining of the peptides and proteins identified. Conclusion Using this pipeline, we have successfully identified several interactions of biological significance between PARP-1 and other proteins, namely RFC-1, 2, 3, 4 and 5.

ProDis-ContSHC: Learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrieval

KAUST Repository

Wang, Jim Jing-Yan

2012-05-08

Background: The need to retrieve or classify protein molecules using structure or sequence-based similarity measures underlies a wide range of biomedical applications. Traditional protein search methods rely on a pairwise dissimilarity/similarity measure for comparing a pair of proteins. This kind of pairwise measures suffer from the limitation of neglecting the distribution of other proteins and thus cannot satisfy the need for high accuracy of the retrieval systems. Recent work in the machine learning community has shown that exploiting the global structure of the database and learning the contextual dissimilarity/similarity measures can improve the retrieval performance significantly. However, most existing contextual dissimilarity/similarity learning algorithms work in an unsupervised manner, which does not utilize the information of the known class labels of proteins in the database.Results: In this paper, we propose a novel protein-protein dissimilarity learning algorithm, ProDis-ContSHC. ProDis-ContSHC regularizes an existing dissimilarity measure dij by considering the contextual information of the proteins. The context of a protein is defined by its neighboring proteins. The basic idea is, for a pair of proteins (i, j), if their context N (i) and N (j) is similar to each other, the two proteins should also have a high similarity. We implement this idea by regularizing dij by a factor learned from the context N (i) and N (j). Moreover, we divide the context to hierarchial sub-context and get the contextual dissimilarity vector for each protein pair. Using the class label information of the proteins, we select the relevant (a pair of proteins that has the same class labels) and irrelevant (with different labels) protein pairs, and train an SVM model to distinguish between their contextual dissimilarity vectors. The SVM model is further used to learn a supervised regularizing factor. Finally, with the new Supervised learned Dissimilarity measure, we update

PDTD: a web-accessible protein database for drug target identification

Directory of Open Access Journals (Sweden)

Gao Zhenting

2008-02-01

Full Text Available Abstract Background Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (Target Fishing Docking http://www.dddc.ac.cn/tarfisdock, which has been used widely by others. Recently, we have constructed a protein target database, Potential Drug Target Database (PDTD, and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation. Description PDTD is a web-accessible protein database for in silico target identification. It currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of >830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores. Conclusion PDTD serves as a comprehensive and

Medicago PhosphoProtein Database: a repository for Medicago truncatula phosphoprotein data

Directory of Open Access Journals (Sweden)

Christopher M. Rose

2012-06-01

Full Text Available The ability of legume crops to fix atmospheric nitrogen via a symbiotic association with soil rhizobia makes them an essential component of many agricultural systems. Initiation of this symbiosis requires protein phosphorylation-mediated signaling in response to rhizobial signals named Nod factors. Medicago truncatula (Medicago is the model system for studying legume biology, making the study of its phosphoproteome essential. Here, we describe the Medicago Phosphoprotein Database (http://phospho.medicago.wisc.edu, a repository built to house phosphoprotein, phosphopeptide, and phosphosite data specific to Medicago. Currently, the Medicago Phosphoprotein Database holds 3,457 unique phosphopeptides that contain 3,404 non-redundant sites of phosphorylation on 829 proteins. Through the web-based interface, users are allowed to browse identified proteins or search for proteins of interest. Furthermore, we allow users to conduct BLAST searches of the database using both peptide sequences and phosphorylation motifs as queries. The data contained within the database are available for download to be investigated at the user’s discretion. The Medicago Phosphoprotein Database will be updated continually with novel phosphoprotein and phosphopeptide identifications, with the intent of constructing an unparalleled compendium of large-scale Medicago phosphorylation data.

Integrated Controlling System and Unified Database for High Throughput Protein Crystallography Experiments

International Nuclear Information System (INIS)

Gaponov, Yu.A.; Igarashi, N.; Hiraki, M.; Sasajima, K.; Matsugaki, N.; Suzuki, M.; Kosuge, T.; Wakatsuki, S.

2004-01-01

An integrated controlling system and a unified database for high throughput protein crystallography experiments have been developed. Main features of protein crystallography experiments (purification, crystallization, crystal harvesting, data collection, data processing) were integrated into the software under development. All information necessary to perform protein crystallography experiments is stored (except raw X-ray data that are stored in a central data server) in a MySQL relational database. The database contains four mutually linked hierarchical trees describing protein crystals, data collection of protein crystal and experimental data processing. A database editor was designed and developed. The editor supports basic database functions to view, create, modify and delete user records in the database. Two search engines were realized: direct search of necessary information in the database and object oriented search. The system is based on TCP/IP secure UNIX sockets with four predefined sending and receiving behaviors, which support communications between all connected servers and clients with remote control functions (creating and modifying data for experimental conditions, data acquisition, viewing experimental data, and performing data processing). Two secure login schemes were designed and developed: a direct method (using the developed Linux clients with secure connection) and an indirect method (using the secure SSL connection using secure X11 support from any operating system with X-terminal and SSH support). A part of the system has been implemented on a new MAD beam line, NW12, at the Photon Factory Advanced Ring for general user experiments

Domain fusion analysis by applying relational algebra to protein sequence and domain databases.

Science.gov (United States)

Truong, Kevin; Ikura, Mitsuhiko

2003-05-06

Domain fusion analysis is a useful method to predict functionally linked proteins that may be involved in direct protein-protein interactions or in the same metabolic or signaling pathway. As separate domain databases like BLOCKS, PROSITE, Pfam, SMART, PRINTS-S, ProDom, TIGRFAMs, and amalgamated domain databases like InterPro continue to grow in size and quality, a computational method to perform domain fusion analysis that leverages on these efforts will become increasingly powerful. This paper proposes a computational method employing relational algebra to find domain fusions in protein sequence databases. The feasibility of this method was illustrated on the SWISS-PROT+TrEMBL sequence database using domain predictions from the Pfam HMM (hidden Markov model) database. We identified 235 and 189 putative functionally linked protein partners in H. sapiens and S. cerevisiae, respectively. From scientific literature, we were able to confirm many of these functional linkages, while the remainder offer testable experimental hypothesis. Results can be viewed at http://calcium.uhnres.utoronto.ca/pi. As the analysis can be computed quickly on any relational database that supports standard SQL (structured query language), it can be dynamically updated along with the sequence and domain databases, thereby improving the quality of predictions over time.

Toxicological relationships between proteins obtained from protein target predictions of large toxicity databases

International Nuclear Information System (INIS)

Nigsch, Florian; Mitchell, John B.O.

2008-01-01

The combination of models for protein target prediction with large databases containing toxicological information for individual molecules allows the derivation of 'toxiclogical' profiles, i.e., to what extent are molecules of known toxicity predicted to interact with a set of protein targets. To predict protein targets of drug-like and toxic molecules, we built a computational multiclass model using the Winnow algorithm based on a dataset of protein targets derived from the MDL Drug Data Report. A 15-fold Monte Carlo cross-validation using 50% of each class for training, and the remaining 50% for testing, provided an assessment of the accuracy of that model. We retained the 3 top-ranking predictions and found that in 82% of all cases the correct target was predicted within these three predictions. The first prediction was the correct one in almost 70% of cases. A model built on the whole protein target dataset was then used to predict the protein targets for 150 000 molecules from the MDL Toxicity Database. We analysed the frequency of the predictions across the panel of protein targets for experimentally determined toxicity classes of all molecules. This allowed us to identify clusters of proteins related by their toxicological profiles, as well as toxicities that are related. Literature-based evidence is provided for some specific clusters to show the relevance of the relationships identified

PACSY, a relational database management system for protein structure and chemical shift analysis.

Science.gov (United States)

Lee, Woonghee; Yu, Wookyung; Kim, Suhkmann; Chang, Iksoo; Lee, Weontae; Markley, John L

2012-10-01

PACSY (Protein structure And Chemical Shift NMR spectroscopY) is a relational database management system that integrates information from the Protein Data Bank, the Biological Magnetic Resonance Data Bank, and the Structural Classification of Proteins database. PACSY provides three-dimensional coordinates and chemical shifts of atoms along with derived information such as torsion angles, solvent accessible surface areas, and hydrophobicity scales. PACSY consists of six relational table types linked to one another for coherence by key identification numbers. Database queries are enabled by advanced search functions supported by an RDBMS server such as MySQL or PostgreSQL. PACSY enables users to search for combinations of information from different database sources in support of their research. Two software packages, PACSY Maker for database creation and PACSY Analyzer for database analysis, are available from http://pacsy.nmrfam.wisc.edu.

PACSY, a relational database management system for protein structure and chemical shift analysis

Energy Technology Data Exchange (ETDEWEB)

Lee, Woonghee, E-mail: whlee@nmrfam.wisc.edu [University of Wisconsin-Madison, National Magnetic Resonance Facility at Madison, and Biochemistry Department (United States); Yu, Wookyung [Center for Proteome Biophysics, Pusan National University, Department of Physics (Korea, Republic of); Kim, Suhkmann [Pusan National University, Department of Chemistry and Chemistry Institute for Functional Materials (Korea, Republic of); Chang, Iksoo [Center for Proteome Biophysics, Pusan National University, Department of Physics (Korea, Republic of); Lee, Weontae, E-mail: wlee@spin.yonsei.ac.kr [Yonsei University, Structural Biochemistry and Molecular Biophysics Laboratory, Department of Biochemistry (Korea, Republic of); Markley, John L., E-mail: markley@nmrfam.wisc.edu [University of Wisconsin-Madison, National Magnetic Resonance Facility at Madison, and Biochemistry Department (United States)

2012-10-15

PACSY (Protein structure And Chemical Shift NMR spectroscopY) is a relational database management system that integrates information from the Protein Data Bank, the Biological Magnetic Resonance Data Bank, and the Structural Classification of Proteins database. PACSY provides three-dimensional coordinates and chemical shifts of atoms along with derived information such as torsion angles, solvent accessible surface areas, and hydrophobicity scales. PACSY consists of six relational table types linked to one another for coherence by key identification numbers. Database queries are enabled by advanced search functions supported by an RDBMS server such as MySQL or PostgreSQL. PACSY enables users to search for combinations of information from different database sources in support of their research. Two software packages, PACSY Maker for database creation and PACSY Analyzer for database analysis, are available from http://pacsy.nmrfam.wisc.eduhttp://pacsy.nmrfam.wisc.edu.

PACSY, a relational database management system for protein structure and chemical shift analysis

Science.gov (United States)

Lee, Woonghee; Yu, Wookyung; Kim, Suhkmann; Chang, Iksoo

2012-01-01

PACSY (Protein structure And Chemical Shift NMR spectroscopY) is a relational database management system that integrates information from the Protein Data Bank, the Biological Magnetic Resonance Data Bank, and the Structural Classification of Proteins database. PACSY provides three-dimensional coordinates and chemical shifts of atoms along with derived information such as torsion angles, solvent accessible surface areas, and hydrophobicity scales. PACSY consists of six relational table types linked to one another for coherence by key identification numbers. Database queries are enabled by advanced search functions supported by an RDBMS server such as MySQL or PostgreSQL. PACSY enables users to search for combinations of information from different database sources in support of their research. Two software packages, PACSY Maker for database creation and PACSY Analyzer for database analysis, are available from http://pacsy.nmrfam.wisc.edu. PMID:22903636

PACSY, a relational database management system for protein structure and chemical shift analysis

International Nuclear Information System (INIS)

Lee, Woonghee; Yu, Wookyung; Kim, Suhkmann; Chang, Iksoo; Lee, Weontae; Markley, John L.

2012-01-01

PACSY (Protein structure And Chemical Shift NMR spectroscopY) is a relational database management system that integrates information from the Protein Data Bank, the Biological Magnetic Resonance Data Bank, and the Structural Classification of Proteins database. PACSY provides three-dimensional coordinates and chemical shifts of atoms along with derived information such as torsion angles, solvent accessible surface areas, and hydrophobicity scales. PACSY consists of six relational table types linked to one another for coherence by key identification numbers. Database queries are enabled by advanced search functions supported by an RDBMS server such as MySQL or PostgreSQL. PACSY enables users to search for combinations of information from different database sources in support of their research. Two software packages, PACSY Maker for database creation and PACSY Analyzer for database analysis, are available from http://pacsy.nmrfam.wisc.eduhttp://pacsy.nmrfam.wisc.edu.

Thermodynamic database for proteins: features and applications.

Science.gov (United States)

Gromiha, M Michael; Sarai, Akinori

2010-01-01

We have developed a thermodynamic database for proteins and mutants, ProTherm, which is a collection of a large number of thermodynamic data on protein stability along with the sequence and structure information, experimental methods and conditions, and literature information. This is a valuable resource for understanding/predicting the stability of proteins, and it can be accessible at http://www.gibk26.bse.kyutech.ac.jp/jouhou/Protherm/protherm.html . ProTherm has several features including various search, display, and sorting options and visualization tools. We have analyzed the data in ProTherm to examine the relationship among thermodynamics, structure, and function of proteins. We describe the progress on the development of methods for understanding/predicting protein stability, such as (i) relationship between the stability of protein mutants and amino acid properties, (ii) average assignment method, (iii) empirical energy functions, (iv) torsion, distance, and contact potentials, and (v) machine learning techniques. The list of online resources for predicting protein stability has also been provided.

ARCPHdb: A comprehensive protein database for SF1 and SF2 helicase from archaea.

Science.gov (United States)

Moukhtar, Mirna; Chaar, Wafi; Abdel-Razzak, Ziad; Khalil, Mohamad; Taha, Samir; Chamieh, Hala

2017-01-01

Superfamily 1 and Superfamily 2 helicases, two of the largest helicase protein families, play vital roles in many biological processes including replication, transcription and translation. Study of helicase proteins in the model microorganisms of archaea have largely contributed to the understanding of their function, architecture and assembly. Based on a large phylogenomics approach, we have identified and classified all SF1 and SF2 protein families in ninety five sequenced archaea genomes. Here we developed an online webserver linked to a specialized protein database named ARCPHdb to provide access for SF1 and SF2 helicase families from archaea. ARCPHdb was implemented using MySQL relational database. Web interfaces were developed using Netbeans. Data were stored according to UniProt accession numbers, NCBI Ref Seq ID, PDB IDs and Entrez Databases. A user-friendly interactive web interface has been developed to browse, search and download archaeal helicase protein sequences, their available 3D structure models, and related documentation available in the literature provided by ARCPHdb. The database provides direct links to matching external databases. The ARCPHdb is the first online database to compile all protein information on SF1 and SF2 helicase from archaea in one platform. This database provides essential resource information for all researchers interested in the field. Copyright © 2016 Elsevier Ltd. All rights reserved.

Efficiency of Database Search for Identification of Mutated and Modified Proteins via Mass Spectrometry

OpenAIRE

Pevzner, Pavel A.; Mulyukov, Zufar; Dancik, Vlado; Tang, Chris L

2001-01-01

Although protein identification by matching tandem mass spectra (MS/MS) against protein databases is a widespread tool in mass spectrometry, the question about reliability of such searches remains open. Absence of rigorous significance scores in MS/MS database search makes it difficult to discard random database hits and may lead to erroneous protein identification, particularly in the case of mutated or post-translationally modified peptides. This problem is especially important for high-thr...

A protein domain interaction interface database: InterPare

Directory of Open Access Journals (Sweden)

Lee Jungsul

2005-08-01

Full Text Available Abstract Background Most proteins function by interacting with other molecules. Their interaction interfaces are highly conserved throughout evolution to avoid undesirable interactions that lead to fatal disorders in cells. Rational drug discovery includes computational methods to identify the interaction sites of lead compounds to the target molecules. Identifying and classifying protein interaction interfaces on a large scale can help researchers discover drug targets more efficiently. Description We introduce a large-scale protein domain interaction interface database called InterPare http://interpare.net. It contains both inter-chain (between chains interfaces and intra-chain (within chain interfaces. InterPare uses three methods to detect interfaces: 1 the geometric distance method for checking the distance between atoms that belong to different domains, 2 Accessible Surface Area (ASA, a method for detecting the buried region of a protein that is detached from a solvent when forming multimers or complexes, and 3 the Voronoi diagram, a computational geometry method that uses a mathematical definition of interface regions. InterPare includes visualization tools to display protein interior, surface, and interaction interfaces. It also provides statistics such as the amino acid propensities of queried protein according to its interior, surface, and interface region. The atom coordinates that belong to interface, surface, and interior regions can be downloaded from the website. Conclusion InterPare is an open and public database server for protein interaction interface information. It contains the large-scale interface data for proteins whose 3D-structures are known. As of November 2004, there were 10,583 (Geometric distance, 10,431 (ASA, and 11,010 (Voronoi diagram entries in the Protein Data Bank (PDB containing interfaces, according to the above three methods. In the case of the geometric distance method, there are 31,620 inter-chain domain

HIP2: An online database of human plasma proteins from healthy individuals

Directory of Open Access Journals (Sweden)

Shen Changyu

2008-04-01

Full Text Available Abstract Background With the introduction of increasingly powerful mass spectrometry (MS techniques for clinical research, several recent large-scale MS proteomics studies have sought to characterize the entire human plasma proteome with a general objective for identifying thousands of proteins leaked from tissues in the circulating blood. Understanding the basic constituents, diversity, and variability of the human plasma proteome is essential to the development of sensitive molecular diagnosis and treatment monitoring solutions for future biomedical applications. Biomedical researchers today, however, do not have an integrated online resource in which they can search for plasma proteins collected from different mass spectrometry platforms, experimental protocols, and search software for healthy individuals. The lack of such a resource for comparisons has made it difficult to interpret proteomics profile changes in patients' plasma and to design protein biomarker discovery experiments. Description To aid future protein biomarker studies of disease and health from human plasma, we developed an online database, HIP2 (Healthy Human Individual's Integrated Plasma Proteome. The current version contains 12,787 protein entries linked to 86,831 peptide entries identified using different MS platforms. Conclusion This web-based database will be useful to biomedical researchers involved in biomarker discovery research. This database has been developed to be the comprehensive collection of healthy human plasma proteins, and has protein data captured in a relational database schema built to contain mappings of supporting peptide evidence from several high-quality and high-throughput mass-spectrometry (MS experimental data sets. Users can search for plasma protein/peptide annotations, peptide/protein alignments, and experimental/sample conditions with options for filter-based retrieval to achieve greater analytical power for discovery and validation.

CPLA 1.0: an integrated database of protein lysine acetylation.

Science.gov (United States)

Liu, Zexian; Cao, Jun; Gao, Xinjiao; Zhou, Yanhong; Wen, Longping; Yang, Xiangjiao; Yao, Xuebiao; Ren, Jian; Xue, Yu

2011-01-01

As a reversible post-translational modification (PTM) discovered decades ago, protein lysine acetylation was known for its regulation of transcription through the modification of histones. Recent studies discovered that lysine acetylation targets broad substrates and especially plays an essential role in cellular metabolic regulation. Although acetylation is comparable with other major PTMs such as phosphorylation, an integrated resource still remains to be developed. In this work, we presented the compendium of protein lysine acetylation (CPLA) database for lysine acetylated substrates with their sites. From the scientific literature, we manually collected 7151 experimentally identified acetylation sites in 3311 targets. We statistically studied the regulatory roles of lysine acetylation by analyzing the Gene Ontology (GO) and InterPro annotations. Combined with protein-protein interaction information, we systematically discovered a potential human lysine acetylation network (HLAN) among histone acetyltransferases (HATs), substrates and histone deacetylases (HDACs). In particular, there are 1862 triplet relationships of HAT-substrate-HDAC retrieved from the HLAN, at least 13 of which were previously experimentally verified. The online services of CPLA database was implemented in PHP + MySQL + JavaScript, while the local packages were developed in JAVA 1.5 (J2SE 5.0). The CPLA database is freely available for all users at: http://cpla.biocuckoo.org.

Protein - TP Atlas | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data ...p_atlas_protein.zip File URL: ftp://ftp.biosciencedbc.jp/archive/tp_atlas/LATEST/...story of This Database Site Policy | Contact Us Protein - TP Atlas | LSDB Archive ...

An update of the DEF database of protein fold class predictions

DEFF Research Database (Denmark)

Reczko, Martin; Karras, Dimitris; Bohr, Henrik

1997-01-01

An update is given on the Database of Expected Fold classes (DEF) that contains a collection of fold-class predictions made from protein sequences and a mail server that provides new predictions for new sequences. To any given sequence one of 49 fold-classes is chosen to classify the structure re...... related to the sequence with high accuracy. The updated predictions system is developed using data from the new version of the 3D-ALI database of aligned protein structures and thus is giving more reliable and more detailed predictions than the previous DEF system.......An update is given on the Database of Expected Fold classes (DEF) that contains a collection of fold-class predictions made from protein sequences and a mail server that provides new predictions for new sequences. To any given sequence one of 49 fold-classes is chosen to classify the structure...

Exploring Protein Function Using the Saccharomyces Genome Database.

Science.gov (United States)

Wong, Edith D

2017-01-01

Elucidating the function of individual proteins will help to create a comprehensive picture of cell biology, as well as shed light on human disease mechanisms, possible treatments, and cures. Due to its compact genome, and extensive history of experimentation and annotation, the budding yeast Saccharomyces cerevisiae is an ideal model organism in which to determine protein function. This information can then be leveraged to infer functions of human homologs. Despite the large amount of research and biological data about S. cerevisiae, many proteins' functions remain unknown. Here, we explore ways to use the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org ) to predict the function of proteins and gain insight into their roles in various cellular processes.

iPfam: a database of protein family and domain interactions found in the Protein Data Bank.

Science.gov (United States)

Finn, Robert D; Miller, Benjamin L; Clements, Jody; Bateman, Alex

2014-01-01

The database iPfam, available at http://ipfam.org, catalogues Pfam domain interactions based on known 3D structures that are found in the Protein Data Bank, providing interaction data at the molecular level. Previously, the iPfam domain-domain interaction data was integrated within the Pfam database and website, but it has now been migrated to a separate database. This allows for independent development, improving data access and giving clearer separation between the protein family and interactions datasets. In addition to domain-domain interactions, iPfam has been expanded to include interaction data for domain bound small molecule ligands. Functional annotations are provided from source databases, supplemented by the incorporation of Wikipedia articles where available. iPfam (version 1.0) contains >9500 domain-domain and 15 500 domain-ligand interactions. The new website provides access to this data in a variety of ways, including interactive visualizations of the interaction data.

VaProS: a database-integration approach for protein/genome information retrieval

KAUST Repository

Gojobori, Takashi; Ikeo, Kazuho; Katayama, Yukie; Kawabata, Takeshi; Kinjo, Akira R.; Kinoshita, Kengo; Kwon, Yeondae; Migita, Ohsuke; Mizutani, Hisashi; Muraoka, Masafumi; Nagata, Koji; Omori, Satoshi; Sugawara, Hideaki; Yamada, Daichi; Yura, Kei

2016-01-01

Life science research now heavily relies on all sorts of databases for genome sequences, transcription, protein three-dimensional (3D) structures, protein–protein interactions, phenotypes and so forth. The knowledge accumulated by all the omics research is so vast that a computer-aided search of data is now a prerequisite for starting a new study. In addition, a combinatory search throughout these databases has a chance to extract new ideas and new hypotheses that can be examined by wet-lab experiments. By virtually integrating the related databases on the Internet, we have built a new web application that facilitates life science researchers for retrieving experts’ knowledge stored in the databases and for building a new hypothesis of the research target. This web application, named VaProS, puts stress on the interconnection between the functional information of genome sequences and protein 3D structures, such as structural effect of the gene mutation. In this manuscript, we present the notion of VaProS, the databases and tools that can be accessed without any knowledge of database locations and data formats, and the power of search exemplified in quest of the molecular mechanisms of lysosomal storage disease. VaProS can be freely accessed at http://p4d-info.nig.ac.jp/vapros/.

VaProS: a database-integration approach for protein/genome information retrieval

KAUST Repository

Gojobori, Takashi

2016-12-24

Life science research now heavily relies on all sorts of databases for genome sequences, transcription, protein three-dimensional (3D) structures, protein–protein interactions, phenotypes and so forth. The knowledge accumulated by all the omics research is so vast that a computer-aided search of data is now a prerequisite for starting a new study. In addition, a combinatory search throughout these databases has a chance to extract new ideas and new hypotheses that can be examined by wet-lab experiments. By virtually integrating the related databases on the Internet, we have built a new web application that facilitates life science researchers for retrieving experts’ knowledge stored in the databases and for building a new hypothesis of the research target. This web application, named VaProS, puts stress on the interconnection between the functional information of genome sequences and protein 3D structures, such as structural effect of the gene mutation. In this manuscript, we present the notion of VaProS, the databases and tools that can be accessed without any knowledge of database locations and data formats, and the power of search exemplified in quest of the molecular mechanisms of lysosomal storage disease. VaProS can be freely accessed at http://p4d-info.nig.ac.jp/vapros/.

muBLASTP: database-indexed protein sequence search on multicore CPUs.

Science.gov (United States)

Zhang, Jing; Misra, Sanchit; Wang, Hao; Feng, Wu-Chun

2016-11-04

The Basic Local Alignment Search Tool (BLAST) is a fundamental program in the life sciences that searches databases for sequences that are most similar to a query sequence. Currently, the BLAST algorithm utilizes a query-indexed approach. Although many approaches suggest that sequence search with a database index can achieve much higher throughput (e.g., BLAT, SSAHA, and CAFE), they cannot deliver the same level of sensitivity as the query-indexed BLAST, i.e., NCBI BLAST, or they can only support nucleotide sequence search, e.g., MegaBLAST. Due to different challenges and characteristics between query indexing and database indexing, the existing techniques for query-indexed search cannot be used into database indexed search. muBLASTP, a novel database-indexed BLAST for protein sequence search, delivers identical hits returned to NCBI BLAST. On Intel Haswell multicore CPUs, for a single query, the single-threaded muBLASTP achieves up to a 4.41-fold speedup for alignment stages, and up to a 1.75-fold end-to-end speedup over single-threaded NCBI BLAST. For a batch of queries, the multithreaded muBLASTP achieves up to a 5.7-fold speedups for alignment stages, and up to a 4.56-fold end-to-end speedup over multithreaded NCBI BLAST. With a newly designed index structure for protein database and associated optimizations in BLASTP algorithm, we re-factored BLASTP algorithm for modern multicore processors that achieves much higher throughput with acceptable memory footprint for the database index.

SCOWLP: a web-based database for detailed characterization and visualization of protein interfaces

Directory of Open Access Journals (Sweden)

Schroeder Michael

2006-03-01

Full Text Available Abstract Background Currently there is a strong need for methods that help to obtain an accurate description of protein interfaces in order to be able to understand the principles that govern molecular recognition and protein function. Many of the recent efforts to computationally identify and characterize protein networks extract protein interaction information at atomic resolution from the PDB. However, they pay none or little attention to small protein ligands and solvent. They are key components and mediators of protein interactions and fundamental for a complete description of protein interfaces. Interactome profiling requires the development of computational tools to extract and analyze protein-protein, protein-ligand and detailed solvent interaction information from the PDB in an automatic and comparative fashion. Adding this information to the existing one on protein-protein interactions will allow us to better understand protein interaction networks and protein function. Description SCOWLP (Structural Characterization Of Water, Ligands and Proteins is a user-friendly and publicly accessible web-based relational database for detailed characterization and visualization of the PDB protein interfaces. The SCOWLP database includes proteins, peptidic-ligands and interface water molecules as descriptors of protein interfaces. It contains currently 74,907 protein interfaces and 2,093,976 residue-residue interactions formed by 60,664 structural units (protein domains and peptidic-ligands and their interacting solvent. The SCOWLP web-server allows detailed structural analysis and comparisons of protein interfaces at atomic level by text query of PDB codes and/or by navigating a SCOP-based tree. It includes a visualization tool to interactively display the interfaces and label interacting residues and interface solvent by atomic physicochemical properties. SCOWLP is automatically updated with every SCOP release. Conclusion SCOWLP enriches

Protein Structural Change Data - PSCDB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us PSCDB Protein Structural Change Data Data detail Data name Protein Structural Change Data DO...History of This Database Site Policy | Contact Us Protein Structural Change Data - PSCDB | LSDB Archive ...

Development of human protein reference database as an initial platform for approaching systems biology in humans

DEFF Research Database (Denmark)

Peri, Suraj; Navarro, J Daniel; Amanchy, Ramars

2003-01-01

Human Protein Reference Database (HPRD) is an object database that integrates a wealth of information relevant to the function of human proteins in health and disease. Data pertaining to thousands of protein-protein interactions, posttranslational modifications, enzyme/substrate relationships...

Merging in-silico and in vitro salivary protein complex partners using the STRING database: A tutorial.

Science.gov (United States)

Crosara, Karla Tonelli Bicalho; Moffa, Eduardo Buozi; Xiao, Yizhi; Siqueira, Walter Luiz

2018-01-16

Protein-protein interaction is a common physiological mechanism for protection and actions of proteins in an organism. The identification and characterization of protein-protein interactions in different organisms is necessary to better understand their physiology and to determine their efficacy. In a previous in vitro study using mass spectrometry, we identified 43 proteins that interact with histatin 1. Six previously documented interactors were confirmed and 37 novel partners were identified. In this tutorial, we aimed to demonstrate the usefulness of the STRING database for studying protein-protein interactions. We used an in-silico approach along with the STRING database (http://string-db.org/) and successfully performed a fast simulation of a novel constructed histatin 1 protein-protein network, including both the previously known and the predicted interactors, along with our newly identified interactors. Our study highlights the advantages and importance of applying bioinformatics tools to merge in-silico tactics with experimental in vitro findings for rapid advancement of our knowledge about protein-protein interactions. Our findings also indicate that bioinformatics tools such as the STRING protein network database can help predict potential interactions between proteins and thus serve as a guide for future steps in our exploration of the Human Interactome. Our study highlights the usefulness of the STRING protein database for studying protein-protein interactions. The STRING database can collect and integrate data about known and predicted protein-protein associations from many organisms, including both direct (physical) and indirect (functional) interactions, in an easy-to-use interface. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrating protein structures and precomputed genealogies in the Magnum database: Examples with cellular retinoid binding proteins

Directory of Open Access Journals (Sweden)

Bradley Michael E

2006-02-01

Full Text Available Abstract Background When accurate models for the divergent evolution of protein sequences are integrated with complementary biological information, such as folded protein structures, analyses of the combined data often lead to new hypotheses about molecular physiology. This represents an excellent example of how bioinformatics can be used to guide experimental research. However, progress in this direction has been slowed by the lack of a publicly available resource suitable for general use. Results The precomputed Magnum database offers a solution to this problem for ca. 1,800 full-length protein families with at least one crystal structure. The Magnum deliverables include 1 multiple sequence alignments, 2 mapping of alignment sites to crystal structure sites, 3 phylogenetic trees, 4 inferred ancestral sequences at internal tree nodes, and 5 amino acid replacements along tree branches. Comprehensive evaluations revealed that the automated procedures used to construct Magnum produced accurate models of how proteins divergently evolve, or genealogies, and correctly integrated these with the structural data. To demonstrate Magnum's capabilities, we asked for amino acid replacements requiring three nucleotide substitutions, located at internal protein structure sites, and occurring on short phylogenetic tree branches. In the cellular retinoid binding protein family a site that potentially modulates ligand binding affinity was discovered. Recruitment of cellular retinol binding protein to function as a lens crystallin in the diurnal gecko afforded another opportunity to showcase the predictive value of a browsable database containing branch replacement patterns integrated with protein structures. Conclusion We integrated two areas of protein science, evolution and structure, on a large scale and created a precomputed database, known as Magnum, which is the first freely available resource of its kind. Magnum provides evolutionary and structural

The master two-dimensional gel database of human AMA cell proteins: towards linking protein and genome sequence and mapping information (update 1991)

DEFF Research Database (Denmark)

Celis, J E; Leffers, H; Rasmussen, H H

1991-01-01

autoantigens" and "cDNAs". For convenience we have included an alphabetical list of all known proteins recorded in this database. In the long run, the main goal of this database is to link protein and DNA sequencing and mapping information (Human Genome Program) and to provide an integrated picture......The master two-dimensional gel database of human AMA cells currently lists 3801 cellular and secreted proteins, of which 371 cellular polypeptides (306 IEF; 65 NEPHGE) were added to the master images during the last 10 months. These include: (i) very basic and acidic proteins that do not focus...

STITCH 2: an interaction network database for small molecules and proteins

DEFF Research Database (Denmark)

Kuhn, Michael; Szklarczyk, Damian; Franceschini, Andrea

2010-01-01

Over the last years, the publicly available knowledge on interactions between small molecules and proteins has been steadily increasing. To create a network of interactions, STITCH aims to integrate the data dispersed over the literature and various databases of biological pathways, drug......-target relationships and binding affinities. In STITCH 2, the number of relevant interactions is increased by incorporation of BindingDB, PharmGKB and the Comparative Toxicogenomics Database. The resulting network can be explored interactively or used as the basis for large-scale analyses. To facilitate links to other...... chemical databases, we adopt InChIKeys that allow identification of chemicals with a short, checksum-like string. STITCH 2.0 connects proteins from 630 organisms to over 74,000 different chemicals, including 2200 drugs. STITCH can be accessed at http://stitch.embl.de/....

Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database

KAUST Repository

Komatsu, Setsuko

2017-05-10

The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max ‘Enrei’). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. Biological significanceThe Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all

Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database.

Science.gov (United States)

Komatsu, Setsuko; Wang, Xin; Yin, Xiaojian; Nanjo, Yohei; Ohyanagi, Hajime; Sakata, Katsumi

2017-06-23

The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max 'Enrei'). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. The Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all predicted proteins from

Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database

KAUST Repository

Komatsu, Setsuko; Wang, Xin; Yin, Xiaojian; Nanjo, Yohei; Ohyanagi, Hajime; Sakata, Katsumi

2017-01-01

The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max ‘Enrei’). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. Biological significanceThe Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all

O-GLYCOBASE version 4.0: a revised database of O-glycosylated proteins

DEFF Research Database (Denmark)

Gupta, Ramneek; Birch, Hanne; Rapacki, Krzysztof

1999-01-01

O-GLYCBASE is a database of glycoproteins with O-linked glycosylation sites. Entries with at least one experimentally verified O-glycosylation site have been complied from protein sequence databases and literature. Each entry contains information about the glycan involved, the species, sequence, ...

Protein (Viridiplantae) - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available ase Description Download License Update History of This Database Site Policy | Contact Us Protein (Viridiplantae) - PGDBj - Ortholog DB | LSDB Archive ... ...List Contact us PGDBj - Ortholog DB Protein (Viridiplantae) Data detail Data name Protein (Viridiplantae) DO...switchLanguage; BLAST Search Image Search Home About Archive Update History Data

UNcleProt (Universal Nuclear Protein database of barley): The first nuclear protein database that distinguishes proteins from different phases of the cell cycle

Czech Academy of Sciences Publication Activity Database

Blavet, Nicolas; Uřinovská, J.; Jeřábková, Hana; Chamrád, I.; Vrána, Jan; Lenobel, R.; Beinhauer, D.; Šebela, M.; Doležel, Jaroslav; Petrovská, Beáta

2017-01-01

Roč. 8, č. 1 (2017), s. 70-80 ISSN 1949-1034 R&D Projects: GA ČR(CZ) GA14-28443S; GA MŠk(CZ) LO1204 Institutional support: RVO:61389030 Keywords : cicer-arietinum l. * rice oryza-sativa * chromatin-associated protein s * proteomic analysis * mitotic chromosomes * dehydration * localization * chickpea * network * phosphoproteome * barley * cell cycle * database * flow-cytometry * localization * mass spectrometry * nuclear proteome * nucleus Subject RIV: CE - Biochemistry OBOR OECD: Cell biology Impact factor: 2.387, year: 2016

BtoxDB: a comprehensive database of protein structural data on toxin-antitoxin systems.

Science.gov (United States)

Barbosa, Luiz Carlos Bertucci; Garrido, Saulo Santesso; Marchetto, Reinaldo

2015-03-01

Toxin-antitoxin (TA) systems are diverse and abundant genetic modules in prokaryotic cells that are typically formed by two genes encoding a stable toxin and a labile antitoxin. Because TA systems are able to repress growth or kill cells and are considered to be important actors in cell persistence (multidrug resistance without genetic change), these modules are considered potential targets for alternative drug design. In this scenario, structural information for the proteins in these systems is highly valuable. In this report, we describe the development of a web-based system, named BtoxDB, that stores all protein structural data on TA systems. The BtoxDB database was implemented as a MySQL relational database using PHP scripting language. Web interfaces were developed using HTML, CSS and JavaScript. The data were collected from the PDB, UniProt and Entrez databases. These data were appropriately filtered using specialized literature and our previous knowledge about toxin-antitoxin systems. The database provides three modules ("Search", "Browse" and "Statistics") that enable searches, acquisition of contents and access to statistical data. Direct links to matching external databases are also available. The compilation of all protein structural data on TA systems in one platform is highly useful for researchers interested in this content. BtoxDB is publicly available at http://www.gurupi.uft.edu.br/btoxdb. Copyright © 2015 Elsevier Ltd. All rights reserved.

MannDB – A microbial database of automated protein sequence analyses and evidence integration for protein characterization

Directory of Open Access Journals (Sweden)

Kuczmarski Thomas A

2006-10-01

Full Text Available Abstract Background MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the development of reagents for pathogen or protein toxin detection. Because a large number of open-source tools were needed, it was necessary to produce a software system to scale the computations for whole-proteome analysis. Thus, we built a fully automated system for executing software tools and for storage, integration, and display of automated protein sequence analysis and annotation data. Description MannDB is a relational database that organizes data resulting from fully automated, high-throughput protein-sequence analyses using open-source tools. Types of analyses provided include predictions of cleavage, chemical properties, classification, features, functional assignment, post-translational modifications, motifs, antigenicity, and secondary structure. Proteomes (lists of hypothetical and known proteins are downloaded and parsed from Genbank and then inserted into MannDB, and annotations from SwissProt are downloaded when identifiers are found in the Genbank entry or when identical sequences are identified. Currently 36 open-source tools are run against MannDB protein sequences either on local systems or by means of batch submission to external servers. In addition, BLAST against protein entries in MvirDB, our database of microbial virulence factors, is performed. A web client browser enables viewing of computational results and downloaded annotations, and a query tool enables structured and free-text search capabilities. When available, links to external databases, including MvirDB, are provided. MannDB contains whole-proteome analyses for at least one representative organism from each category of biological threat organism listed by APHIS, CDC, HHS, NIAID, USDA, USFDA, and WHO. Conclusion MannDB comprises a large number of genomes and comprehensive protein

CPAD, Curated Protein Aggregation Database: A Repository of Manually Curated Experimental Data on Protein and Peptide Aggregation.

Science.gov (United States)

Thangakani, A Mary; Nagarajan, R; Kumar, Sandeep; Sakthivel, R; Velmurugan, D; Gromiha, M Michael

2016-01-01

Accurate distinction between peptide sequences that can form amyloid-fibrils or amorphous β-aggregates, identification of potential aggregation prone regions in proteins, and prediction of change in aggregation rate of a protein upon mutation(s) are critical to research on protein misfolding diseases, such as Alzheimer's and Parkinson's, as well as biotechnological production of protein based therapeutics. We have developed a Curated Protein Aggregation Database (CPAD), which has collected results from experimental studies performed by scientific community aimed at understanding protein/peptide aggregation. CPAD contains more than 2300 experimentally observed aggregation rates upon mutations in known amyloidogenic proteins. Each entry includes numerical values for the following parameters: change in rate of aggregation as measured by fluorescence intensity or turbidity, name and source of the protein, Uniprot and Protein Data Bank codes, single point as well as multiple mutations, and literature citation. The data in CPAD has been supplemented with five different types of additional information: (i) Amyloid fibril forming hexa-peptides, (ii) Amorphous β-aggregating hexa-peptides, (iii) Amyloid fibril forming peptides of different lengths, (iv) Amyloid fibril forming hexa-peptides whose crystal structures are available in the Protein Data Bank (PDB) and (v) Experimentally validated aggregation prone regions found in amyloidogenic proteins. Furthermore, CPAD is linked to other related databases and resources, such as Uniprot, Protein Data Bank, PUBMED, GAP, TANGO, WALTZ etc. We have set up a web interface with different search and display options so that users have the ability to get the data in multiple ways. CPAD is freely available at http://www.iitm.ac.in/bioinfo/CPAD/. The potential applications of CPAD have also been discussed.

The Princeton Protein Orthology Database (P-POD): a comparative genomics analysis tool for biologists.

OpenAIRE

Sven Heinicke; Michael S Livstone; Charles Lu; Rose Oughtred; Fan Kang; Samuel V Angiuoli; Owen White; David Botstein; Kara Dolinski

2007-01-01

Many biological databases that provide comparative genomics information and tools are now available on the internet. While certainly quite useful, to our knowledge none of the existing databases combine results from multiple comparative genomics methods with manually curated information from the literature. Here we describe the Princeton Protein Orthology Database (P-POD, http://ortholog.princeton.edu), a user-friendly database system that allows users to find and visualize the phylogenetic r...

THPdb: Database of FDA-approved peptide and protein therapeutics.

Directory of Open Access Journals (Sweden)

Salman Sadullah Usmani

Full Text Available THPdb (http://crdd.osdd.net/raghava/thpdb/ is a manually curated repository of Food and Drug Administration (FDA approved therapeutic peptides and proteins. The information in THPdb has been compiled from 985 research publications, 70 patents and other resources like DrugBank. The current version of the database holds a total of 852 entries, providing comprehensive information on 239 US-FDA approved therapeutic peptides and proteins and their 380 drug variants. The information on each peptide and protein includes their sequences, chemical properties, composition, disease area, mode of activity, physical appearance, category or pharmacological class, pharmacodynamics, route of administration, toxicity, target of activity, etc. In addition, we have annotated the structure of most of the protein and peptides. A number of user-friendly tools have been integrated to facilitate easy browsing and data analysis. To assist scientific community, a web interface and mobile App have also been developed.

Identification and correction of abnormal, incomplete and mispredicted proteins in public databases

Directory of Open Access Journals (Sweden)

Bányai László

2008-08-01

Full Text Available Abstract Background Despite significant improvements in computational annotation of genomes, sequences of abnormal, incomplete or incorrectly predicted genes and proteins remain abundant in public databases. Since the majority of incomplete, abnormal or mispredicted entries are not annotated as such, these errors seriously affect the reliability of these databases. Here we describe the MisPred approach that may provide an efficient means for the quality control of databases. The current version of the MisPred approach uses five distinct routines for identifying abnormal, incomplete or mispredicted entries based on the principle that a sequence is likely to be incorrect if some of its features conflict with our current knowledge about protein-coding genes and proteins: (i conflict between the predicted subcellular localization of proteins and the absence of the corresponding sequence signals; (ii presence of extracellular and cytoplasmic domains and the absence of transmembrane segments; (iii co-occurrence of extracellular and nuclear domains; (iv violation of domain integrity; (v chimeras encoded by two or more genes located on different chromosomes. Results Analyses of predicted EnsEMBL protein sequences of nine deuterostome (Homo sapiens, Mus musculus, Rattus norvegicus, Monodelphis domestica, Gallus gallus, Xenopus tropicalis, Fugu rubripes, Danio rerio and Ciona intestinalis and two protostome species (Caenorhabditis elegans and Drosophila melanogaster have revealed that the absence of expected signal peptides and violation of domain integrity account for the majority of mispredictions. Analyses of sequences predicted by NCBI's GNOMON annotation pipeline show that the rates of mispredictions are comparable to those of EnsEMBL. Interestingly, even the manually curated UniProtKB/Swiss-Prot dataset is contaminated with mispredicted or abnormal proteins, although to a much lesser extent than UniProtKB/TrEMBL or the EnsEMBL or GNOMON

The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development.

Science.gov (United States)

Kunz, Meik; Liang, Chunguang; Nilla, Santosh; Cecil, Alexander; Dandekar, Thomas

2016-01-01

The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure-activity relationships.Database URL:http://drumpid.bioapps.biozentrum.uni-wuerzburg.de. © The Author(s) 2016. Published by Oxford University Press.

Database Description - RPSD | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available base Description General information of database Database name RPSD Alternative nam...e Rice Protein Structure Database DOI 10.18908/lsdba.nbdc00749-000 Creator Creator Name: Toshimasa Yamazaki ... Ibaraki 305-8602, Japan National Institute of Agrobiological Sciences Toshimasa Yamazaki E-mail : Databas...e classification Structure Databases - Protein structure Organism Taxonomy Name: Or...or name(s): Journal: External Links: Original website information Database maintenance site National Institu

Database Description - Trypanosomes Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Trypanosomes Database Database Description General information of database Database name Trypanosomes Database...stitute of Genetics Research Organization of Information and Systems Yata 1111, Mishima, Shizuoka 411-8540, JAPAN E mail: Database...y Name: Trypanosoma Taxonomy ID: 5690 Taxonomy Name: Homo sapiens Taxonomy ID: 9606 Database description The... Article title: Author name(s): Journal: External Links: Original website information Database maintenance s...DB (Protein Data Bank) KEGG PATHWAY Database DrugPort Entry list Available Query search Available Web servic

dbPAF: an integrative database of protein phosphorylation in animals and fungi.

Science.gov (United States)

Ullah, Shahid; Lin, Shaofeng; Xu, Yang; Deng, Wankun; Ma, Lili; Zhang, Ying; Liu, Zexian; Xue, Yu

2016-03-24

Protein phosphorylation is one of the most important post-translational modifications (PTMs) and regulates a broad spectrum of biological processes. Recent progresses in phosphoproteomic identifications have generated a flood of phosphorylation sites, while the integration of these sites is an urgent need. In this work, we developed a curated database of dbPAF, containing known phosphorylation sites in H. sapiens, M. musculus, R. norvegicus, D. melanogaster, C. elegans, S. pombe and S. cerevisiae. From the scientific literature and public databases, we totally collected and integrated 54,148 phosphoproteins with 483,001 phosphorylation sites. Multiple options were provided for accessing the data, while original references and other annotations were also present for each phosphoprotein. Based on the new data set, we computationally detected significantly over-represented sequence motifs around phosphorylation sites, predicted potential kinases that are responsible for the modification of collected phospho-sites, and evolutionarily analyzed phosphorylation conservation states across different species. Besides to be largely consistent with previous reports, our results also proposed new features of phospho-regulation. Taken together, our database can be useful for further analyses of protein phosphorylation in human and other model organisms. The dbPAF database was implemented in PHP + MySQL and freely available at http://dbpaf.biocuckoo.org.

Two-dimensional gel human protein databases offer a systematic approach to the study of cell proliferation and differentiation

DEFF Research Database (Denmark)

Celis, julio E.; Gesser, Borbala; Dejgaard, Kurt

1989-01-01

Human cellular protein databases have been established using computer-analyzed 2D gel electrophoresis. These databases, which include information on various properties of proteins, offer a global approach to the study of regulation of cell proliferation and differentiation. Furthermore, thanks...

Two dimensional gel human protein databases offer a systematic approach to the study of cell proliferation and differentiation

DEFF Research Database (Denmark)

Celis, J E; Gesser, B; Dejgaard, K

1989-01-01

Human cellular protein databases have been established using computer-analyzed 2D gel electrophoresis. These databases, which include information on various properties of proteins, offer a global approach to the study of regulation of cell proliferation and differentiation. Furthermore, thanks to...

Ebolavirus Database: Gene and Protein Information Resource for Ebolaviruses

Directory of Open Access Journals (Sweden)

Rayapadi G. Swetha

2016-01-01

Full Text Available Ebola Virus Disease (EVD is a life-threatening haemorrhagic fever in humans. Even though there are many reports on EVD, the protein precursor functions and virulent factors of ebolaviruses remain poorly understood. Comparative analyses of Ebolavirus genomes will help in the identification of these important features. This prompted us to develop the Ebolavirus Database (EDB and we have provided links to various tools that will aid researchers to locate important regions in both the genomes and proteomes of Ebolavirus. The genomic analyses of ebolaviruses will provide important clues for locating the essential and core functional genes. The aim of EDB is to act as an integrated resource for ebolaviruses and we strongly believe that the database will be a useful tool for clinicians, microbiologists, health care workers, and bioscience researchers.

Database Description - eSOL | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available base Description General information of database Database name eSOL Alternative nam...eator Affiliation: The Research and Development of Biological Databases Project, National Institute of Genet...nology 4259 Nagatsuta-cho, Midori-ku, Yokohama, Kanagawa 226-8501 Japan Email: Tel.: +81-45-924-5785 Database... classification Protein sequence databases - Protein properties Organism Taxonomy Name: Escherichia coli Taxonomy ID: 562 Database...i U S A. 2009 Mar 17;106(11):4201-6. External Links: Original website information Database maintenance site

Neutron cross-sections database for amino acids and proteins analysis

Energy Technology Data Exchange (ETDEWEB)

Voi, Dante L.; Ferreira, Francisco de O.; Nunes, Rogerio Chaffin, E-mail: dante@ien.gov.br, E-mail: fferreira@ien.gov.br, E-mail: Chaffin@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Rocha, Helio F. da, E-mail: hrocha@gbl.com.br [Universidade Federal do Rio de Janeiro (IPPMG/UFRJ), Rio de Janeiro, RJ (Brazil). Instituto de Pediatria

2015-07-01

Biological materials may be studied using neutrons as an unconventional tool of analysis. Dynamics and structures data can be obtained for amino acids, protein and others cellular components by neutron cross sections determinations especially for applications in nuclear purity and conformation analysis. The instrument used for this is the crystal spectrometer of the Instituto de Engenharia Nuclear (IEN-CNEN-RJ), the only one in Latin America that uses neutrons for this type of analyzes and it is installed in one of the reactor Argonauta irradiation channels. The experimentally values obtained are compared with calculated values using literature data with a rigorous analysis of the chemical composition, conformation and molecular structure analysis of the materials. A neutron cross-section database was constructed to assist in determining molecular dynamic, structure and formulae of biological materials. The database contains neutron cross-sections values of all amino acids, chemical elements, molecular groups, auxiliary radicals, as well as values of constants and parameters necessary for the analysis. An unprecedented analytical procedure was developed using the neutron cross section parceling and grouping method for data manipulation. This database is a result of measurements obtained from twenty amino acids that were provided by different manufactories and are used in oral administration in hospital individuals for nutritional applications. It was also constructed a small data file of compounds with different molecular groups including carbon, nitrogen, sulfur and oxygen, all linked to hydrogen atoms. A review of global and national scene in the acquisition of neutron cross sections data, the formation of libraries and the application of neutrons for analyzing biological materials is presented. This database has further application in protein analysis and the neutron cross-section from the insulin was estimated. (author)

Neutron cross-sections database for amino acids and proteins analysis

International Nuclear Information System (INIS)

Voi, Dante L.; Ferreira, Francisco de O.; Nunes, Rogerio Chaffin; Rocha, Helio F. da

2015-01-01

Biological materials may be studied using neutrons as an unconventional tool of analysis. Dynamics and structures data can be obtained for amino acids, protein and others cellular components by neutron cross sections determinations especially for applications in nuclear purity and conformation analysis. The instrument used for this is the crystal spectrometer of the Instituto de Engenharia Nuclear (IEN-CNEN-RJ), the only one in Latin America that uses neutrons for this type of analyzes and it is installed in one of the reactor Argonauta irradiation channels. The experimentally values obtained are compared with calculated values using literature data with a rigorous analysis of the chemical composition, conformation and molecular structure analysis of the materials. A neutron cross-section database was constructed to assist in determining molecular dynamic, structure and formulae of biological materials. The database contains neutron cross-sections values of all amino acids, chemical elements, molecular groups, auxiliary radicals, as well as values of constants and parameters necessary for the analysis. An unprecedented analytical procedure was developed using the neutron cross section parceling and grouping method for data manipulation. This database is a result of measurements obtained from twenty amino acids that were provided by different manufactories and are used in oral administration in hospital individuals for nutritional applications. It was also constructed a small data file of compounds with different molecular groups including carbon, nitrogen, sulfur and oxygen, all linked to hydrogen atoms. A review of global and national scene in the acquisition of neutron cross sections data, the formation of libraries and the application of neutrons for analyzing biological materials is presented. This database has further application in protein analysis and the neutron cross-section from the insulin was estimated. (author)

Protein structure determination by exhaustive search of Protein Data Bank derived databases.

Science.gov (United States)

Stokes-Rees, Ian; Sliz, Piotr

2010-12-14

Parallel sequence and structure alignment tools have become ubiquitous and invaluable at all levels in the study of biological systems. We demonstrate the application and utility of this same parallel search paradigm to the process of protein structure determination, benefitting from the large and growing corpus of known structures. Such searches were previously computationally intractable. Through the method of Wide Search Molecular Replacement, developed here, they can be completed in a few hours with the aide of national-scale federated cyberinfrastructure. By dramatically expanding the range of models considered for structure determination, we show that small (less than 12% structural coverage) and low sequence identity (less than 20% identity) template structures can be identified through multidimensional template scoring metrics and used for structure determination. Many new macromolecular complexes can benefit significantly from such a technique due to the lack of known homologous protein folds or sequences. We demonstrate the effectiveness of the method by determining the structure of a full-length p97 homologue from Trichoplusia ni. Example cases with the MHC/T-cell receptor complex and the EmoB protein provide systematic estimates of minimum sequence identity, structure coverage, and structural similarity required for this method to succeed. We describe how this structure-search approach and other novel computationally intensive workflows are made tractable through integration with the US national computational cyberinfrastructure, allowing, for example, rapid processing of the entire Structural Classification of Proteins protein fragment database.

ASAView: Database and tool for solvent accessibility representation in proteins

Directory of Open Access Journals (Sweden)

Fawareh Hamed

2004-05-01

Full Text Available Abstract Background Accessible surface area (ASA or solvent accessibility of amino acids in a protein has important implications. Knowledge of surface residues helps in locating potential candidates of active sites. Therefore, a method to quickly see the surface residues in a two dimensional model would help to immediately understand the population of amino acid residues on the surface and in the inner core of the proteins. Results ASAView is an algorithm, an application and a database of schematic representations of solvent accessibility of amino acid residues within proteins. A characteristic two-dimensional spiral plot of solvent accessibility provides a convenient graphical view of residues in terms of their exposed surface areas. In addition, sequential plots in the form of bar charts are also provided. Online plots of the proteins included in the entire Protein Data Bank (PDB, are provided for the entire protein as well as their chains separately. Conclusions These graphical plots of solvent accessibility are likely to provide a quick view of the overall topological distribution of residues in proteins. Chain-wise computation of solvent accessibility is also provided.

Protein backbone angle restraints from searching a database for chemical shift and sequence homology

Energy Technology Data Exchange (ETDEWEB)

Cornilescu, Gabriel; Delaglio, Frank; Bax, Ad [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)

1999-03-15

Chemical shifts of backbone atoms in proteins are exquisitely sensitive to local conformation, and homologous proteins show quite similar patterns of secondary chemical shifts. The inverse of this relation is used to search a database for triplets of adjacent residues with secondary chemical shifts and sequence similarity which provide the best match to the query triplet of interest. The database contains 13C{alpha}, 13C{beta}, 13C', 1H{alpha} and 15N chemical shifts for 20 proteins for which a high resolution X-ray structure is available. The computer program TALOS was developed to search this database for strings of residues with chemical shift and residue type homology. The relative importance of the weighting factors attached to the secondary chemical shifts of the five types of resonances relative to that of sequence similarity was optimized empirically. TALOS yields the 10 triplets which have the closest similarity in secondary chemical shift and amino acid sequence to those of the query sequence. If the central residues in these 10 triplets exhibit similar {phi} and {psi} backbone angles, their averages can reliably be used as angular restraints for the protein whose structure is being studied. Tests carried out for proteins of known structure indicate that the root-mean-square difference (rmsd) between the output of TALOS and the X-ray derived backbone angles is about 15 deg. Approximately 3% of the predictions made by TALOS are found to be in error.

DSFL database: A hub of target proteins of Leishmania sp. to combat leishmaniasis

Directory of Open Access Journals (Sweden)

Ameer Khusro

2017-07-01

Full Text Available Leishmaniasis is a vector-borne chronic infectious tropical dermal disease caused by the protozoa parasite of the genus Leishmania that causes high mortality globally. Among three different clinical forms of leishmaniasis, visceral leishmaniasis (VL or kala-azar is a systemic public health disease with high morbidity and mortality in developing countries, caused by Leishmania donovani, Leishmania infantum or Leishmania chagasi. Unfortunately, there is no vaccine available till date for the treatment of leishmaniasis. On the other hand, the therapeutics approved to treat this fatal disease is expensive, toxic, and associated with serious side effects. Furthermore, the emergence of drug-resistant Leishmania parasites in most endemic countries due to the incessant utilization of existing drugs is a major concern at present. Drug Search for Leishmaniasis (DSFL is a unique database that involves 50 crystallized target proteins of varied Leishmania sp. in order to develop new drugs in future by interacting several antiparasitic compounds or molecules with specific protein through computational tools. The structure of target protein from different Leishmania sp. is available in this database. In this review, we spotlighted not only the current global status of leishmaniasis in brief but also detailed information about target proteins of various Leishmania sp. available in DSFL. DSFL has created a new expectation for mankind in order to combat leishmaniasis by targeting parasitic proteins and commence a new era to get rid of drug resistance parasites. The database will substantiate to be a worthwhile project for further development of new, non-toxic, and cost-effective antileishmanial drugs as targeted therapies using in vitro/in vivo assays.

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

Directory of Open Access Journals (Sweden)

Ma'ayan Avi

2007-10-01

Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

PROCARB: A Database of Known and Modelled Carbohydrate-Binding Protein Structures with Sequence-Based Prediction Tools

Directory of Open Access Journals (Sweden)

Adeel Malik

2010-01-01

Full Text Available Understanding of the three-dimensional structures of proteins that interact with carbohydrates covalently (glycoproteins as well as noncovalently (protein-carbohydrate complexes is essential to many biological processes and plays a significant role in normal and disease-associated functions. It is important to have a central repository of knowledge available about these protein-carbohydrate complexes as well as preprocessed data of predicted structures. This can be significantly enhanced by tools de novo which can predict carbohydrate-binding sites for proteins in the absence of structure of experimentally known binding site. PROCARB is an open-access database comprising three independently working components, namely, (i Core PROCARB module, consisting of three-dimensional structures of protein-carbohydrate complexes taken from Protein Data Bank (PDB, (ii Homology Models module, consisting of manually developed three-dimensional models of N-linked and O-linked glycoproteins of unknown three-dimensional structure, and (iii CBS-Pred prediction module, consisting of web servers to predict carbohydrate-binding sites using single sequence or server-generated PSSM. Several precomputed structural and functional properties of complexes are also included in the database for quick analysis. In particular, information about function, secondary structure, solvent accessibility, hydrogen bonds and literature reference, and so forth, is included. In addition, each protein in the database is mapped to Uniprot, Pfam, PDB, and so forth.

UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

Science.gov (United States)

Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

2016-01-04

The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Conformational dynamics data bank: a database for conformational dynamics of proteins and supramolecular protein assemblies.

Science.gov (United States)

Kim, Do-Nyun; Altschuler, Josiah; Strong, Campbell; McGill, Gaël; Bathe, Mark

2011-01-01

The conformational dynamics data bank (CDDB, http://www.cdyn.org) is a database that aims to provide comprehensive results on the conformational dynamics of high molecular weight proteins and protein assemblies. Analysis is performed using a recently introduced coarse-grained computational approach that is applied to the majority of structures present in the electron microscopy data bank (EMDB). Results include equilibrium thermal fluctuations and elastic strain energy distributions that identify rigid versus flexible protein domains generally, as well as those associated with specific functional transitions, and correlations in molecular motions that identify molecular regions that are highly coupled dynamically, with implications for allosteric mechanisms. A practical web-based search interface enables users to easily collect conformational dynamics data in various formats. The data bank is maintained and updated automatically to include conformational dynamics results for new structural entries as they become available in the EMDB. The CDDB complements static structural information to facilitate the investigation and interpretation of the biological function of proteins and protein assemblies essential to cell function.

Searching the protein structure database for ligand-binding site similarities using CPASS v.2

Directory of Open Access Journals (Sweden)

Caprez Adam

2011-01-01

Full Text Available Abstract Background A recent analysis of protein sequences deposited in the NCBI RefSeq database indicates that ~8.5 million protein sequences are encoded in prokaryotic and eukaryotic genomes, where ~30% are explicitly annotated as "hypothetical" or "uncharacterized" protein. Our Comparison of Protein Active-Site Structures (CPASS v.2 database and software compares the sequence and structural characteristics of experimentally determined ligand binding sites to infer a functional relationship in the absence of global sequence or structure similarity. CPASS is an important component of our Functional Annotation Screening Technology by NMR (FAST-NMR protocol and has been successfully applied to aid the annotation of a number of proteins of unknown function. Findings We report a major upgrade to our CPASS software and database that significantly improves its broad utility. CPASS v.2 is designed with a layered architecture to increase flexibility and portability that also enables job distribution over the Open Science Grid (OSG to increase speed. Similarly, the CPASS interface was enhanced to provide more user flexibility in submitting a CPASS query. CPASS v.2 now allows for both automatic and manual definition of ligand-binding sites and permits pair-wise, one versus all, one versus list, or list versus list comparisons. Solvent accessible surface area, ligand root-mean square difference, and Cβ distances have been incorporated into the CPASS similarity function to improve the quality of the results. The CPASS database has also been updated. Conclusions CPASS v.2 is more than an order of magnitude faster than the original implementation, and allows for multiple simultaneous job submissions. Similarly, the CPASS database of ligand-defined binding sites has increased in size by ~ 38%, dramatically increasing the likelihood of a positive search result. The modification to the CPASS similarity function is effective in reducing CPASS similarity scores

Viral Genome DataBase: storing and analyzing genes and proteins from complete viral genomes.

Science.gov (United States)

Hiscock, D; Upton, C

2000-05-01

The Viral Genome DataBase (VGDB) contains detailed information of the genes and predicted protein sequences from 15 completely sequenced genomes of large (&100 kb) viruses (2847 genes). The data that is stored includes DNA sequence, protein sequence, GenBank and user-entered notes, molecular weight (MW), isoelectric point (pI), amino acid content, A + T%, nucleotide frequency, dinucleotide frequency and codon use. The VGDB is a mySQL database with a user-friendly JAVA GUI. Results of queries can be easily sorted by any of the individual parameters. The software and additional figures and information are available at http://athena.bioc.uvic.ca/genomes/index.html .

AT_CHLORO, a comprehensive chloroplast proteome database with subplastidial localization and curated information on envelope proteins.

Science.gov (United States)

Ferro, Myriam; Brugière, Sabine; Salvi, Daniel; Seigneurin-Berny, Daphné; Court, Magali; Moyet, Lucas; Ramus, Claire; Miras, Stéphane; Mellal, Mourad; Le Gall, Sophie; Kieffer-Jaquinod, Sylvie; Bruley, Christophe; Garin, Jérôme; Joyard, Jacques; Masselon, Christophe; Rolland, Norbert

2010-06-01

Recent advances in the proteomics field have allowed a series of high throughput experiments to be conducted on chloroplast samples, and the data are available in several public databases. However, the accurate localization of many chloroplast proteins often remains hypothetical. This is especially true for envelope proteins. We went a step further into the knowledge of the chloroplast proteome by focusing, in the same set of experiments, on the localization of proteins in the stroma, the thylakoids, and envelope membranes. LC-MS/MS-based analyses first allowed building the AT_CHLORO database (http://www.grenoble.prabi.fr/protehome/grenoble-plant-proteomics/), a comprehensive repertoire of the 1323 proteins, identified by 10,654 unique peptide sequences, present in highly purified chloroplasts and their subfractions prepared from Arabidopsis thaliana leaves. This database also provides extensive proteomics information (peptide sequences and molecular weight, chromatographic retention times, MS/MS spectra, and spectral count) for a unique chloroplast protein accurate mass and time tag database gathering identified peptides with their respective and precise analytical coordinates, molecular weight, and retention time. We assessed the partitioning of each protein in the three chloroplast compartments by using a semiquantitative proteomics approach (spectral count). These data together with an in-depth investigation of the literature were compiled to provide accurate subplastidial localization of previously known and newly identified proteins. A unique knowledge base containing extensive information on the proteins identified in envelope fractions was thus obtained, allowing new insights into this membrane system to be revealed. Altogether, the data we obtained provide unexpected information about plastidial or subplastidial localization of some proteins that were not suspected to be associated to this membrane system. The spectral counting-based strategy was further

ZifBASE: a database of zinc finger proteins and associated resources

Directory of Open Access Journals (Sweden)

Punetha Ankita

2009-09-01

databases like UniprotKB, PDB, ModBase and Protein Model Portal and PubMed for making it more informative. Conclusion A database is established to maintain the information of the sequence features, including the class, framework, number of fingers, residues, position, recognition site and physio-chemical properties (molecular weight, isoelectric point of both natural and engineered zinc finger proteins and dissociation constant of few. ZifBASE can provide more effective and efficient way of accessing the zinc finger protein sequences and their target binding sites with the links to their three-dimensional structures. All the data and functions are available at the advanced web-based search interface http://web.iitd.ac.in/~sundar/zifbase.

Kin-Driver: a database of driver mutations in protein kinases.

Science.gov (United States)

Simonetti, Franco L; Tornador, Cristian; Nabau-Moretó, Nuria; Molina-Vila, Miguel A; Marino-Buslje, Cristina

2014-01-01

Somatic mutations in protein kinases (PKs) are frequent driver events in many human tumors, while germ-line mutations are associated with hereditary diseases. Here we present Kin-driver, the first database that compiles driver mutations in PKs with experimental evidence demonstrating their functional role. Kin-driver is a manual expert-curated database that pays special attention to activating mutations (AMs) and can serve as a validation set to develop new generation tools focused on the prediction of gain-of-function driver mutations. It also offers an easy and intuitive environment to facilitate the visualization and analysis of mutations in PKs. Because all mutations are mapped onto a multiple sequence alignment, analogue positions between kinases can be identified and tentative new mutations can be proposed for studying by transferring annotation. Finally, our database can also be of use to clinical and translational laboratories, helping them to identify uncommon AMs that can correlate with response to new antitumor drugs. The website was developed using PHP and JavaScript, which are supported by all major browsers; the database was built using MySQL server. Kin-driver is available at: http://kin-driver.leloir.org.ar/ © The Author(s) 2014. Published by Oxford University Press.

AllergenOnline: A peer-reviewed, curated allergen database to assess novel food proteins for potential cross-reactivity.

Science.gov (United States)

Goodman, Richard E; Ebisawa, Motohiro; Ferreira, Fatima; Sampson, Hugh A; van Ree, Ronald; Vieths, Stefan; Baumert, Joseph L; Bohle, Barbara; Lalithambika, Sreedevi; Wise, John; Taylor, Steve L

2016-05-01

Increasingly regulators are demanding evaluation of potential allergenicity of foods prior to marketing. Primary risks are the transfer of allergens or potentially cross-reactive proteins into new foods. AllergenOnline was developed in 2005 as a peer-reviewed bioinformatics platform to evaluate risks of new dietary proteins in genetically modified organisms (GMO) and novel foods. The process used to identify suspected allergens and evaluate the evidence of allergenicity was refined between 2010 and 2015. Candidate proteins are identified from the NCBI database using keyword searches, the WHO/IUIS nomenclature database and peer reviewed publications. Criteria to classify proteins as allergens are described. Characteristics of the protein, the source and human subjects, test methods and results are evaluated by our expert panel and archived. Food, inhalant, salivary, venom, and contact allergens are included. Users access allergen sequences through links to the NCBI database and relevant references are listed online. Version 16 includes 1956 sequences from 778 taxonomic-protein groups that are accepted with evidence of allergic serum IgE-binding and/or biological activity. AllergenOnline provides a useful peer-reviewed tool for identifying the primary potential risks of allergy for GMOs and novel foods based on criteria described by the Codex Alimentarius Commission (2003). © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The human interactome knowledge base (hint-kb): An integrative human protein interaction database enriched with predicted protein–protein interaction scores using a novel hybrid technique

KAUST Repository

Theofilatos, Konstantinos A.

2013-07-12

Proteins are the functional components of many cellular processes and the identification of their physical protein–protein interactions (PPIs) is an area of mature academic research. Various databases have been developed containing information about experimentally and computationally detected human PPIs as well as their corresponding annotation data. However, these databases contain many false positive interactions, are partial and only a few of them incorporate data from various sources. To overcome these limitations, we have developed HINT-KB (http://biotools.ceid.upatras.gr/hint-kb/), a knowledge base that integrates data from various sources, provides a user-friendly interface for their retrieval, cal-culatesasetoffeaturesofinterest and computesaconfidence score for every candidate protein interaction. This confidence score is essential for filtering the false positive interactions which are present in existing databases, predicting new protein interactions and measuring the frequency of each true protein interaction. For this reason, a novel machine learning hybrid methodology, called (Evolutionary Kalman Mathematical Modelling—EvoKalMaModel), was used to achieve an accurate and interpretable scoring methodology. The experimental results indicated that the proposed scoring scheme outperforms existing computational methods for the prediction of PPIs.

Database Description - ConfC | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available abase Description General information of database Database name ConfC Alternative name Database...amotsu Noguchi Tel: 042-495-8736 E-mail: Database classification Structure Database...s - Protein structure Structure Databases - Small molecules Structure Databases - Nucleic acid structure Database... services - Need for user registration - About This Database Database Description Download License Update History of This Database... Site Policy | Contact Us Database Description - ConfC | LSDB Archive ...

Database Description - TMFunction | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available sidue (or mutant) in a protein. The experimental data are collected from the literature both by searching th...the sequence database, UniProt, structural database, PDB, and literature database

A curated gluten protein sequence database to support development of proteomics methods for determination of gluten in gluten-free foods.

Science.gov (United States)

Bromilow, Sophie; Gethings, Lee A; Buckley, Mike; Bromley, Mike; Shewry, Peter R; Langridge, James I; Clare Mills, E N

2017-06-23

The unique physiochemical properties of wheat gluten enable a diverse range of food products to be manufactured. However, gluten triggers coeliac disease, a condition which is treated using a gluten-free diet. Analytical methods are required to confirm if foods are gluten-free, but current immunoassay-based methods can unreliable and proteomic methods offer an alternative but require comprehensive and well annotated sequence databases which are lacking for gluten. A manually a curated database (GluPro V1.0) of gluten proteins, comprising 630 discrete unique full length protein sequences has been compiled. It is representative of the different types of gliadin and glutenin components found in gluten. An in silico comparison of their coeliac toxicity was undertaken by analysing the distribution of coeliac toxic motifs. This demonstrated that whilst the α-gliadin proteins contained more toxic motifs, these were distributed across all gluten protein sub-types. Comparison of annotations observed using a discovery proteomics dataset acquired using ion mobility MS/MS showed that more reliable identifications were obtained using the GluPro V1.0 database compared to the complete reviewed Viridiplantae database. This highlights the value of a curated sequence database specifically designed to support the proteomic workflows and the development of methods to detect and quantify gluten. We have constructed the first manually curated open-source wheat gluten protein sequence database (GluPro V1.0) in a FASTA format to support the application of proteomic methods for gluten protein detection and quantification. We have also analysed the manually verified sequences to give the first comprehensive overview of the distribution of sequences able to elicit a reaction in coeliac disease, the prevalent form of gluten intolerance. Provision of this database will improve the reliability of gluten protein identification by proteomic analysis, and aid the development of targeted mass

Database Description - PSCDB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available abase Description General information of database Database name PSCDB Alternative n...rial Science and Technology (AIST) Takayuki Amemiya E-mail: Database classification Structure Databases - Protein structure Database...554-D558. External Links: Original website information Database maintenance site Graduate School of Informat...available URL of Web services - Need for user registration Not available About This Database Database Descri...ption Download License Update History of This Database Site Policy | Contact Us Database Description - PSCDB | LSDB Archive ...

Database Description - SAHG | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available base Description General information of database Database name SAHG Alternative nam...h: Contact address Chie Motono Tel : +81-3-3599-8067 E-mail : Database classification Structure Databases - ...e databases - Protein properties Organism Taxonomy Name: Homo sapiens Taxonomy ID: 9606 Database description... Links: Original website information Database maintenance site The Molecular Profiling Research Center for D...stration Not available About This Database Database Description Download License Update History of This Database Site Policy | Contact Us Database Description - SAHG | LSDB Archive ...

High Performance Protein Sequence Database Scanning on the Cell Broadband Engine

Directory of Open Access Journals (Sweden)

Adrianto Wirawan

2009-01-01

Full Text Available The enormous growth of biological sequence databases has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing rapidly as well. The recent emergence of low cost parallel multicore accelerator technologies has made it possible to reduce execution times of many bioinformatics applications. In this paper, we demonstrate how the Cell Broadband Engine can be used as a computational platform to accelerate two approaches for protein sequence database scanning: exhaustive and heuristic. We present efficient parallelization techniques for two representative algorithms: the dynamic programming based Smith–Waterman algorithm and the popular BLASTP heuristic. Their implementation on a Playstation®3 leads to significant runtime savings compared to corresponding sequential implementations.

The human interactome knowledge base (hint-kb): An integrative human protein interaction database enriched with predicted protein–protein interaction scores using a novel hybrid technique

KAUST Repository

Theofilatos, Konstantinos A.; Dimitrakopoulos, Christos M.; Likothanassis, Spiridon D.; Kleftogiannis, Dimitrios A.; Moschopoulos, Charalampos N.; Alexakos, Christos; Papadimitriou, Stergios; Mavroudi, Seferina P.

2013-01-01

Proteins are the functional components of many cellular processes and the identification of their physical protein–protein interactions (PPIs) is an area of mature academic research. Various databases have been developed containing information about

PATtyFams: Protein families for the microbial genomes in the PATRIC database

Directory of Open Access Journals (Sweden)

James J Davis

2016-02-01

Full Text Available The ability to build accurate protein families is a fundamental operation in bioinformatics that influences comparative analyses, genome annotation and metabolic modeling. For several years we have been maintaining protein families for all microbial genomes in the PATRIC database (Pathosystems Resource Integration Center, patricbrc.org in order to drive many of the comparative analysis tools that are available through the PATRIC website. However, due to the burgeoning number of genomes, traditional approaches for generating protein families are becoming prohibitive. In this report, we describe a new approach for generating protein families, which we call PATtyFams. This method uses the k-mer-based function assignments available through RAST (Rapid Annotation using Subsystem Technology to rapidly guide family formation, and then differentiates the function-based groups into families using a Markov Cluster algorithm (MCL. This new approach for generating protein families is rapid, scalable and has properties that are consistent with alignment-based methods.

The human keratinocyte two-dimensional protein database (update 1994): towards an integrated approach to the study of cell proliferation, differentiation and skin diseases

DEFF Research Database (Denmark)

Celis, J E; Rasmussen, H H; Olsen, E

1994-01-01

The master two-dimensional (2-D) gel database of human keratinocytes currently lists 3087 cellular proteins (2168 isoelectric focusing, IEF; and 919 none-quilibrium pH gradient electrophoresis, NEPHGE), many of which correspond to posttranslational modifications, 890 polypeptides have been...... in the database. We also report a database of proteins recovered from the medium of noncultured, unfractionated keratinocytes. This database lists 398 polypeptides (309 IEF; 89 NEPHGE) of which 76 have been identified. The aim of the comprehensive databases is to gather, through a systematic study...

Yeast Interacting Proteins Database: YNR006W, YHL002W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ling Golgi proteins, forming lumenal membranes and sorting ubiquitinated proteins destined for degradation; ..., as well as for recycling of Golgi proteins and formation of lumenal membranes Rows with this prey as prey ...1p; required for recycling Golgi proteins, forming lumenal membranes and sorting ubiquitinated proteins dest...degradation, as well as for recycling of Golgi proteins and formation of lumenal membranes

The CATH database

Directory of Open Access Journals (Sweden)

Knudsen Michael

2010-02-01

Full Text Available Abstract The CATH database provides hierarchical classification of protein domains based on their folding patterns. Domains are obtained from protein structures deposited in the Protein Data Bank and both domain identification and subsequent classification use manual as well as automated procedures. The accompanying website http://www.cathdb.info provides an easy-to-use entry to the classification, allowing for both browsing and downloading of data. Here, we give a brief review of the database, its corresponding website and some related tools.

The role of the UPS in cystic fibrosis

Directory of Open Access Journals (Sweden)

Cyr Douglas M

2007-11-01

Full Text Available Abstract CF is an inherited autosomal recessive disease whose lethality arises from malfunction of CFTR, a single chloride (Cl- ion channel protein. CF patients harbor mutations in the CFTR gene that lead to misfolding of the resulting CFTR protein, rendering it inactive and mislocalized. Hundreds of CF-related mutations have been identified, many of which abrogate CFTR folding in the endoplasmic reticulum (ER. More than 70% of patients harbor the ΔF508 CFTR mutation that causes misfolding of the CFTR proteins. Consequently, mutant CFTR is unable to reach the apical plasma membrane of epithelial cells that line the lungs and gut, and is instead targeted for degradation by the UPS. Proteins located in both the cytoplasm and ER membrane are believed to identify misfolded CFTR for UPS-mediated degradation. The aberrantly folded CFTR protein then undergoes polyubiquitylation, carried out by an E1-E2-E3 ubiquitin ligase system, leading to degradation by the 26S proteasome. This ubiquitin-dependent loss of misfolded CFTR protein can be inhibited by the application of ‘corrector’ drugs that aid CFTR folding, shielding it from the UPS machinery. Corrector molecules elevate cellular CFTR protein levels by protecting the protein from degradation and aiding folding, promoting its maturation and localization to the apical plasma membrane. Combinatory application of corrector drugs with activator molecules that enhance CFTR Cl- ion channel activity offers significant potential for treatment of CF patients. Publication history: Republished from Current BioData's Targeted Proteins database (TPdb; http://www.targetedproteinsdb.com.

Yeast Interacting Proteins Database: YHL002W, YNR006W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ycling of Golgi proteins and formation of lumenal membranes Rows with this bait as bait (1) Rows with this b...required for recycling Golgi proteins, forming lumenal membranes and sorting ubiquitinated proteins destined...on, as well as for recycling of Golgi proteins and formation of lumenal membranes...ith Hse1p; required for recycling Golgi proteins, forming lumenal membranes and sorting ubiquitinated protei

Yeast Interacting Proteins Database: YOR047C, YKL038W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available racts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a...Bait description Protein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose senso...rs Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regulator of the tra

Yeast Interacting Proteins Database: YFR049W, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regulator... (0) YOR047C STD1 Protein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sens...ors Snf3p and Rgt2p, and TATA-binding protein Spt15p; ac

RADARS, a bioinformatics solution that automates proteome mass spectral analysis, optimises protein identification, and archives data in a relational database.

Science.gov (United States)

Field, Helen I; Fenyö, David; Beavis, Ronald C

2002-01-01

RADARS, a rapid, automated, data archiving and retrieval software system for high-throughput proteomic mass spectral data processing and storage, is described. The majority of mass spectrometer data files are compatible with RADARS, for consistent processing. The system automatically takes unprocessed data files, identifies proteins via in silico database searching, then stores the processed data and search results in a relational database suitable for customized reporting. The system is robust, used in 24/7 operation, accessible to multiple users of an intranet through a web browser, may be monitored by Virtual Private Network, and is secure. RADARS is scalable for use on one or many computers, and is suited to multiple processor systems. It can incorporate any local database in FASTA format, and can search protein and DNA databases online. A key feature is a suite of visualisation tools (many available gratis), allowing facile manipulation of spectra, by hand annotation, reanalysis, and access to all procedures. We also described the use of Sonar MS/MS, a novel, rapid search engine requiring 40 MB RAM per process for searches against a genomic or EST database translated in all six reading frames. RADARS reduces the cost of analysis by its efficient algorithms: Sonar MS/MS can identifiy proteins without accurate knowledge of the parent ion mass and without protein tags. Statistical scoring methods provide close-to-expert accuracy and brings robust data analysis to the non-expert user.

Yeast Interacting Proteins Database: YLR447C, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available xpression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Sp...; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; act

The STRING database in 2017

DEFF Research Database (Denmark)

Szklarczyk, Damian; Morris, John H; Cook, Helen

2017-01-01

A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein-protein association data for a large number of organi......A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein-protein association data for a large number...... of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein-protein interactions, and importing known...... pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer...

Interleukin-1beta induced changes in the protein expression of rat islets: a computerized database

DEFF Research Database (Denmark)

Andersen, H U; Fey, S J; Larsen, Peter Mose

1997-01-01

as well as the intracellular mechanisms of action of interleukin 1-mediated beta-cell cytotoxicity are unknown. However, previous studies have found an association of beta-cell destruction with alterations in protein synthesis. Thus, two-dimensional (2-D) gel electrophoresis of pancreatic islet proteins...... may be an important tool facilitating studies of the molecular pathogenesis of insulin-dependent diabetes mellitus. 2-D gel electrophoresis of islet proteins may lead to (i) the determination of qualitative and quantitative changes in specific islet proteins induced by cytokines, (ii......) the determination of the effects of agents modulating cytokine action, and (iii) the identification of primary islet protein antigen(s) initiating the immune destruction of the beta-cells. Therefore, the aim of this study was to create databases (DB) of all reproducibly detectable protein spots on 10% and 15...

Fly-DPI: database of protein interactomes for D. melanogaster in the approach of systems biology

Directory of Open Access Journals (Sweden)

Lin Chieh-Hua

2006-12-01

Full Text Available Abstract Background Proteins control and mediate many biological activities of cells by interacting with other protein partners. This work presents a statistical model to predict protein interaction networks of Drosophila melanogaster based on insight into domain interactions. Results Three high-throughput yeast two-hybrid experiments and the collection in FlyBase were used as our starting datasets. The co-occurrences of domains in these interactive events are converted into a probability score of domain-domain interaction. These scores are used to infer putative interaction among all available open reading frames (ORFs of fruit fly. Additionally, the likelihood function is used to estimate all potential protein-protein interactions. All parameters are successfully iterated and MLE is obtained for each pair of domains. Additionally, the maximized likelihood reaches its converged criteria and maintains the probability stable. The hybrid model achieves a high specificity with a loss of sensitivity, suggesting that the model may possess major features of protein-protein interactions. Several putative interactions predicted by the proposed hybrid model are supported by literatures, while experimental data with a low probability score indicate an uncertain reliability and require further proof of interaction. Fly-DPI is the online database used to present this work. It is an integrated proteomics tool with comprehensive protein annotation information from major databases as well as an effective means of predicting protein-protein interactions. As a novel search strategy, the ping-pong search is a naïve path map between two chosen proteins based on pre-computed shortest paths. Adopting effective filtering strategies will facilitate researchers in depicting the bird's eye view of the network of interest. Fly-DPI can be accessed at http://flydpi.nhri.org.tw. Conclusion This work provides two reference systems, statistical and biological, to evaluate

Amino acid sequences of predicted proteins and their annotation for 95 organism species. - Gclust Server | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Gclust Server Amino acid sequences of predicted proteins and their annotation for 95 organis...m species. Data detail Data name Amino acid sequences of predicted proteins and their annotation for 95 orga...nism species. DOI 10.18908/lsdba.nbdc00464-001 Description of data contents Amino acid sequences of predicted proteins...Database Description Download License Update History of This Database Site Policy | Contact Us Amino acid sequences of predicted prot...eins and their annotation for 95 organism species. - Gclust Server | LSDB Archive ...

SpirPro: A Spirulina proteome database and web-based tools for the analysis of protein-protein interactions at the metabolic level in Spirulina (Arthrospira) platensis C1.

Science.gov (United States)

Senachak, Jittisak; Cheevadhanarak, Supapon; Hongsthong, Apiradee

2015-07-29

Spirulina (Arthrospira) platensis is the only cyanobacterium that in addition to being studied at the molecular level and subjected to gene manipulation, can also be mass cultivated in outdoor ponds for commercial use as a food supplement. Thus, encountering environmental changes, including temperature stresses, is common during the mass production of Spirulina. The use of cyanobacteria as an experimental platform, especially for photosynthetic gene manipulation in plants and bacteria, is becoming increasingly important. Understanding the mechanisms and protein-protein interaction networks that underlie low- and high-temperature responses is relevant to Spirulina mass production. To accomplish this goal, high-throughput techniques such as OMICs analyses are used. Thus, large datasets must be collected, managed and subjected to information extraction. Therefore, databases including (i) proteomic analysis and protein-protein interaction (PPI) data and (ii) domain/motif visualization tools are required for potential use in temperature response models for plant chloroplasts and photosynthetic bacteria. A web-based repository was developed including an embedded database, SpirPro, and tools for network visualization. Proteome data were analyzed integrated with protein-protein interactions and/or metabolic pathways from KEGG. The repository provides various information, ranging from raw data (2D-gel images) to associated results, such as data from interaction and/or pathway analyses. This integration allows in silico analyses of protein-protein interactions affected at the metabolic level and, particularly, analyses of interactions between and within the affected metabolic pathways under temperature stresses for comparative proteomic analysis. The developed tool, which is coded in HTML with CSS/JavaScript and depicted in Scalable Vector Graphics (SVG), is designed for interactive analysis and exploration of the constructed network. SpirPro is publicly available on the web

Yeast Interacting Proteins Database: YGR013W, YKL012W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available tion U1 snRNP protein involved in splicing, interacts with the branchpoint-binding protein during the formation of the second commitm... PRP40 U1 snRNP protein involved in splicing, interacts with the branchpoint-binding protein during the form...ation of the second commitment complex Rows with this prey as prey (1) Rows with

Protein backbone chemical shifts predicted from searching a database for torsion angle and sequence homology

International Nuclear Information System (INIS)

Shen Yang; Bax, Ad

2007-01-01

Chemical shifts of nuclei in or attached to a protein backbone are exquisitely sensitive to their local environment. A computer program, SPARTA, is described that uses this correlation with local structure to predict protein backbone chemical shifts, given an input three-dimensional structure, by searching a newly generated database for triplets of adjacent residues that provide the best match in φ/ψ/χ 1 torsion angles and sequence similarity to the query triplet of interest. The database contains 15 N, 1 H N , 1 H α , 13 C α , 13 C β and 13 C' chemical shifts for 200 proteins for which a high resolution X-ray (≤2.4 A) structure is available. The relative importance of the weighting factors for the φ/ψ/χ 1 angles and sequence similarity was optimized empirically. The weighted, average secondary shifts of the central residues in the 20 best-matching triplets, after inclusion of nearest neighbor, ring current, and hydrogen bonding effects, are used to predict chemical shifts for the protein of known structure. Validation shows good agreement between the SPARTA-predicted and experimental shifts, with standard deviations of 2.52, 0.51, 0.27, 0.98, 1.07 and 1.08 ppm for 15 N, 1 H N , 1 H α , 13 C α , 13 C β and 13 C', respectively, including outliers

Yeast Interacting Proteins Database: YGL237C, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding prote... expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein

Yeast Interacting Proteins Database: YKL002W, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding prote...xpression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Sp

Yeast Interacting Proteins Database: YGL127C, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ith protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regula...rotein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors

Yeast Interacting Proteins Database: YOR358W, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; act...rotein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regulator o

The ABC (Analysing Biomolecular Contacts-database

Directory of Open Access Journals (Sweden)

Walter Peter

2007-03-01

Full Text Available As protein-protein interactions are one of the basic mechanisms in most cellular processes, it is desirable to understand the molecular details of protein-protein contacts and ultimately be able to predict which proteins interact. Interface areas on a protein surface that are involved in protein interactions exhibit certain characteristics. Therefore, several attempts were made to distinguish protein interactions from each other and to categorize them. One way of classification are the groups of transient and permanent interactions. Previously two of the authors analysed several properties for transient complexes such as the amino acid and secondary structure element composition and pairing preferences. Certainly, interfaces can be characterized by many more possible attributes and this is a subject of intense ongoing research. Although several freely available online databases exist that illuminate various aspects of protein-protein interactions, we decided to construct a new database collecting all desired interface features allowing for facile selection of subsets of complexes. As database-server we applied MySQL and the program logic was written in JAVA. Furthermore several class extensions and tools such as JMOL were included to visualize the interfaces and JfreeChart for the representation of diagrams and statistics. The contact data is automatically generated from standard PDB files by a tcl/tk-script running through the molecular visualization package VMD. Currently the database contains 536 interfaces extracted from 479 PDB files and it can be queried by various types of parameters. Here, we describe the database design and demonstrate its usefulness with a number of selected features.

Sting_RDB: a relational database of structural parameters for protein analysis with support for data warehousing and data mining.

Science.gov (United States)

Oliveira, S R M; Almeida, G V; Souza, K R R; Rodrigues, D N; Kuser-Falcão, P R; Yamagishi, M E B; Santos, E H; Vieira, F D; Jardine, J G; Neshich, G

2007-10-05

An effective strategy for managing protein databases is to provide mechanisms to transform raw data into consistent, accurate and reliable information. Such mechanisms will greatly reduce operational inefficiencies and improve one's ability to better handle scientific objectives and interpret the research results. To achieve this challenging goal for the STING project, we introduce Sting_RDB, a relational database of structural parameters for protein analysis with support for data warehousing and data mining. In this article, we highlight the main features of Sting_RDB and show how a user can explore it for efficient and biologically relevant queries. Considering its importance for molecular biologists, effort has been made to advance Sting_RDB toward data quality assessment. To the best of our knowledge, Sting_RDB is one of the most comprehensive data repositories for protein analysis, now also capable of providing its users with a data quality indicator. This paper differs from our previous study in many aspects. First, we introduce Sting_RDB, a relational database with mechanisms for efficient and relevant queries using SQL. Sting_rdb evolved from the earlier, text (flat file)-based database, in which data consistency and integrity was not guaranteed. Second, we provide support for data warehousing and mining. Third, the data quality indicator was introduced. Finally and probably most importantly, complex queries that could not be posed on a text-based database, are now easily implemented. Further details are accessible at the Sting_RDB demo web page: http://www.cbi.cnptia.embrapa.br/StingRDB.

ProBiS tools (algorithm, database, and web servers) for predicting and modeling of biologically interesting proteins.

Science.gov (United States)

Konc, Janez; Janežič, Dušanka

2017-09-01

ProBiS (Protein Binding Sites) Tools consist of algorithm, database, and web servers for prediction of binding sites and protein ligands based on the detection of structurally similar binding sites in the Protein Data Bank. In this article, we review the operations that ProBiS Tools perform, provide comments on the evolution of the tools, and give some implementation details. We review some of its applications to biologically interesting proteins. ProBiS Tools are freely available at http://probis.cmm.ki.si and http://probis.nih.gov. Copyright © 2017 Elsevier Ltd. All rights reserved.

ORFer--retrieval of protein sequences and open reading frames from GenBank and storage into relational databases or text files.

Science.gov (United States)

Büssow, Konrad; Hoffmann, Steve; Sievert, Volker

2002-12-19

Functional genomics involves the parallel experimentation with large sets of proteins. This requires management of large sets of open reading frames as a prerequisite of the cloning and recombinant expression of these proteins. A Java program was developed for retrieval of protein and nucleic acid sequences and annotations from NCBI GenBank, using the XML sequence format. Annotations retrieved by ORFer include sequence name, organism and also the completeness of the sequence. The program has a graphical user interface, although it can be used in a non-interactive mode. For protein sequences, the program also extracts the open reading frame sequence, if available, and checks its correct translation. ORFer accepts user input in the form of single or lists of GenBank GI identifiers or accession numbers. It can be used to extract complete sets of open reading frames and protein sequences from any kind of GenBank sequence entry, including complete genomes or chromosomes. Sequences are either stored with their features in a relational database or can be exported as text files in Fasta or tabulator delimited format. The ORFer program is freely available at http://www.proteinstrukturfabrik.de/orfer. The ORFer program allows for fast retrieval of DNA sequences, protein sequences and their open reading frames and sequence annotations from GenBank. Furthermore, storage of sequences and features in a relational database is supported. Such a database can supplement a laboratory information system (LIMS) with appropriate sequence information.

Improving decoy databases for protein folding algorithms

KAUST Repository

Lindsey, Aaron; Yeh, Hsin-Yi (Cindy); Wu, Chih-Peng; Thomas, Shawna; Amato, Nancy M.

2014-01-01

energetically stable) from non-native structures. Decoy databases are collections of non-native structures used to test and verify these functions. We present a method to evaluate and improve the quality of decoy databases by adding novel structures and removing

A database and tool, IM Browser, for exploring and integrating emerging gene and protein interaction data for Drosophila

Directory of Open Access Journals (Sweden)

Parrish Jodi R

2006-04-01

Full Text Available Abstract Background Biological processes are mediated by networks of interacting genes and proteins. Efforts to map and understand these networks are resulting in the proliferation of interaction data derived from both experimental and computational techniques for a number of organisms. The volume of this data combined with the variety of specific forms it can take has created a need for comprehensive databases that include all of the available data sets, and for exploration tools to facilitate data integration and analysis. One powerful paradigm for the navigation and analysis of interaction data is an interaction graph or map that represents proteins or genes as nodes linked by interactions. Several programs have been developed for graphical representation and analysis of interaction data, yet there remains a need for alternative programs that can provide casual users with rapid easy access to many existing and emerging data sets. Description Here we describe a comprehensive database of Drosophila gene and protein interactions collected from a variety of sources, including low and high throughput screens, genetic interactions, and computational predictions. We also present a program for exploring multiple interaction data sets and for combining data from different sources. The program, referred to as the Interaction Map (IM Browser, is a web-based application for searching and visualizing interaction data stored in a relational database system. Use of the application requires no downloads and minimal user configuration or training, thereby enabling rapid initial access to interaction data. IM Browser was designed to readily accommodate and integrate new types of interaction data as it becomes available. Moreover, all information associated with interaction measurements or predictions and the genes or proteins involved are accessible to the user. This allows combined searches and analyses based on either common or technique-specific attributes

Yeast Interacting Proteins Database: YGL145W, YNL258C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available ripheral membrane protein required for Golgi-to-ER retrograde traffic; component ... membrane protein required for Golgi-to-ER retrograde traffic; component of the ER target site that interact

Yeast Interacting Proteins Database: YNL152W, YMR032W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available YNL152W INN1 Essential protein that associates with the contractile actomyosin ring... Bait description Essential protein that associates with the contractile actomyosin ring, required for ingre

The evolution of a Web resource: The Galactosemia Proteins Database 2.0.

Science.gov (United States)

d'Acierno, Antonio; Scafuri, Bernardina; Facchiano, Angelo; Marabotti, Anna

2018-01-01

Galactosemia Proteins Database 2.0 is a Web-accessible resource collecting information about the structural and functional effects of the known variations associated to the three different enzymes of the Leloir pathway encoded by the genes GALT, GALE, and GALK1 and involved in the different forms of the genetic disease globally called "galactosemia." It represents an evolution of two available online resources we previously developed, with new data deriving from new structures, new analysis tools, and new interfaces and filters in order to improve the quality and quantity of information available for different categories of users. We propose this new resource both as a landmark for the entire world community of galactosemia and as a model for the development of similar tools for other proteins object of variations and involved in human diseases. © 2017 Wiley Periodicals, Inc.

Yeast Interacting Proteins Database: YPR103W, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available tein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors...gulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf

Yeast Interacting Proteins Database: YCL046W, YGL115W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available YCL046W - Dubious open reading frame unlikely to encode a protein, based on availab...ading frame unlikely to encode a protein, based on available experimental and comparative sequence data; par

Yeast Interacting Proteins Database: YNL258C, YGL145W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available YNL258C DSL1 Peripheral membrane protein required for Golgi-to-ER retrograde traffi...t description Peripheral membrane protein required for Golgi-to-ER retrograde traffic; component of the ER t

Yeast Interacting Proteins Database: YOL006C, YMR233W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available fusion protein localizes to the cytoplasm, nucleus and nucleolus Rows with this prey as prey (1) Rows with t...on protein localizes to the cytoplasm, nucleus and nucleolus Rows with this prey

Yeast Interacting Proteins Database: YJR091C, YKL002W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available g of integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly sy... integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthe

Yeast Interacting Proteins Database: YNL216W, YLR453C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available YNL216W RAP1 DNA-binding protein involved in either activation or repression of transcription, depending...NA-binding protein involved in either activation or repression of transcription, depending on binding site c

HCSD: the human cancer secretome database

DEFF Research Database (Denmark)

Feizi, Amir; Banaei-Esfahani, Amir; Nielsen, Jens

2015-01-01

The human cancer secretome database (HCSD) is a comprehensive database for human cancer secretome data. The cancer secretome describes proteins secreted by cancer cells and structuring information about the cancer secretome will enable further analysis of how this is related with tumor biology...... database is limiting the ability to query the increasing community knowledge. We therefore developed the Human Cancer Secretome Database (HCSD) to fulfil this gap. HCSD contains >80 000 measurements for about 7000 nonredundant human proteins collected from up to 35 high-throughput studies on 17 cancer...

The MAR databases: development and implementation of databases specific for marine metagenomics.

Science.gov (United States)

Klemetsen, Terje; Raknes, Inge A; Fu, Juan; Agafonov, Alexander; Balasundaram, Sudhagar V; Tartari, Giacomo; Robertsen, Espen; Willassen, Nils P

2018-01-04

We introduce the marine databases; MarRef, MarDB and MarCat (https://mmp.sfb.uit.no/databases/), which are publicly available resources that promote marine research and innovation. These data resources, which have been implemented in the Marine Metagenomics Portal (MMP) (https://mmp.sfb.uit.no/), are collections of richly annotated and manually curated contextual (metadata) and sequence databases representing three tiers of accuracy. While MarRef is a database for completely sequenced marine prokaryotic genomes, which represent a marine prokaryote reference genome database, MarDB includes all incomplete sequenced prokaryotic genomes regardless level of completeness. The last database, MarCat, represents a gene (protein) catalog of uncultivable (and cultivable) marine genes and proteins derived from marine metagenomics samples. The first versions of MarRef and MarDB contain 612 and 3726 records, respectively. Each record is built up of 106 metadata fields including attributes for sampling, sequencing, assembly and annotation in addition to the organism and taxonomic information. Currently, MarCat contains 1227 records with 55 metadata fields. Ontologies and controlled vocabularies are used in the contextual databases to enhance consistency. The user-friendly web interface lets the visitors browse, filter and search in the contextual databases and perform BLAST searches against the corresponding sequence databases. All contextual and sequence databases are freely accessible and downloadable from https://s1.sfb.uit.no/public/mar/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Yeast Interacting Proteins Database: YMR280C, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available olved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensor... glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, an

Yeast Interacting Proteins Database: YOR302W, YOR047C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available rol of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt...tein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt1

PDBj Mine: design and implementation of relational database interface for Protein Data Bank Japan.

Science.gov (United States)

Kinjo, Akira R; Yamashita, Reiko; Nakamura, Haruki

2010-08-25

This article is a tutorial for PDBj Mine, a new database and its interface for Protein Data Bank Japan (PDBj). In PDBj Mine, data are loaded from files in the PDBMLplus format (an extension of PDBML, PDB's canonical XML format, enriched with annotations), which are then served for the user of PDBj via the worldwide web (WWW). We describe the basic design of the relational database (RDB) and web interfaces of PDBj Mine. The contents of PDBMLplus files are first broken into XPath entities, and these paths and data are indexed in the way that reflects the hierarchical structure of the XML files. The data for each XPath type are saved into the corresponding relational table that is named as the XPath itself. The generation of table definitions from the PDBMLplus XML schema is fully automated. For efficient search, frequently queried terms are compiled into a brief summary table. Casual users can perform simple keyword search, and 'Advanced Search' which can specify various conditions on the entries. More experienced users can query the database using SQL statements which can be constructed in a uniform manner. Thus, PDBj Mine achieves a combination of the flexibility of XML documents and the robustness of the RDB. Database URL: http://www.pdbj.org/

Composition of Overlapping Protein-Protein and Protein-Ligand Interfaces.

Directory of Open Access Journals (Sweden)

Ruzianisra Mohamed

Full Text Available Protein-protein interactions (PPIs play a major role in many biological processes and they represent an important class of targets for therapeutic intervention. However, targeting PPIs is challenging because often no convenient natural substrates are available as starting point for small-molecule design. Here, we explored the characteristics of protein interfaces in five non-redundant datasets of 174 protein-protein (PP complexes, and 161 protein-ligand (PL complexes from the ABC database, 436 PP complexes, and 196 PL complexes from the PIBASE database and a dataset of 89 PL complexes from the Timbal database. In all cases, the small molecule ligands must bind at the respective PP interface. We observed similar amino acid frequencies in all three datasets. Remarkably, also the characteristics of PP contacts and overlapping PL contacts are highly similar.

Accelerating Smith-Waterman Alignment for Protein Database Search Using Frequency Distance Filtration Scheme Based on CPU-GPU Collaborative System

Directory of Open Access Journals (Sweden)

Yu Liu

2015-01-01

Full Text Available The Smith-Waterman (SW algorithm has been widely utilized for searching biological sequence databases in bioinformatics. Recently, several works have adopted the graphic card with Graphic Processing Units (GPUs and their associated CUDA model to enhance the performance of SW computations. However, these works mainly focused on the protein database search by using the intertask parallelization technique, and only using the GPU capability to do the SW computations one by one. Hence, in this paper, we will propose an efficient SW alignment method, called CUDA-SWfr, for the protein database search by using the intratask parallelization technique based on a CPU-GPU collaborative system. Before doing the SW computations on GPU, a procedure is applied on CPU by using the frequency distance filtration scheme (FDFS to eliminate the unnecessary alignments. The experimental results indicate that CUDA-SWfr runs 9.6 times and 96 times faster than the CPU-based SW method without and with FDFS, respectively.

Accelerating Smith-Waterman Alignment for Protein Database Search Using Frequency Distance Filtration Scheme Based on CPU-GPU Collaborative System.

Science.gov (United States)

Liu, Yu; Hong, Yang; Lin, Chun-Yuan; Hung, Che-Lun

2015-01-01

The Smith-Waterman (SW) algorithm has been widely utilized for searching biological sequence databases in bioinformatics. Recently, several works have adopted the graphic card with Graphic Processing Units (GPUs) and their associated CUDA model to enhance the performance of SW computations. However, these works mainly focused on the protein database search by using the intertask parallelization technique, and only using the GPU capability to do the SW computations one by one. Hence, in this paper, we will propose an efficient SW alignment method, called CUDA-SWfr, for the protein database search by using the intratask parallelization technique based on a CPU-GPU collaborative system. Before doing the SW computations on GPU, a procedure is applied on CPU by using the frequency distance filtration scheme (FDFS) to eliminate the unnecessary alignments. The experimental results indicate that CUDA-SWfr runs 9.6 times and 96 times faster than the CPU-based SW method without and with FDFS, respectively.

Yeast Interacting Proteins Database: YDL239C, YDR273W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...it as prey (1) YDR273W DON1 Meiosis-specific component of the spindle pole body, part of the leading... edge protein (LEP) coat, forms a ring-like structure at the leading edge of the prospore...ption Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing structure at the leading...description Meiosis-specific component of the spindle pole body, part of the leading edge protein (LEP) coat

The Mitochondrial Protein Atlas: A Database of Experimentally Verified Information on the Human Mitochondrial Proteome.

Science.gov (United States)

Godin, Noa; Eichler, Jerry

2017-09-01

Given its central role in various biological systems, as well as its involvement in numerous pathologies, the mitochondrion is one of the best-studied organelles. However, although the mitochondrial genome has been extensively investigated, protein-level information remains partial, and in many cases, hypothetical. The Mitochondrial Protein Atlas (MPA; URL: lifeserv.bgu.ac.il/wb/jeichler/MPA ) is a database that provides a complete, manually curated inventory of only experimentally validated human mitochondrial proteins. The MPA presently contains 911 unique protein entries, each of which is associated with at least one experimentally validated and referenced mitochondrial localization. The MPA also contains experimentally validated and referenced information defining function, structure, involvement in pathologies, interactions with other MPA proteins, as well as the method(s) of analysis used in each instance. Connections to relevant external data sources are offered for each entry, including links to NCBI Gene, PubMed, and Protein Data Bank. The MPA offers a prototype for other information sources that allow for a distinction between what has been confirmed and what remains to be verified experimentally.

TcoF-DB: dragon database for human transcription co-factors and transcription factor interacting proteins

KAUST Repository

Schaefer, Ulf; Schmeier, Sebastian; Bajic, Vladimir B.

2010-01-01

The initiation and regulation of transcription in eukaryotes is complex and involves a large number of transcription factors (TFs), which are known to bind to the regulatory regions of eukaryotic DNA. Apart from TF-DNA binding, protein-protein interaction involving TFs is an essential component of the machinery facilitating transcriptional regulation. Proteins that interact with TFs in the context of transcription regulation but do not bind to the DNA themselves, we consider transcription co-factors (TcoFs). The influence of TcoFs on transcriptional regulation and initiation, although indirect, has been shown to be significant with the functionality of TFs strongly influenced by the presence of TcoFs. While the role of TFs and their interaction with regulatory DNA regions has been well-studied, the association between TFs and TcoFs has so far been given less attention. Here, we present a resource that is comprised of a collection of human TFs and the TcoFs with which they interact. Other proteins that have a proven interaction with a TF, but are not considered TcoFs are also included. Our database contains 157 high-confidence TcoFs and additionally 379 hypothetical TcoFs. These have been identified and classified according to the type of available evidence for their involvement in transcriptional regulation and their presence in the cell nucleus. We have divided TcoFs into four groups, one of which contains high-confidence TcoFs and three others contain TcoFs which are hypothetical to different extents. We have developed the Dragon Database for Human Transcription Co-Factors and Transcription Factor Interacting Proteins (TcoF-DB). A web-based interface for this resource can be freely accessed at http://cbrc.kaust.edu.sa/tcof/ and http://apps.sanbi.ac.za/tcof/. © The Author(s) 2010.

TcoF-DB: dragon database for human transcription co-factors and transcription factor interacting proteins

KAUST Repository

Schaefer, Ulf

2010-10-21

The initiation and regulation of transcription in eukaryotes is complex and involves a large number of transcription factors (TFs), which are known to bind to the regulatory regions of eukaryotic DNA. Apart from TF-DNA binding, protein-protein interaction involving TFs is an essential component of the machinery facilitating transcriptional regulation. Proteins that interact with TFs in the context of transcription regulation but do not bind to the DNA themselves, we consider transcription co-factors (TcoFs). The influence of TcoFs on transcriptional regulation and initiation, although indirect, has been shown to be significant with the functionality of TFs strongly influenced by the presence of TcoFs. While the role of TFs and their interaction with regulatory DNA regions has been well-studied, the association between TFs and TcoFs has so far been given less attention. Here, we present a resource that is comprised of a collection of human TFs and the TcoFs with which they interact. Other proteins that have a proven interaction with a TF, but are not considered TcoFs are also included. Our database contains 157 high-confidence TcoFs and additionally 379 hypothetical TcoFs. These have been identified and classified according to the type of available evidence for their involvement in transcriptional regulation and their presence in the cell nucleus. We have divided TcoFs into four groups, one of which contains high-confidence TcoFs and three others contain TcoFs which are hypothetical to different extents. We have developed the Dragon Database for Human Transcription Co-Factors and Transcription Factor Interacting Proteins (TcoF-DB). A web-based interface for this resource can be freely accessed at http://cbrc.kaust.edu.sa/tcof/ and http://apps.sanbi.ac.za/tcof/. © The Author(s) 2010.

Yeast Interacting Proteins Database: YNL258C, YKR022C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available YNL258C DSL1 Peripheral membrane protein required for Golgi-to-ER retrograde traffi...equired for Golgi-to-ER retrograde traffic; component of the ER target site that interacts with coatomer, th...it ORF YNL258C Bait gene name DSL1 Bait description Peripheral membrane protein r

Metagenomic Taxonomy-Guided Database-Searching Strategy for Improving Metaproteomic Analysis.

Science.gov (United States)

Xiao, Jinqiu; Tanca, Alessandro; Jia, Ben; Yang, Runqing; Wang, Bo; Zhang, Yu; Li, Jing

2018-04-06

Metaproteomics provides a direct measure of the functional information by investigating all proteins expressed by a microbiota. However, due to the complexity and heterogeneity of microbial communities, it is very hard to construct a sequence database suitable for a metaproteomic study. Using a public database, researchers might not be able to identify proteins from poorly characterized microbial species, while a sequencing-based metagenomic database may not provide adequate coverage for all potentially expressed protein sequences. To address this challenge, we propose a metagenomic taxonomy-guided database-search strategy (MT), in which a merged database is employed, consisting of both taxonomy-guided reference protein sequences from public databases and proteins from metagenome assembly. By applying our MT strategy to a mock microbial mixture, about two times as many peptides were detected as with the metagenomic database only. According to the evaluation of the reliability of taxonomic attribution, the rate of misassignments was comparable to that obtained using an a priori matched database. We also evaluated the MT strategy with a human gut microbial sample, and we found 1.7 times as many peptides as using a standard metagenomic database. In conclusion, our MT strategy allows the construction of databases able to provide high sensitivity and precision in peptide identification in metaproteomic studies, enabling the detection of proteins from poorly characterized species within the microbiota.

Yeast Interacting Proteins Database: YKL002W, YFL034C-B [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthes...ntegral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthesi

SoyDB: a knowledge database of soybean transcription factors

Directory of Open Access Journals (Sweden)

Valliyodan Babu

2010-01-01

Full Text Available Abstract Background Transcription factors play the crucial rule of regulating gene expression and influence almost all biological processes. Systematically identifying and annotating transcription factors can greatly aid further understanding their functions and mechanisms. In this article, we present SoyDB, a user friendly database containing comprehensive knowledge of soybean transcription factors. Description The soybean genome was recently sequenced by the Department of Energy-Joint Genome Institute (DOE-JGI and is publicly available. Mining of this sequence identified 5,671 soybean genes as putative transcription factors. These genes were comprehensively annotated as an aid to the soybean research community. We developed SoyDB - a knowledge database for all the transcription factors in the soybean genome. The database contains protein sequences, predicted tertiary structures, putative DNA binding sites, domains, homologous templates in the Protein Data Bank (PDB, protein family classifications, multiple sequence alignments, consensus protein sequence motifs, web logo of each family, and web links to the soybean transcription factor database PlantTFDB, known EST sequences, and other general protein databases including Swiss-Prot, Gene Ontology, KEGG, EMBL, TAIR, InterPro, SMART, PROSITE, NCBI, and Pfam. The database can be accessed via an interactive and convenient web server, which supports full-text search, PSI-BLAST sequence search, database browsing by protein family, and automatic classification of a new protein sequence into one of 64 annotated transcription factor families by hidden Markov models. Conclusions A comprehensive soybean transcription factor database was constructed and made publicly accessible at http://casp.rnet.missouri.edu/soydb/.

ContaMiner and ContaBase: a webserver and database for early identification of unwantedly crystallized protein contaminants

KAUST Repository

Hungler, Arnaud; Momin, Afaque Ahmad Imtiyaz; Diederichs, Kay; Arold, Stefan T.

2016-01-01

Solving the phase problem in protein X-ray crystallography relies heavily on the identity of the crystallized protein, especially when molecular replacement (MR) methods are used. Yet, it is not uncommon that a contaminant crystallizes instead of the protein of interest. Such contaminants may be proteins from the expression host organism, protein fusion tags or proteins added during the purification steps. Many contaminants co-purify easily, crystallize and give good diffraction data. Identification of contaminant crystals may take time, since the presence of the contaminant is unexpected and its identity unknown. A webserver (ContaMiner) and a contaminant database (ContaBase) have been established, to allow fast MR-based screening of crystallographic data against currently 62 known contaminants. The web-based ContaMiner (available at http://strube.cbrc.kaust.edu.sa/contaminer/) currently produces results in 5 min to 4 h. The program is also available in a github repository and can be installed locally. ContaMiner enables screening of novel crystals at synchrotron beamlines, and it would be valuable as a routine safety check for 'crystallization and preliminary X-ray analysis' publications. Thus, in addition to potentially saving X-ray crystallographers much time and effort, ContaMiner might considerably lower the risk of publishing erroneous data. A web server, titled ContaMiner, has been established, which allows fast molecular-replacement-based screening of crystallographic data against a database (ContaBase) of currently 62 potential contaminants. ContaMiner enables systematic screening of novel crystals at synchrotron beamlines, and it would be valuable as a routine safety check for 'crystallization and preliminary X-ray analysis' publications. © Arnaud Hungler et al. 2016.

ContaMiner and ContaBase: a webserver and database for early identification of unwantedly crystallized protein contaminants

KAUST Repository

Hungler, Arnaud

2016-11-02

Solving the phase problem in protein X-ray crystallography relies heavily on the identity of the crystallized protein, especially when molecular replacement (MR) methods are used. Yet, it is not uncommon that a contaminant crystallizes instead of the protein of interest. Such contaminants may be proteins from the expression host organism, protein fusion tags or proteins added during the purification steps. Many contaminants co-purify easily, crystallize and give good diffraction data. Identification of contaminant crystals may take time, since the presence of the contaminant is unexpected and its identity unknown. A webserver (ContaMiner) and a contaminant database (ContaBase) have been established, to allow fast MR-based screening of crystallographic data against currently 62 known contaminants. The web-based ContaMiner (available at http://strube.cbrc.kaust.edu.sa/contaminer/) currently produces results in 5 min to 4 h. The program is also available in a github repository and can be installed locally. ContaMiner enables screening of novel crystals at synchrotron beamlines, and it would be valuable as a routine safety check for \\'crystallization and preliminary X-ray analysis\\' publications. Thus, in addition to potentially saving X-ray crystallographers much time and effort, ContaMiner might considerably lower the risk of publishing erroneous data. A web server, titled ContaMiner, has been established, which allows fast molecular-replacement-based screening of crystallographic data against a database (ContaBase) of currently 62 potential contaminants. ContaMiner enables systematic screening of novel crystals at synchrotron beamlines, and it would be valuable as a routine safety check for \\'crystallization and preliminary X-ray analysis\\' publications. © Arnaud Hungler et al. 2016.

Olfactory Receptor Database: a sensory chemoreceptor resource

OpenAIRE

Skoufos, Emmanouil; Marenco, Luis; Nadkarni, Prakash M.; Miller, Perry L.; Shepherd, Gordon M.

2000-01-01

The Olfactory Receptor Database (ORDB) is a WWW-accessible database that has been expanded from an olfactory receptor resource to a chemoreceptor resource. It stores data on six classes of G-protein-coupled sensory chemoreceptors: (i) olfactory receptor-like proteins, (ii) vomeronasal receptors, (iii) insect olfactory receptors, (iv) worm chemoreceptors, (v) taste papilla receptors and (vi) fungal pheromone receptors. A complementary database of the ligands of these receptors (OdorDB) has bee...

SwissPalm: Protein Palmitoylation database.

Science.gov (United States)

Blanc, Mathieu; David, Fabrice; Abrami, Laurence; Migliozzi, Daniel; Armand, Florence; Bürgi, Jérôme; van der Goot, Françoise Gisou

2015-01-01

Protein S-palmitoylation is a reversible post-translational modification that regulates many key biological processes, although the full extent and functions of protein S-palmitoylation remain largely unexplored. Recent developments of new chemical methods have allowed the establishment of palmitoyl-proteomes of a variety of cell lines and tissues from different species.  As the amount of information generated by these high-throughput studies is increasing, the field requires centralization and comparison of this information. Here we present SwissPalm ( http://swisspalm.epfl.ch), our open, comprehensive, manually curated resource to study protein S-palmitoylation. It currently encompasses more than 5000 S-palmitoylated protein hits from seven species, and contains more than 500 specific sites of S-palmitoylation. SwissPalm also provides curated information and filters that increase the confidence in true positive hits, and integrates predictions of S-palmitoylated cysteine scores, orthologs and isoform multiple alignments. Systems analysis of the palmitoyl-proteome screens indicate that 10% or more of the human proteome is susceptible to S-palmitoylation. Moreover, ontology and pathway analyses of the human palmitoyl-proteome reveal that key biological functions involve this reversible lipid modification. Comparative analysis finally shows a strong crosstalk between S-palmitoylation and other post-translational modifications. Through the compilation of data and continuous updates, SwissPalm will provide a powerful tool to unravel the global importance of protein S-palmitoylation.

O-GLYCBASE: a revised database of O-glycosylated proteins

DEFF Research Database (Denmark)

Hansen, Jan; Lund, Ole; Nielsen, Jens O.

1996-01-01

O-GLYCBASE is a comprehensive database of information on glycoproteins and their O-linked glycosylation sites. Entries are compiled and revised from the SWISS-PROT and PIR databases as well as directly from recently published reports. Nineteen percent of the entries extracted from the databases n...... of mucin type O-glycosylation sites in mammalian glycoproteins exclusively from the primary sequence is made available by E-mail or WWW. The O-GLYCBASE database is also available electronically through our WWW server or by anonymous FTP....

Exploring the Ligand-Protein Networks in Traditional Chinese Medicine: Current Databases, Methods, and Applications

Directory of Open Access Journals (Sweden)

Mingzhu Zhao

2013-01-01

Full Text Available The traditional Chinese medicine (TCM, which has thousands of years of clinical application among China and other Asian countries, is the pioneer of the “multicomponent-multitarget” and network pharmacology. Although there is no doubt of the efficacy, it is difficult to elucidate convincing underlying mechanism of TCM due to its complex composition and unclear pharmacology. The use of ligand-protein networks has been gaining significant value in the history of drug discovery while its application in TCM is still in its early stage. This paper firstly surveys TCM databases for virtual screening that have been greatly expanded in size and data diversity in recent years. On that basis, different screening methods and strategies for identifying active ingredients and targets of TCM are outlined based on the amount of network information available, both on sides of ligand bioactivity and the protein structures. Furthermore, applications of successful in silico target identification attempts are discussed in detail along with experiments in exploring the ligand-protein networks of TCM. Finally, it will be concluded that the prospective application of ligand-protein networks can be used not only to predict protein targets of a small molecule, but also to explore the mode of action of TCM.

BioMagResBank databases DOCR and FRED containing converted and filtered sets of experimental NMR restraints and coordinates from over 500 protein PDB structures

Energy Technology Data Exchange (ETDEWEB)

Doreleijers, Jurgen F. [University of Wisconsin-Madison, BioMagResBank, Department of Biochemistry (United States); Nederveen, Aart J. [Utrecht University, Bijvoet Center for Biomolecular Research (Netherlands); Vranken, Wim [European Bioinformatics Institute, Macromolecular Structure Database group (United Kingdom); Lin Jundong [University of Wisconsin-Madison, BioMagResBank, Department of Biochemistry (United States); Bonvin, Alexandre M.J.J.; Kaptein, Robert [Utrecht University, Bijvoet Center for Biomolecular Research (Netherlands); Markley, John L.; Ulrich, Eldon L. [University of Wisconsin-Madison, BioMagResBank, Department of Biochemistry (United States)], E-mail: elu@bmrb.wisc.edu

2005-05-15

We present two new databases of NMR-derived distance and dihedral angle restraints: the Database Of Converted Restraints (DOCR) and the Filtered Restraints Database (FRED). These databases currently correspond to 545 proteins with NMR structures deposited in the Protein Databank (PDB). The criteria for inclusion were that these should be unique, monomeric proteins with author-provided experimental NMR data and coordinates available from the PDB capable of being parsed and prepared in a consistent manner. The Wattos program was used to parse the files, and the CcpNmr FormatConverter program was used to prepare them semi-automatically. New modules, including a new implementation of Aqua in the BioMagResBank (BMRB) software Wattos were used to analyze the sets of distance restraints (DRs) for inconsistencies, redundancies, NOE completeness, classification and violations with respect to the original coordinates. Restraints that could not be associated with a known nomenclature were flagged. The coordinates of hydrogen atoms were recalculated from the positions of heavy atoms to allow for a full restraint analysis. The DOCR database contains restraint and coordinate data that is made consistent with each other and with IUPAC conventions. The FRED database is based on the DOCR data but is filtered for use by test calculation protocols and longitudinal analyses and validations. These two databases are available from websites of the BMRB and the Macromolecular Structure Database (MSD) in various formats: NMR-STAR, CCPN XML, and in formats suitable for direct use in the software packages CNS and CYANA.

BioMagResBank databases DOCR and FRED containing converted and filtered sets of experimental NMR restraints and coordinates from over 500 protein PDB structures

International Nuclear Information System (INIS)

Doreleijers, Jurgen F.; Nederveen, Aart J.; Vranken, Wim; Lin Jundong; Bonvin, Alexandre M.J.J.; Kaptein, Robert; Markley, John L.; Ulrich, Eldon L.

2005-01-01

We present two new databases of NMR-derived distance and dihedral angle restraints: the Database Of Converted Restraints (DOCR) and the Filtered Restraints Database (FRED). These databases currently correspond to 545 proteins with NMR structures deposited in the Protein Databank (PDB). The criteria for inclusion were that these should be unique, monomeric proteins with author-provided experimental NMR data and coordinates available from the PDB capable of being parsed and prepared in a consistent manner. The Wattos program was used to parse the files, and the CcpNmr FormatConverter program was used to prepare them semi-automatically. New modules, including a new implementation of Aqua in the BioMagResBank (BMRB) software Wattos were used to analyze the sets of distance restraints (DRs) for inconsistencies, redundancies, NOE completeness, classification and violations with respect to the original coordinates. Restraints that could not be associated with a known nomenclature were flagged. The coordinates of hydrogen atoms were recalculated from the positions of heavy atoms to allow for a full restraint analysis. The DOCR database contains restraint and coordinate data that is made consistent with each other and with IUPAC conventions. The FRED database is based on the DOCR data but is filtered for use by test calculation protocols and longitudinal analyses and validations. These two databases are available from websites of the BMRB and the Macromolecular Structure Database (MSD) in various formats: NMR-STAR, CCPN XML, and in formats suitable for direct use in the software packages CNS and CYANA

Dynameomics: a multi-dimensional analysis-optimized database for dynamic protein data.

Science.gov (United States)

Kehl, Catherine; Simms, Andrew M; Toofanny, Rudesh D; Daggett, Valerie

2008-06-01

The Dynameomics project is our effort to characterize the native-state dynamics and folding/unfolding pathways of representatives of all known protein folds by way of molecular dynamics simulations, as described by Beck et al. (in Protein Eng. Des. Select., the first paper in this series). The data produced by these simulations are highly multidimensional in structure and multi-terabytes in size. Both of these features present significant challenges for storage, retrieval and analysis. For optimal data modeling and flexibility, we needed a platform that supported both multidimensional indices and hierarchical relationships between related types of data and that could be integrated within our data warehouse, as described in the accompanying paper directly preceding this one. For these reasons, we have chosen On-line Analytical Processing (OLAP), a multi-dimensional analysis optimized database, as an analytical platform for these data. OLAP is a mature technology in the financial sector, but it has not been used extensively for scientific analysis. Our project is further more unusual for its focus on the multidimensional and analytical capabilities of OLAP rather than its aggregation capacities. The dimensional data model and hierarchies are very flexible. The query language is concise for complex analysis and rapid data retrieval. OLAP shows great promise for the dynamic protein analysis for bioengineering and biomedical applications. In addition, OLAP may have similar potential for other scientific and engineering applications involving large and complex datasets.

Cluster based on sequence comparison of homologous proteins of 95 organism species - Gclust Server | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Gclust Server Cluster based on sequence comparison of homologous proteins of 95 organism spe...cies Data detail Data name Cluster based on sequence comparison of homologous proteins of 95 organism specie...istory of This Database Site Policy | Contact Us Cluster based on sequence compariso

Gene composer: database software for protein construct design, codon engineering, and gene synthesis.

Science.gov (United States)

Lorimer, Don; Raymond, Amy; Walchli, John; Mixon, Mark; Barrow, Adrienne; Wallace, Ellen; Grice, Rena; Burgin, Alex; Stewart, Lance

2009-04-21

To improve efficiency in high throughput protein structure determination, we have developed a database software package, Gene Composer, which facilitates the information-rich design of protein constructs and their codon engineered synthetic gene sequences. With its modular workflow design and numerous graphical user interfaces, Gene Composer enables researchers to perform all common bio-informatics steps used in modern structure guided protein engineering and synthetic gene engineering. An interactive Alignment Viewer allows the researcher to simultaneously visualize sequence conservation in the context of known protein secondary structure, ligand contacts, water contacts, crystal contacts, B-factors, solvent accessible area, residue property type and several other useful property views. The Construct Design Module enables the facile design of novel protein constructs with altered N- and C-termini, internal insertions or deletions, point mutations, and desired affinity tags. The modifications can be combined and permuted into multiple protein constructs, and then virtually cloned in silico into defined expression vectors. The Gene Design Module uses a protein-to-gene algorithm that automates the back-translation of a protein amino acid sequence into a codon engineered nucleic acid gene sequence according to a selected codon usage table with minimal codon usage threshold, defined G:C% content, and desired sequence features achieved through synonymous codon selection that is optimized for the intended expression system. The gene-to-oligo algorithm of the Gene Design Module plans out all of the required overlapping oligonucleotides and mutagenic primers needed to synthesize the desired gene constructs by PCR, and for physically cloning them into selected vectors by the most popular subcloning strategies. We present a complete description of Gene Composer functionality, and an efficient PCR-based synthetic gene assembly procedure with mis-match specific endonuclease

Gene Composer: database software for protein construct design, codon engineering, and gene synthesis

Directory of Open Access Journals (Sweden)

Mixon Mark

2009-04-01

Full Text Available Abstract Background To improve efficiency in high throughput protein structure determination, we have developed a database software package, Gene Composer, which facilitates the information-rich design of protein constructs and their codon engineered synthetic gene sequences. With its modular workflow design and numerous graphical user interfaces, Gene Composer enables researchers to perform all common bio-informatics steps used in modern structure guided protein engineering and synthetic gene engineering. Results An interactive Alignment Viewer allows the researcher to simultaneously visualize sequence conservation in the context of known protein secondary structure, ligand contacts, water contacts, crystal contacts, B-factors, solvent accessible area, residue property type and several other useful property views. The Construct Design Module enables the facile design of novel protein constructs with altered N- and C-termini, internal insertions or deletions, point mutations, and desired affinity tags. The modifications can be combined and permuted into multiple protein constructs, and then virtually cloned in silico into defined expression vectors. The Gene Design Module uses a protein-to-gene algorithm that automates the back-translation of a protein amino acid sequence into a codon engineered nucleic acid gene sequence according to a selected codon usage table with minimal codon usage threshold, defined G:C% content, and desired sequence features achieved through synonymous codon selection that is optimized for the intended expression system. The gene-to-oligo algorithm of the Gene Design Module plans out all of the required overlapping oligonucleotides and mutagenic primers needed to synthesize the desired gene constructs by PCR, and for physically cloning them into selected vectors by the most popular subcloning strategies. Conclusion We present a complete description of Gene Composer functionality, and an efficient PCR-based synthetic gene

Mycobacteriophage genome database.

Science.gov (United States)

Joseph, Jerrine; Rajendran, Vasanthi; Hassan, Sameer; Kumar, Vanaja

2011-01-01

Mycobacteriophage genome database (MGDB) is an exclusive repository of the 64 completely sequenced mycobacteriophages with annotated information. It is a comprehensive compilation of the various gene parameters captured from several databases pooled together to empower mycobacteriophage researchers. The MGDB (Version No.1.0) comprises of 6086 genes from 64 mycobacteriophages classified into 72 families based on ACLAME database. Manual curation was aided by information available from public databases which was enriched further by analysis. Its web interface allows browsing as well as querying the classification. The main objective is to collect and organize the complexity inherent to mycobacteriophage protein classification in a rational way. The other objective is to browse the existing and new genomes and describe their functional annotation. The database is available for free at http://mpgdb.ibioinformatics.org/mpgdb.php.

Using SQL Databases for Sequence Similarity Searching and Analysis.

Science.gov (United States)

Pearson, William R; Mackey, Aaron J

2017-09-13

Relational databases can integrate diverse types of information and manage large sets of similarity search results, greatly simplifying genome-scale analyses. By focusing on taxonomic subsets of sequences, relational databases can reduce the size and redundancy of sequence libraries and improve the statistical significance of homologs. In addition, by loading similarity search results into a relational database, it becomes possible to explore and summarize the relationships between all of the proteins in an organism and those in other biological kingdoms. This unit describes how to use relational databases to improve the efficiency of sequence similarity searching and demonstrates various large-scale genomic analyses of homology-related data. It also describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. The unit also introduces search_demo, a database that stores sequence similarity search results. The search_demo database is then used to explore the evolutionary relationships between E. coli proteins and proteins in other organisms in a large-scale comparative genomic analysis. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Database-independent, database-dependent, and extended interpretation of peptide mass spectra in VEMS V2.0

DEFF Research Database (Denmark)

Matthiesen, Rune; Bunkenborg, Jakob; Stensballe, Allan

2004-01-01

, and generation of protein and peptide databases. VEMS V2.0 has been developed into a fast tool for combining database-independent and -dependent protein assignments in an extended analysis of MS/MS-peptide data. MS or MS/MS data can be directly recalibrated after the first search by fitting the data to the best...... search result using polynomial equations. The score function is an improvement of known scoring algorithms and can be adapted for any MS instrument type. In addition, VEMS offers a novel statistical model for evaluating the significance of the protein assignment. The novel features are illustrated...

PSI/TM-Coffee: a web server for fast and accurate multiple sequence alignments of regular and transmembrane proteins using homology extension on reduced databases.

Science.gov (United States)

Floden, Evan W; Tommaso, Paolo D; Chatzou, Maria; Magis, Cedrik; Notredame, Cedric; Chang, Jia-Ming

2016-07-08

The PSI/TM-Coffee web server performs multiple sequence alignment (MSA) of proteins by combining homology extension with a consistency based alignment approach. Homology extension is performed with Position Specific Iterative (PSI) BLAST searches against a choice of redundant and non-redundant databases. The main novelty of this server is to allow databases of reduced complexity to rapidly perform homology extension. This server also gives the possibility to use transmembrane proteins (TMPs) reference databases to allow even faster homology extension on this important category of proteins. Aside from an MSA, the server also outputs topological prediction of TMPs using the HMMTOP algorithm. Previous benchmarking of the method has shown this approach outperforms the most accurate alignment methods such as MSAProbs, Kalign, PROMALS, MAFFT, ProbCons and PRALINE™. The web server is available at http://tcoffee.crg.cat/tmcoffee. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification of ace inhibitory cryptides in Tilapia protein hydrolysate by UPLC-MS/MS coupled to database analysis.

Science.gov (United States)

Yesmine, Ben Henda; Antoine, Bonnet; da Silva Ortência Leocádia, Nunes Gonzalez; Rogério, Boscolo Wilson; Ingrid, Arnaudin; Nicolas, Bridiau; Thierry, Maugard; Jean-Marie, Piot; Frédéric, Sannier; Stéphanie, Bordenave-Juchereau

2017-05-01

An ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry method was developed and applied to identify short angiotensin-I-converting enzyme (ACE) inhibitory cryptides in Tilapia (Oreochromis Niloticus) protein hydrolyzate. A database was created with previously identified ACE-inhibitory di- and tripeptides and the lowest molecular weight fraction of Tilapia hydrolysate was analysed for coincidences. Only VW and VY were identified. Further analysis of collected fractions conducted to the identification of 51 different peptides in major fractions. 19 peptides selected were synthesised and tested for their ACE inhibitory potential. TL, TI, IK, LR, LD, IQ, DI, AILE, ALLE, ALIE and AIIE were identified as new ACE inhibitors. The findings from this study point UPLC-MS/MS combined with the creation of a database as an efficient technique to identify specific short peptides within a complex hydrolysate, in addition with de novo sequencing. This efficient characterisation of bioactive factors like cryptides in protein hydrolysates will extend their use as functional foods. Copyright © 2017 Elsevier B.V. All rights reserved.

YMDB: the Yeast Metabolome Database

Science.gov (United States)

Jewison, Timothy; Knox, Craig; Neveu, Vanessa; Djoumbou, Yannick; Guo, An Chi; Lee, Jacqueline; Liu, Philip; Mandal, Rupasri; Krishnamurthy, Ram; Sinelnikov, Igor; Wilson, Michael; Wishart, David S.

2012-01-01

The Yeast Metabolome Database (YMDB, http://www.ymdb.ca) is a richly annotated ‘metabolomic’ database containing detailed information about the metabolome of Saccharomyces cerevisiae. Modeled closely after the Human Metabolome Database, the YMDB contains >2000 metabolites with links to 995 different genes/proteins, including enzymes and transporters. The information in YMDB has been gathered from hundreds of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the YMDB also contains an extensive collection of experimental intracellular and extracellular metabolite concentration data compiled from detailed Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR) metabolomic analyses performed in our lab. This is further supplemented with thousands of NMR and MS spectra collected on pure, reference yeast metabolites. Each metabolite entry in the YMDB contains an average of 80 separate data fields including comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, intracellular/extracellular concentrations, growth conditions and substrates, pathway information, enzyme data, gene/protein sequence data, as well as numerous hyperlinks to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided that support text, chemical structure, spectral, molecular weight and gene/protein sequence queries. Because of S. cervesiae's importance as a model organism for biologists and as a biofactory for industry, we believe this kind of database could have considerable appeal not only to metabolomics researchers, but also to yeast biologists, systems biologists, the industrial fermentation industry, as well as the beer, wine and spirit industry. PMID:22064855

ECMDB: The E. coli Metabolome Database

OpenAIRE

Guo, An Chi; Jewison, Timothy; Wilson, Michael; Liu, Yifeng; Knox, Craig; Djoumbou, Yannick; Lo, Patrick; Mandal, Rupasri; Krishnamurthy, Ram; Wishart, David S.

2012-01-01

The Escherichia coli Metabolome Database (ECMDB, http://www.ecmdb.ca) is a comprehensively annotated metabolomic database containing detailed information about the metabolome of E. coli (K-12). Modelled closely on the Human and Yeast Metabolome Databases, the ECMDB contains >2600 metabolites with links to ?1500 different genes and proteins, including enzymes and transporters. The information in the ECMDB has been collected from dozens of textbooks, journal articles and electronic databases. E...

Database Description - TMBETA-GENOME | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available ENOME is a database for transmembrane β-barrel proteins in complete genomes. For each genome, calculations with machine learning algo...rithms and statistical methods have been perfumed and th

Generation of a predicted protein database from EST data and application to iTRAQ analyses in grape (Vitis vinifera cv. Cabernet Sauvignon) berries at ripening initiation

Science.gov (United States)

Lücker, Joost; Laszczak, Mario; Smith, Derek; Lund, Steven T

2009-01-01

Background iTRAQ is a proteomics technique that uses isobaric tags for relative and absolute quantitation of tryptic peptides. In proteomics experiments, the detection and high confidence annotation of proteins and the significance of corresponding expression differences can depend on the quality and the species specificity of the tryptic peptide map database used for analysis of the data. For species for which finished genome sequence data are not available, identification of proteins relies on similarity to proteins from other species using comprehensive peptide map databases such as the MSDB. Results We were interested in characterizing ripening initiation ('veraison') in grape berries at the protein level in order to better define the molecular control of this important process for grape growers and wine makers. We developed a bioinformatic pipeline for processing EST data in order to produce a predicted tryptic peptide database specifically targeted to the wine grape cultivar, Vitis vinifera cv. Cabernet Sauvignon, and lacking truncated N- and C-terminal fragments. By searching iTRAQ MS/MS data generated from berry exocarp and mesocarp samples at ripening initiation, we determined that implementation of the custom database afforded a large improvement in high confidence peptide annotation in comparison to the MSDB. We used iTRAQ MS/MS in conjunction with custom peptide db searches to quantitatively characterize several important pathway components for berry ripening previously described at the transcriptional level and confirmed expression patterns for these at the protein level. Conclusion We determined that a predicted peptide database for MS/MS applications can be derived from EST data using advanced clustering and trimming approaches and successfully implemented for quantitative proteome profiling. Quantitative shotgun proteome profiling holds great promise for characterizing biological processes such as fruit ripening initiation and may be further

ATGC database and ATGC-COGs: an updated resource for micro- and macro-evolutionary studies of prokaryotic genomes and protein family annotation.

Science.gov (United States)

Kristensen, David M; Wolf, Yuri I; Koonin, Eugene V

2017-01-04

The Alignable Tight Genomic Clusters (ATGCs) database is a collection of closely related bacterial and archaeal genomes that provides several tools to aid research into evolutionary processes in the microbial world. Each ATGC is a taxonomy-independent cluster of 2 or more completely sequenced genomes that meet the objective criteria of a high degree of local gene order (synteny) and a small number of synonymous substitutions in the protein-coding genes. As such, each ATGC is suited for analysis of microevolutionary variations within a cohesive group of organisms (e.g. species), whereas the entire collection of ATGCs is useful for macroevolutionary studies. The ATGC database includes many forms of pre-computed data, in particular ATGC-COGs (Clusters of Orthologous Genes), multiple sequence alignments, a set of 'index' orthologs representing the most well-conserved members of each ATGC-COG, the phylogenetic tree of the organisms within each ATGC, etc. Although the ATGC database contains several million proteins from thousands of genomes organized into hundreds of clusters (roughly a 4-fold increase since the last version of the ATGC database), it is now built with completely automated methods and will be regularly updated following new releases of the NCBI RefSeq database. The ATGC database is hosted jointly at the University of Iowa at dmk-brain.ecn.uiowa.edu/ATGC/ and the NCBI at ftp.ncbi.nlm.nih.gov/pub/kristensen/ATGC/atgc_home.html. Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

RaftProt: mammalian lipid raft proteome database.

Science.gov (United States)

Shah, Anup; Chen, David; Boda, Akash R; Foster, Leonard J; Davis, Melissa J; Hill, Michelle M

2015-01-01

RaftProt (http://lipid-raft-database.di.uq.edu.au/) is a database of mammalian lipid raft-associated proteins as reported in high-throughput mass spectrometry studies. Lipid rafts are specialized membrane microdomains enriched in cholesterol and sphingolipids thought to act as dynamic signalling and sorting platforms. Given their fundamental roles in cellular regulation, there is a plethora of information on the size, composition and regulation of these membrane microdomains, including a large number of proteomics studies. To facilitate the mining and analysis of published lipid raft proteomics studies, we have developed a searchable database RaftProt. In addition to browsing the studies, performing basic queries by protein and gene names, searching experiments by cell, tissue and organisms; we have implemented several advanced features to facilitate data mining. To address the issue of potential bias due to biochemical preparation procedures used, we have captured the lipid raft preparation methods and implemented advanced search option for methodology and sample treatment conditions, such as cholesterol depletion. Furthermore, we have identified a list of high confidence proteins, and enabled searching only from this list of likely bona fide lipid raft proteins. Given the apparent biological importance of lipid raft and their associated proteins, this database would constitute a key resource for the scientific community. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Transporter Classification Database (TCDB)

Data.gov (United States)

U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

E-MSD: the European Bioinformatics Institute Macromolecular Structure Database.

Science.gov (United States)

Boutselakis, H; Dimitropoulos, D; Fillon, J; Golovin, A; Henrick, K; Hussain, A; Ionides, J; John, M; Keller, P A; Krissinel, E; McNeil, P; Naim, A; Newman, R; Oldfield, T; Pineda, J; Rachedi, A; Copeland, J; Sitnov, A; Sobhany, S; Suarez-Uruena, A; Swaminathan, J; Tagari, M; Tate, J; Tromm, S; Velankar, S; Vranken, W

2003-01-01

The E-MSD macromolecular structure relational database (http://www.ebi.ac.uk/msd) is designed to be a single access point for protein and nucleic acid structures and related information. The database is derived from Protein Data Bank (PDB) entries. Relational database technologies are used in a comprehensive cleaning procedure to ensure data uniformity across the whole archive. The search database contains an extensive set of derived properties, goodness-of-fit indicators, and links to other EBI databases including InterPro, GO, and SWISS-PROT, together with links to SCOP, CATH, PFAM and PROSITE. A generic search interface is available, coupled with a fast secondary structure domain search tool.

Yeast Interacting Proteins Database: YKL002W, YLR423C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthes... into lumenal vesicles of multivesicular bodies, and for delivery of newly synthesized vacuolar enzymes to t

Yeast Interacting Proteins Database: YKL002W, YDL165W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available integral membrane proteins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthes...ins into lumenal vesicles of multivesicular bodies, and for delivery of newly synthesized vacuolar enzymes t

Yeast Interacting Proteins Database: YER081W, YDR105C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available YDR105C TMS1 Vacuolar membrane protein of unknown function that is conserved in mammals; predicted to contai...tion that is conserved in mammals; predicted to contain eleven transmembrane heli

The NCBI BioSystems database.

Science.gov (United States)

Geer, Lewis Y; Marchler-Bauer, Aron; Geer, Renata C; Han, Lianyi; He, Jane; He, Siqian; Liu, Chunlei; Shi, Wenyao; Bryant, Stephen H

2010-01-01

The NCBI BioSystems database, found at http://www.ncbi.nlm.nih.gov/biosystems/, centralizes and cross-links existing biological systems databases, increasing their utility and target audience by integrating their pathways and systems into NCBI resources. This integration allows users of NCBI's Entrez databases to quickly categorize proteins, genes and small molecules by metabolic pathway, disease state or other BioSystem type, without requiring time-consuming inference of biological relationships from the literature or multiple experimental datasets.

Yeast Interacting Proteins Database: YOR117W, YJL184W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available c stress response, telomere uncapping and elongation, transcription; component of the EKC/KEOPS protein comp...n proposed to be involved in the modification of N-linked oligosaccharides, osmotic stress response, telomere uncap

InSilico Proteomics System: Integration and Application of Protein and Protein-Protein Interaction Data using Microsoft .NET

Directory of Open Access Journals (Sweden)

Straßer Wolfgang

2006-12-01

Full Text Available In the last decades, biological databases became the major knowledge resource for researchers in the field of molecular biology. The distribution of information among these databases is one of the major problems. An overview about the subject area of data access and representation of protein and protein-protein interaction data within public biological databases is described. For a comprehensive and consistent way of searching and analysing integrated protein and protein-protein interaction data, the InSilico Proteomics (ISP project has been initiated. Its three main objectives are (1 to provide an integrated knowledge pool for data investigation and global network analysis functions for a better understanding of a cell’s interactome, (2 employment of public data for plausibility analysis and validation of in-house experimental data and (3 testing the applicability of Microsoft’s .NET architecture for bioinformatics applications. Data integrated into the ISP database can be queried through the Web portal PRIMOS (PRotein Interaction and MOlecule Search which is freely available at http://biomis.fh-hagenberg.at/isp/primos.

Using random forests for assistance in the curation of G-protein coupled receptor databases.

Science.gov (United States)

Shkurin, Aleksei; Vellido, Alfredo

2017-08-18

Biology is experiencing a gradual but fast transformation from a laboratory-centred science towards a data-centred one. As such, it requires robust data engineering and the use of quantitative data analysis methods as part of database curation. This paper focuses on G protein-coupled receptors, a large and heterogeneous super-family of cell membrane proteins of interest to biology in general. One of its families, Class C, is of particular interest to pharmacology and drug design. This family is quite heterogeneous on its own, and the discrimination of its several sub-families is a challenging problem. In the absence of known crystal structure, such discrimination must rely on their primary amino acid sequences. We are interested not as much in achieving maximum sub-family discrimination accuracy using quantitative methods, but in exploring sequence misclassification behavior. Specifically, we are interested in isolating those sequences showing consistent misclassification, that is, sequences that are very often misclassified and almost always to the same wrong sub-family. Random forests are used for this analysis due to their ensemble nature, which makes them naturally suited to gauge the consistency of misclassification. This consistency is here defined through the voting scheme of their base tree classifiers. Detailed consistency results for the random forest ensemble classification were obtained for all receptors and for all data transformations of their unaligned primary sequences. Shortlists of the most consistently misclassified receptors for each subfamily and transformation, as well as an overall shortlist including those cases that were consistently misclassified across transformations, were obtained. The latter should be referred to experts for further investigation as a data curation task. The automatic discrimination of the Class C sub-families of G protein-coupled receptors from their unaligned primary sequences shows clear limits. This study has

Linking genotypes database with locus-specific database and genotype-phenotype correlation in phenylketonuria.

Science.gov (United States)

Wettstein, Sarah; Underhaug, Jarl; Perez, Belen; Marsden, Brian D; Yue, Wyatt W; Martinez, Aurora; Blau, Nenad

2015-03-01

The wide range of metabolic phenotypes in phenylketonuria is due to a large number of variants causing variable impairment in phenylalanine hydroxylase function. A total of 834 phenylalanine hydroxylase gene variants from the locus-specific database PAHvdb and genotypes of 4181 phenylketonuria patients from the BIOPKU database were characterized using FoldX, SIFT Blink, Polyphen-2 and SNPs3D algorithms. Obtained data was correlated with residual enzyme activity, patients' phenotype and tetrahydrobiopterin responsiveness. A descriptive analysis of both databases was compiled and an interactive viewer in PAHvdb database was implemented for structure visualization of missense variants. We found a quantitative relationship between phenylalanine hydroxylase protein stability and enzyme activity (r(s) = 0.479), between protein stability and allelic phenotype (r(s) = -0.458), as well as between enzyme activity and allelic phenotype (r(s) = 0.799). Enzyme stability algorithms (FoldX and SNPs3D), allelic phenotype and enzyme activity were most powerful to predict patients' phenotype and tetrahydrobiopterin response. Phenotype prediction was most accurate in deleterious genotypes (≈ 100%), followed by homozygous (92.9%), hemizygous (94.8%), and compound heterozygous genotypes (77.9%), while tetrahydrobiopterin response was correctly predicted in 71.0% of all cases. To our knowledge this is the largest study using algorithms for the prediction of patients' phenotype and tetrahydrobiopterin responsiveness in phenylketonuria patients, using data from the locus-specific and genotypes database.

PAMDB: a comprehensive Pseudomonas aeruginosa metabolome database.

Science.gov (United States)

Huang, Weiliang; Brewer, Luke K; Jones, Jace W; Nguyen, Angela T; Marcu, Ana; Wishart, David S; Oglesby-Sherrouse, Amanda G; Kane, Maureen A; Wilks, Angela

2018-01-04

The Pseudomonas aeruginosaMetabolome Database (PAMDB, http://pseudomonas.umaryland.edu) is a searchable, richly annotated metabolite database specific to P. aeruginosa. P. aeruginosa is a soil organism and significant opportunistic pathogen that adapts to its environment through a versatile energy metabolism network. Furthermore, P. aeruginosa is a model organism for the study of biofilm formation, quorum sensing, and bioremediation processes, each of which are dependent on unique pathways and metabolites. The PAMDB is modelled on the Escherichia coli (ECMDB), yeast (YMDB) and human (HMDB) metabolome databases and contains >4370 metabolites and 938 pathways with links to over 1260 genes and proteins. The database information was compiled from electronic databases, journal articles and mass spectrometry (MS) metabolomic data obtained in our laboratories. For each metabolite entered, we provide detailed compound descriptions, names and synonyms, structural and physiochemical information, nuclear magnetic resonance (NMR) and MS spectra, enzymes and pathway information, as well as gene and protein sequences. The database allows extensive searching via chemical names, structure and molecular weight, together with gene, protein and pathway relationships. The PAMBD and its future iterations will provide a valuable resource to biologists, natural product chemists and clinicians in identifying active compounds, potential biomarkers and clinical diagnostics. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

The establishment of a database of Italian feeds for the Cornell Net Carbohydrate and Protein System

Directory of Open Access Journals (Sweden)

Enzo Tartari

2010-01-01

Full Text Available A field application of the Cornell Net Carbohydrate and Protein System (CNCPS in Italy has been limited because thefeed bank is based on North American feedstuffs and still few laboratories are able to analyze feeds as requested by theCNCPS. Moreover, the standardization of analytical procedures is still not homogeneous among laboratories. This workwas carried out to establish a first database for feeds commonly used in Italy, providing nutritionists and producers anaccurate and current feed composition, also indicating methods and apparatus for analytical procedures potentially availablefor routine analysis. A total of 909 samples of hays, silages and raw materials (protein feeds, cereals and by-productswere analyzed through 1999 and 2002; analysis included protein solubility and degradability, protein fractions,structural carbohydrate fractions and the calculation of neutral detergent structural carbohydrates. When possible, averagedata were compared with those included in the feed bank of CNCPS ver. 3 and with those obtained by another Italianlaboratory. The main differences were observed in chemical composition of forages and silages, whose composition largelydepends on environmental conditions and physiological stage; protein feeds, cereals and by-products showed somedifferences in crude protein, soluble protein and protein fractions even in feeds of national origin.The intent to modify the feed bank values of CNCPS for establishing an Italian data base of feeds will require a collaborativestudy of many laboratories not only for forages, hays and silages samples - whose composition is greatly dependenton environmental factors and agronomic techniques - but also for protein fractions, whose values are largely influencedby even small changes in analytical techniques.

LoopX: A Graphical User Interface-Based Database for Comprehensive Analysis and Comparative Evaluation of Loops from Protein Structures.

Science.gov (United States)

Kadumuri, Rajashekar Varma; Vadrevu, Ramakrishna

2017-10-01

Due to their crucial role in function, folding, and stability, protein loops are being targeted for grafting/designing to create novel or alter existing functionality and improve stability and foldability. With a view to facilitate a thorough analysis and effectual search options for extracting and comparing loops for sequence and structural compatibility, we developed, LoopX a comprehensively compiled library of sequence and conformational features of ∼700,000 loops from protein structures. The database equipped with a graphical user interface is empowered with diverse query tools and search algorithms, with various rendering options to visualize the sequence- and structural-level information along with hydrogen bonding patterns, backbone φ, ψ dihedral angles of both the target and candidate loops. Two new features (i) conservation of the polar/nonpolar environment and (ii) conservation of sequence and conformation of specific residues within the loops have also been incorporated in the search and retrieval of compatible loops for a chosen target loop. Thus, the LoopX server not only serves as a database and visualization tool for sequence and structural analysis of protein loops but also aids in extracting and comparing candidate loops for a given target loop based on user-defined search options.

CLIPZ: a database and analysis environment for experimentally determined binding sites of RNA-binding proteins.

Science.gov (United States)

Khorshid, Mohsen; Rodak, Christoph; Zavolan, Mihaela

2011-01-01

The stability, localization and translation rate of mRNAs are regulated by a multitude of RNA-binding proteins (RBPs) that find their targets directly or with the help of guide RNAs. Among the experimental methods for mapping RBP binding sites, cross-linking and immunoprecipitation (CLIP) coupled with deep sequencing provides transcriptome-wide coverage as well as high resolution. However, partly due to their vast volume, the data that were so far generated in CLIP experiments have not been put in a form that enables fast and interactive exploration of binding sites. To address this need, we have developed the CLIPZ database and analysis environment. Binding site data for RBPs such as Argonaute 1-4, Insulin-like growth factor II mRNA-binding protein 1-3, TNRC6 proteins A-C, Pumilio 2, Quaking and Polypyrimidine tract binding protein can be visualized at the level of the genome and of individual transcripts. Individual users can upload their own sequence data sets while being able to limit the access to these data to specific users, and analyses of the public and private data sets can be performed interactively. CLIPZ, available at http://www.clipz.unibas.ch, aims to provide an open access repository of information for post-transcriptional regulatory elements.

PDBTM: Protein Data Bank of transmembrane proteins after 8 years.

Science.gov (United States)

Kozma, Dániel; Simon, István; Tusnády, Gábor E

2013-01-01

The PDBTM database (available at http://pdbtm.enzim.hu), the first comprehensive and up-to-date transmembrane protein selection of the Protein Data Bank, was launched in 2004. The database was created and has been continuously updated by the TMDET algorithm that is able to distinguish between transmembrane and non-transmembrane proteins using their 3D atomic coordinates only. The TMDET algorithm can locate the spatial positions of transmembrane proteins in lipid bilayer as well. During the last 8 years not only the size of the PDBTM database has been steadily growing from ∼400 to 1700 entries but also new structural elements have been identified, in addition to the well-known α-helical bundle and β-barrel structures. Numerous 'exotic' transmembrane protein structures have been solved since the first release, which has made it necessary to define these new structural elements, such as membrane loops or interfacial helices in the database. This article reports the new features of the PDBTM database that have been added since its first release, and our current efforts to keep the database up-to-date and easy to use so that it may continue to serve as a fundamental resource for the scientific community.

Yeast Interacting Proteins Database: YDL239C, YLR423C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...cription Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing structure at the leading

Yeast Interacting Proteins Database: YDL239C, YPL070W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...cription Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing structure at the leading

Yeast Interacting Proteins Database: YDL239C, YML042W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...iption Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing structure at the leading

Yeast Interacting Proteins Database: YDL239C, YKL103C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...ait description Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing structure at the leading

The Universal Protein Resource (UniProt): an expanding universe of protein information.

Science.gov (United States)

Wu, Cathy H; Apweiler, Rolf; Bairoch, Amos; Natale, Darren A; Barker, Winona C; Boeckmann, Brigitte; Ferro, Serenella; Gasteiger, Elisabeth; Huang, Hongzhan; Lopez, Rodrigo; Magrane, Michele; Martin, Maria J; Mazumder, Raja; O'Donovan, Claire; Redaschi, Nicole; Suzek, Baris

2006-01-01

The Universal Protein Resource (UniProt) provides a central resource on protein sequences and functional annotation with three database components, each addressing a key need in protein bioinformatics. The UniProt Knowledgebase (UniProtKB), comprising the manually annotated UniProtKB/Swiss-Prot section and the automatically annotated UniProtKB/TrEMBL section, is the preeminent storehouse of protein annotation. The extensive cross-references, functional and feature annotations and literature-based evidence attribution enable scientists to analyse proteins and query across databases. The UniProt Reference Clusters (UniRef) speed similarity searches via sequence space compression by merging sequences that are 100% (UniRef100), 90% (UniRef90) or 50% (UniRef50) identical. Finally, the UniProt Archive (UniParc) stores all publicly available protein sequences, containing the history of sequence data with links to the source databases. UniProt databases continue to grow in size and in availability of information. Recent and upcoming changes to database contents, formats, controlled vocabularies and services are described. New download availability includes all major releases of UniProtKB, sequence collections by taxonomic division and complete proteomes. A bibliography mapping service has been added, and an ID mapping service will be available soon. UniProt databases can be accessed online at http://www.uniprot.org or downloaded at ftp://ftp.uniprot.org/pub/databases/.

SU-F-T-101: Insight into Dosimetry Workload and Planning Timelines: A 6 Year Review at One Institution

Energy Technology Data Exchange (ETDEWEB)

Cardan, R; Popple, R; Smith, H; Fiveash, J [The University of Alabama at Birmingham, Birmingham, AL (United States)

2016-06-15

Purpose: To elucidate realistic clinical treatment planning workload and timelines to improve understanding for patients, payers, and other institutions involved in radiotherapy processes. Methods: A web based tool was developed using Oracle Express (Oracle Corp, Redwood City, CA) which allowed communication between the physicians and staff about the current state of the patient plan. For 6 years, all patient courses were logged and time-stamped in 22 discreet steps which detailed start and stop times for simulation, contouring, and treatment planning tasks. This data was combined with the treatment planning database (TPDB) using the Eclipse Scripting API (Varian Medical Systems, Palo Alto, CA) to cross-identify plans between the two systems. This time data was analyzed across our dosimetry staff and treatment modality. Results: In 6 years, 110,477 patient statuses were time-logged for 9683 courses of treatment using our internal software. The courses contained 8305 unique patients who were binned into one of 11 diagnosis site categories. 8253 courses could be reconciled against the TPDB using timestamp data from patient statuses. The average planning volume per dosimetrist was 375.8 ± 142.4 plans per year with the average number of planning revisions per dosimetrist of 71.0 ± 27.1 plans per year. The median treatment planning times by modality ranged from to 48.3 hours for IMRT plans 5 fields or less to 119.6 hours for IMRT with 8 or more fields. Two arc VMAT, three arc VMAT, and 3D plans median times were 89.1 hours, 113.8 hours, and 50.9 hours respectively. Conclusion: Using our web based tool, we have demonstrated the ability to quantify treatment planning timelines and workloads which could help in setting appropriate expectations for patients, payers, and hospital administration. COI: Author received monies from Varian Medical Systems for research and teaching honorarium.

ContaMiner and ContaBase: a webserver and database for early identification of unwantedly crystallized protein contaminants

Science.gov (United States)

Hungler, Arnaud; Momin, Afaque; Diederichs, Kay; Arold, Stefan, T.

2016-01-01

Solving the phase problem in protein X-ray crystallography relies heavily on the identity of the crystallized protein, especially when molecular replacement (MR) methods are used. Yet, it is not uncommon that a contaminant crystallizes instead of the protein of interest. Such contaminants may be proteins from the expression host organism, protein fusion tags or proteins added during the purification steps. Many contaminants co-purify easily, crystallize and give good diffraction data. Identification of contaminant crystals may take time, since the presence of the contaminant is unexpected and its identity unknown. A webserver (ContaMiner) and a contaminant database (ContaBase) have been established, to allow fast MR-based screening of crystallographic data against currently 62 known contaminants. The web-based ContaMiner (available at http://strube.cbrc.kaust.edu.sa/contaminer/) currently produces results in 5 min to 4 h. The program is also available in a github repository and can be installed locally. ContaMiner enables screening of novel crystals at synchrotron beamlines, and it would be valuable as a routine safety check for ‘crystallization and preliminary X-ray analysis’ publications. Thus, in addition to potentially saving X-ray crystallographers much time and effort, ContaMiner might considerably lower the risk of publishing erroneous data. PMID:27980519

Generation of a predicted protein database from EST data and application to iTRAQ analyses in grape (Vitis vinifera cv. Cabernet Sauvignon berries at ripening initiation

Directory of Open Access Journals (Sweden)

Smith Derek

2009-01-01

Full Text Available Abstract Background iTRAQ is a proteomics technique that uses isobaric tags for relative and absolute quantitation of tryptic peptides. In proteomics experiments, the detection and high confidence annotation of proteins and the significance of corresponding expression differences can depend on the quality and the species specificity of the tryptic peptide map database used for analysis of the data. For species for which finished genome sequence data are not available, identification of proteins relies on similarity to proteins from other species using comprehensive peptide map databases such as the MSDB. Results We were interested in characterizing ripening initiation ('veraison' in grape berries at the protein level in order to better define the molecular control of this important process for grape growers and wine makers. We developed a bioinformatic pipeline for processing EST data in order to produce a predicted tryptic peptide database specifically targeted to the wine grape cultivar, Vitis vinifera cv. Cabernet Sauvignon, and lacking truncated N- and C-terminal fragments. By searching iTRAQ MS/MS data generated from berry exocarp and mesocarp samples at ripening initiation, we determined that implementation of the custom database afforded a large improvement in high confidence peptide annotation in comparison to the MSDB. We used iTRAQ MS/MS in conjunction with custom peptide db searches to quantitatively characterize several important pathway components for berry ripening previously described at the transcriptional level and confirmed expression patterns for these at the protein level. Conclusion We determined that a predicted peptide database for MS/MS applications can be derived from EST data using advanced clustering and trimming approaches and successfully implemented for quantitative proteome profiling. Quantitative shotgun proteome profiling holds great promise for characterizing biological processes such as fruit ripening

VerSeDa: vertebrate secretome database.

Science.gov (United States)

Cortazar, Ana R; Oguiza, José A; Aransay, Ana M; Lavín, José L

2017-01-01

Based on the current tools, de novo secretome (full set of proteins secreted by an organism) prediction is a time consuming bioinformatic task that requires a multifactorial analysis in order to obtain reliable in silico predictions. Hence, to accelerate this process and offer researchers a reliable repository where secretome information can be obtained for vertebrates and model organisms, we have developed VerSeDa (Vertebrate Secretome Database). This freely available database stores information about proteins that are predicted to be secreted through the classical and non-classical mechanisms, for the wide range of vertebrate species deposited at the NCBI, UCSC and ENSEMBL sites. To our knowledge, VerSeDa is the only state-of-the-art database designed to store secretome data from multiple vertebrate genomes, thus, saving an important amount of time spent in the prediction of protein features that can be retrieved from this repository directly. VerSeDa is freely available at http://genomics.cicbiogune.es/VerSeDa/index.php. © The Author(s) 2017. Published by Oxford University Press.

PhosphoBase: a database of phosphorylation sites

DEFF Research Database (Denmark)

Blom, Nikolaj; Kreegipuu, Andres; Brunak, Søren

1998-01-01

PhosphoBase is a database of experimentally verified phosphorylation sites. Version 1.0 contains 156 entries and 398 experimentally determined phosphorylation sites. Entries are compiled and revised from the literature and from major protein sequence databases such as SwissProt and PIR. The entries...... provide information about the phosphoprotein and the exact position of its phosphorylation sites. Furthermore, part of the entries contain information about kinetic data obtained from enzyme assays on specific peptides. To illustrate the use of data extracted from PhosphoBase we present a sequence logo...... displaying the overall conservation of positions around serines phosphorylated by protein kinase A (PKA). PhosphoBase is available on the WWW at http://www.cbs.dtu.dk/databases/PhosphoBase/....

BioWarehouse: a bioinformatics database warehouse toolkit.

Science.gov (United States)

Lee, Thomas J; Pouliot, Yannick; Wagner, Valerie; Gupta, Priyanka; Stringer-Calvert, David W J; Tenenbaum, Jessica D; Karp, Peter D

2006-03-23

This article addresses the problem of interoperation of heterogeneous bioinformatics databases. We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. BioWarehouse embodies significant progress on the database integration problem for bioinformatics.

Database Constraints Applied to Metabolic Pathway Reconstruction Tools

Directory of Open Access Journals (Sweden)

Jordi Vilaplana

2014-01-01

Full Text Available Our group developed two biological applications, Biblio-MetReS and Homol-MetReS, accessing the same database of organisms with annotated genes. Biblio-MetReS is a data-mining application that facilitates the reconstruction of molecular networks based on automated text-mining analysis of published scientific literature. Homol-MetReS allows functional (reannotation of proteomes, to properly identify both the individual proteins involved in the process(es of interest and their function. It also enables the sets of proteins involved in the process(es in different organisms to be compared directly. The efficiency of these biological applications is directly related to the design of the shared database. We classified and analyzed the different kinds of access to the database. Based on this study, we tried to adjust and tune the configurable parameters of the database server to reach the best performance of the communication data link to/from the database system. Different database technologies were analyzed. We started the study with a public relational SQL database, MySQL. Then, the same database was implemented by a MapReduce-based database named HBase. The results indicated that the standard configuration of MySQL gives an acceptable performance for low or medium size databases. Nevertheless, tuning database parameters can greatly improve the performance and lead to very competitive runtimes.

Database constraints applied to metabolic pathway reconstruction tools.

Science.gov (United States)

Vilaplana, Jordi; Solsona, Francesc; Teixido, Ivan; Usié, Anabel; Karathia, Hiren; Alves, Rui; Mateo, Jordi

2014-01-01

Our group developed two biological applications, Biblio-MetReS and Homol-MetReS, accessing the same database of organisms with annotated genes. Biblio-MetReS is a data-mining application that facilitates the reconstruction of molecular networks based on automated text-mining analysis of published scientific literature. Homol-MetReS allows functional (re)annotation of proteomes, to properly identify both the individual proteins involved in the process(es) of interest and their function. It also enables the sets of proteins involved in the process(es) in different organisms to be compared directly. The efficiency of these biological applications is directly related to the design of the shared database. We classified and analyzed the different kinds of access to the database. Based on this study, we tried to adjust and tune the configurable parameters of the database server to reach the best performance of the communication data link to/from the database system. Different database technologies were analyzed. We started the study with a public relational SQL database, MySQL. Then, the same database was implemented by a MapReduce-based database named HBase. The results indicated that the standard configuration of MySQL gives an acceptable performance for low or medium size databases. Nevertheless, tuning database parameters can greatly improve the performance and lead to very competitive runtimes.

Access to DNA and protein databases on the Internet.

Science.gov (United States)

Harper, R

1994-02-01

During the past year, the number of biological databases that can be queried via Internet has dramatically increased. This increase has resulted from the introduction of networking tools, such as Gopher and WAIS, that make it easy for research workers to index databases and make them available for on-line browsing. Biocomputing in the nineties will see the advent of more client/server options for the solution of problems in bioinformatics.

Yeast Interacting Proteins Database: YDR176W, YDL239C [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle pole...ining structure at the leading edge of the prospore membrane via interaction with spindle pole body componen...DY3 Prey description Protein required for spore wall formation, thought to mediate assembly of a Don1p-conta

HCVpro: Hepatitis C virus protein interaction database

KAUST Repository

Kwofie, Samuel K.; Schaefer, Ulf; Sundararajan, Vijayaraghava Seshadri; Bajic, Vladimir B.; Christoffels, Alan G.

2011-01-01

It is essential to catalog characterized hepatitis C virus (HCV) protein-protein interaction (PPI) data and the associated plethora of vital functional information to augment the search for therapies, vaccines and diagnostic biomarkers

ProFITS of maize: a database of protein families involved in the transduction of signalling in the maize genome

Directory of Open Access Journals (Sweden)

Zhang Zhenhai

2010-10-01

Full Text Available Abstract Background Maize (Zea mays ssp. mays L. is an important model for plant basic and applied research. In 2009, the B73 maize genome sequencing made a great step forward, using clone by clone strategy; however, functional annotation and gene classification of the maize genome are still limited. Thus, a well-annotated datasets and informative database will be important for further research discoveries. Signal transduction is a fundamental biological process in living cells, and many protein families participate in this process in sensing, amplifying and responding to various extracellular or internal stimuli. Therefore, it is a good starting point to integrate information on the maize functional genes involved in signal transduction. Results Here we introduce a comprehensive database 'ProFITS' (Protein Families Involved in the Transduction of Signalling, which endeavours to identify and classify protein kinases/phosphatases, transcription factors and ubiquitin-proteasome-system related genes in the B73 maize genome. Users can explore gene models, corresponding transcripts and FLcDNAs using the three abovementioned protein hierarchical categories, and visualize them using an AJAX-based genome browser (JBrowse or Generic Genome Browser (GBrowse. Functional annotations such as GO annotation, protein signatures, protein best-hits in the Arabidopsis and rice genome are provided. In addition, pre-calculated transcription factor binding sites of each gene are generated and mutant information is incorporated into ProFITS. In short, ProFITS provides a user-friendly web interface for studies in signal transduction process in maize. Conclusion ProFITS, which utilizes both the B73 maize genome and full length cDNA (FLcDNA datasets, provides users a comprehensive platform of maize annotation with specific focus on the categorization of families involved in the signal transduction process. ProFITS is designed as a user-friendly web interface and it is

BioWarehouse: a bioinformatics database warehouse toolkit

Directory of Open Access Journals (Sweden)

Stringer-Calvert David WJ

2006-03-01

Full Text Available Abstract Background This article addresses the problem of interoperation of heterogeneous bioinformatics databases. Results We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. Conclusion BioWarehouse embodies significant progress on the

An ontology-based search engine for protein-protein interactions.

Science.gov (United States)

Park, Byungkyu; Han, Kyungsook

2010-01-18

Keyword matching or ID matching is the most common searching method in a large database of protein-protein interactions. They are purely syntactic methods, and retrieve the records in the database that contain a keyword or ID specified in a query. Such syntactic search methods often retrieve too few search results or no results despite many potential matches present in the database. We have developed a new method for representing protein-protein interactions and the Gene Ontology (GO) using modified Gödel numbers. This representation is hidden from users but enables a search engine using the representation to efficiently search protein-protein interactions in a biologically meaningful way. Given a query protein with optional search conditions expressed in one or more GO terms, the search engine finds all the interaction partners of the query protein by unique prime factorization of the modified Gödel numbers representing the query protein and the search conditions. Representing the biological relations of proteins and their GO annotations by modified Gödel numbers makes a search engine efficiently find all protein-protein interactions by prime factorization of the numbers. Keyword matching or ID matching search methods often miss the interactions involving a protein that has no explicit annotations matching the search condition, but our search engine retrieves such interactions as well if they satisfy the search condition with a more specific term in the ontology.

Follicle Online: an integrated database of follicle assembly, development and ovulation.

Science.gov (United States)

Hua, Juan; Xu, Bo; Yang, Yifan; Ban, Rongjun; Iqbal, Furhan; Cooke, Howard J; Zhang, Yuanwei; Shi, Qinghua

2015-01-01

Folliculogenesis is an important part of ovarian function as it provides the oocytes for female reproductive life. Characterizing genes/proteins involved in folliculogenesis is fundamental for understanding the mechanisms associated with this biological function and to cure the diseases associated with folliculogenesis. A large number of genes/proteins associated with folliculogenesis have been identified from different species. However, no dedicated public resource is currently available for folliculogenesis-related genes/proteins that are validated by experiments. Here, we are reporting a database 'Follicle Online' that provides the experimentally validated gene/protein map of the folliculogenesis in a number of species. Follicle Online is a web-based database system for storing and retrieving folliculogenesis-related experimental data. It provides detailed information for 580 genes/proteins (from 23 model organisms, including Homo sapiens, Mus musculus, Rattus norvegicus, Mesocricetus auratus, Bos Taurus, Drosophila and Xenopus laevis) that have been reported to be involved in folliculogenesis, POF (premature ovarian failure) and PCOS (polycystic ovary syndrome). The literature was manually curated from more than 43,000 published articles (till 1 March 2014). The Follicle Online database is implemented in PHP + MySQL + JavaScript and this user-friendly web application provides access to the stored data. In summary, we have developed a centralized database that provides users with comprehensive information about genes/proteins involved in folliculogenesis. This database can be accessed freely and all the stored data can be viewed without any registration. Database URL: http://mcg.ustc.edu.cn/sdap1/follicle/index.php © The Author(s) 2015. Published by Oxford University Press.

Database Search Engines: Paradigms, Challenges and Solutions.

Science.gov (United States)

Verheggen, Kenneth; Martens, Lennart; Berven, Frode S; Barsnes, Harald; Vaudel, Marc

2016-01-01

The first step in identifying proteins from mass spectrometry based shotgun proteomics data is to infer peptides from tandem mass spectra, a task generally achieved using database search engines. In this chapter, the basic principles of database search engines are introduced with a focus on open source software, and the use of database search engines is demonstrated using the freely available SearchGUI interface. This chapter also discusses how to tackle general issues related to sequence database searching and shows how to minimize their impact.

ProteinWorldDB: querying radical pairwise alignments among protein sets from complete genomes.

Science.gov (United States)

Otto, Thomas Dan; Catanho, Marcos; Tristão, Cristian; Bezerra, Márcia; Fernandes, Renan Mathias; Elias, Guilherme Steinberger; Scaglia, Alexandre Capeletto; Bovermann, Bill; Berstis, Viktors; Lifschitz, Sergio; de Miranda, Antonio Basílio; Degrave, Wim

2010-03-01

Many analyses in modern biological research are based on comparisons between biological sequences, resulting in functional, evolutionary and structural inferences. When large numbers of sequences are compared, heuristics are often used resulting in a certain lack of accuracy. In order to improve and validate results of such comparisons, we have performed radical all-against-all comparisons of 4 million protein sequences belonging to the RefSeq database, using an implementation of the Smith-Waterman algorithm. This extremely intensive computational approach was made possible with the help of World Community Grid, through the Genome Comparison Project. The resulting database, ProteinWorldDB, which contains coordinates of pairwise protein alignments and their respective scores, is now made available. Users can download, compare and analyze the results, filtered by genomes, protein functions or clusters. ProteinWorldDB is integrated with annotations derived from Swiss-Prot, Pfam, KEGG, NCBI Taxonomy database and gene ontology. The database is a unique and valuable asset, representing a major effort to create a reliable and consistent dataset of cross-comparisons of the whole protein content encoded in hundreds of completely sequenced genomes using a rigorous dynamic programming approach. The database can be accessed through http://proteinworlddb.org

Human Variome Project Quality Assessment Criteria for Variation Databases.

Science.gov (United States)

Vihinen, Mauno; Hancock, John M; Maglott, Donna R; Landrum, Melissa J; Schaafsma, Gerard C P; Taschner, Peter

2016-06-01

Numerous databases containing information about DNA, RNA, and protein variations are available. Gene-specific variant databases (locus-specific variation databases, LSDBs) are typically curated and maintained for single genes or groups of genes for a certain disease(s). These databases are widely considered as the most reliable information source for a particular gene/protein/disease, but it should also be made clear they may have widely varying contents, infrastructure, and quality. Quality is very important to evaluate because these databases may affect health decision-making, research, and clinical practice. The Human Variome Project (HVP) established a Working Group for Variant Database Quality Assessment. The basic principle was to develop a simple system that nevertheless provides a good overview of the quality of a database. The HVP quality evaluation criteria that resulted are divided into four main components: data quality, technical quality, accessibility, and timeliness. This report elaborates on the developed quality criteria and how implementation of the quality scheme can be achieved. Examples are provided for the current status of the quality items in two different databases, BTKbase, an LSDB, and ClinVar, a central archive of submissions about variants and their clinical significance. © 2016 WILEY PERIODICALS, INC.

CUDASW++2.0: enhanced Smith-Waterman protein database search on CUDA-enabled GPUs based on SIMT and virtualized SIMD abstractions

Directory of Open Access Journals (Sweden)

Schmidt Bertil

2010-04-01

Full Text Available Abstract Background Due to its high sensitivity, the Smith-Waterman algorithm is widely used for biological database searches. Unfortunately, the quadratic time complexity of this algorithm makes it highly time-consuming. The exponential growth of biological databases further deteriorates the situation. To accelerate this algorithm, many efforts have been made to develop techniques in high performance architectures, especially the recently emerging many-core architectures and their associated programming models. Findings This paper describes the latest release of the CUDASW++ software, CUDASW++ 2.0, which makes new contributions to Smith-Waterman protein database searches using compute unified device architecture (CUDA. A parallel Smith-Waterman algorithm is proposed to further optimize the performance of CUDASW++ 1.0 based on the single instruction, multiple thread (SIMT abstraction. For the first time, we have investigated a partitioned vectorized Smith-Waterman algorithm using CUDA based on the virtualized single instruction, multiple data (SIMD abstraction. The optimized SIMT and the partitioned vectorized algorithms were benchmarked, and remarkably, have similar performance characteristics. CUDASW++ 2.0 achieves performance improvement over CUDASW++ 1.0 as much as 1.74 (1.72 times using the optimized SIMT algorithm and up to 1.77 (1.66 times using the partitioned vectorized algorithm, with a performance of up to 17 (30 billion cells update per second (GCUPS on a single-GPU GeForce GTX 280 (dual-GPU GeForce GTX 295 graphics card. Conclusions CUDASW++ 2.0 is publicly available open-source software, written in CUDA and C++ programming languages. It obtains significant performance improvement over CUDASW++ 1.0 using either the optimized SIMT algorithm or the partitioned vectorized algorithm for Smith-Waterman protein database searches by fully exploiting the compute capability of commonly used CUDA-enabled low-cost GPUs.

PrionScan: an online database of predicted prion domains in complete proteomes.

Science.gov (United States)

Espinosa Angarica, Vladimir; Angulo, Alfonso; Giner, Arturo; Losilla, Guillermo; Ventura, Salvador; Sancho, Javier

2014-02-05

Prions are a particular type of amyloids related to a large variety of important processes in cells, but also responsible for serious diseases in mammals and humans. The number of experimentally characterized prions is still low and corresponds to a handful of examples in microorganisms and mammals. Prion aggregation is mediated by specific protein domains with a remarkable compositional bias towards glutamine/asparagine and against charged residues and prolines. These compositional features have been used to predict new prion proteins in the genomes of different organisms. Despite these efforts, there are only a few available data sources containing prion predictions at a genomic scale. Here we present PrionScan, a new database of predicted prion-like domains in complete proteomes. We have previously developed a predictive methodology to identify and score prionogenic stretches in protein sequences. In the present work, we exploit this approach to scan all the protein sequences in public databases and compile a repository containing relevant information of proteins bearing prion-like domains. The database is updated regularly alongside UniprotKB and in its present version contains approximately 28000 predictions in proteins from different functional categories in more than 3200 organisms from all the taxonomic subdivisions. PrionScan can be used in two different ways: database query and analysis of protein sequences submitted by the users. In the first mode, simple queries allow to retrieve a detailed description of the properties of a defined protein. Queries can also be combined to generate more complex and specific searching patterns. In the second mode, users can submit and analyze their own sequences. It is expected that this database would provide relevant insights on prion functions and regulation from a genome-wide perspective, allowing researches performing cross-species prion biology studies. Our database might also be useful for guiding experimentalists

A comprehensive two-dimensional gel protein database of noncultured unfractionated normal human epidermal keratinocytes: towards an integrated approach to the study of cell proliferation, differentiation and skin diseases

DEFF Research Database (Denmark)

Celis, J E; Madsen, Peder; Rasmussen, H H

1991-01-01

A two-dimensional (2-D) gel database of cellular proteins from noncultured, unfractionated normal human epidermal keratinocytes has been established. A total of 2651 [35S]methionine-labeled cellular proteins (1868 isoelectric focusing, 783 nonequilibrium pH gradient electrophoresis) were resolved...

Yeast Interacting Proteins Database: YOL069W, YIL144W [Yeast Interacting Proteins Database

Lifescience Database Archive (English)

Full Text Available complex (Ndc80p-Nuf2p-Spc24p-Spc25p); involved in chromosome segregation, spindle checkpoint activity and kinetochore clustering...vity, kinetochore assembly and clustering Rows with this prey as prey (2) Rows with this prey as bait (0) 12...-Nuf2p-Spc24p-Spc25p); involved in chromosome segregation, spindle checkpoint activity and kinetochore clustering...d coiled-coil protein involved in chromosome segregation, spindle checkpoint activity, kinetochore assembly and clustering

BIOPEP database and other programs for processing bioactive peptide sequences.

Science.gov (United States)

Minkiewicz, Piotr; Dziuba, Jerzy; Iwaniak, Anna; Dziuba, Marta; Darewicz, Małgorzata

2008-01-01

This review presents the potential for application of computational tools in peptide science based on a sample BIOPEP database and program as well as other programs and databases available via the World Wide Web. The BIOPEP application contains a database of biologically active peptide sequences and a program enabling construction of profiles of the potential biological activity of protein fragments, calculation of quantitative descriptors as measures of the value of proteins as potential precursors of bioactive peptides, and prediction of bonds susceptible to hydrolysis by endopeptidases in a protein chain. Other bioactive and allergenic peptide sequence databases are also presented. Programs enabling the construction of binary and multiple alignments between peptide sequences, the construction of sequence motifs attributed to a given type of bioactivity, searching for potential precursors of bioactive peptides, and the prediction of sites susceptible to proteolytic cleavage in protein chains are available via the Internet as are other approaches concerning secondary structure prediction and calculation of physicochemical features based on amino acid sequence. Programs for prediction of allergenic and toxic properties have also been developed. This review explores the possibilities of cooperation between various programs.

Cα and Cβ Carbon-13 Chemical Shifts in Proteins From an Empirical Database

International Nuclear Information System (INIS)

Iwadate, Mitsuo; Asakura, Tetsuo; Williamson, Michael P.

1999-01-01

We have constructed an extensive database of 13C Cα and Cβ chemical shifts in proteins of solution, for proteins of which a high-resolution crystal structure exists, and for which the crystal structure has been shown to be essentially identical to the solution structure. There is no systematic effect of temperature, reference compound, or pH on reported shifts, but there appear to be differences in reported shifts arising from referencing differences of up to 4.2 ppm. The major factor affecting chemical shifts is the backbone geometry, which causes differences of ca. 4 ppm between typical α- helix and β-sheet geometries for Cα, and of ca. 2 ppm for Cβ. The side-chain dihedral angle χ1 has an effect of up to 0.5 ppm on the Cα shift, particularly for amino acids with branched side-chains at Cβ. Hydrogen bonding to main-chain atoms has an effect of up to 0.9 ppm, which depends on the main- chain conformation. The sequence of the protein and ring-current shifts from aromatic rings have an insignificant effect (except for residues following proline). There are significant differences between different amino acid types in the backbone geometry dependence; the amino acids can be grouped together into five different groups with different φ,ψ shielding surfaces. The overall fit of individual residues to a single non-residue-specific surface, incorporating the effects of hydrogen bonding and χ1 angle, is 0.96 ppm for both Cα and Cβ. The results from this study are broadly similar to those from ab initio studies, but there are some differences which could merit further attention

ChemProt: a disease chemical biology database

DEFF Research Database (Denmark)

Taboureau, Olivier; Nielsen, Sonny Kim; Audouze, Karine Marie Laure

2011-01-01

Systems pharmacology is an emergent area that studies drug action across multiple scales of complexity, from molecular and cellular to tissue and organism levels. There is a critical need to develop network-based approaches to integrate the growing body of chemical biology knowledge with network...... biology. Here, we report ChemProt, a disease chemical biology database, which is based on a compilation of multiple chemical-protein annotation resources, as well as disease-associated protein-protein interactions (PPIs). We assembled more than 700 000 unique chemicals with biological annotation for 30...... evaluation of environmental chemicals, natural products and approved drugs, as well as the selection of new compounds based on their activity profile against most known biological targets, including those related to adverse drug events. Results from the disease chemical biology database associate citalopram...

Expanded microbial genome coverage and improved protein family annotation in the COG database.

Science.gov (United States)

Galperin, Michael Y; Makarova, Kira S; Wolf, Yuri I; Koonin, Eugene V

2015-01-01

Microbial genome sequencing projects produce numerous sequences of deduced proteins, only a small fraction of which have been or will ever be studied experimentally. This leaves sequence analysis as the only feasible way to annotate these proteins and assign to them tentative functions. The Clusters of Orthologous Groups of proteins (COGs) database (http://www.ncbi.nlm.nih.gov/COG/), first created in 1997, has been a popular tool for functional annotation. Its success was largely based on (i) its reliance on complete microbial genomes, which allowed reliable assignment of orthologs and paralogs for most genes; (ii) orthology-based approach, which used the function(s) of the characterized member(s) of the protein family (COG) to assign function(s) to the entire set of carefully identified orthologs and describe the range of potential functions when there were more than one; and (iii) careful manual curation of the annotation of the COGs, aimed at detailed prediction of the biological function(s) for each COG while avoiding annotation errors and overprediction. Here we present an update of the COGs, the first since 2003, and a comprehensive revision of the COG annotations and expansion of the genome coverage to include representative complete genomes from all bacterial and archaeal lineages down to the genus level. This re-analysis of the COGs shows that the original COG assignments had an error rate below 0.5% and allows an assessment of the progress in functional genomics in the past 12 years. During this time, functions of many previously uncharacterized COGs have been elucidated and tentative functional assignments of many COGs have been validated, either by targeted experiments or through the use of high-throughput methods. A particularly important development is the assignment of functions to several widespread, conserved proteins many of which turned out to participate in translation, in particular rRNA maturation and tRNA modification. The new version of the

UbSRD: The Ubiquitin Structural Relational Database.

Science.gov (United States)

Harrison, Joseph S; Jacobs, Tim M; Houlihan, Kevin; Van Doorslaer, Koenraad; Kuhlman, Brian

2016-02-22

The structurally defined ubiquitin-like homology fold (UBL) can engage in several unique protein-protein interactions and many of these complexes have been characterized with high-resolution techniques. Using Rosetta's structural classification tools, we have created the Ubiquitin Structural Relational Database (UbSRD), an SQL database of features for all 509 UBL-containing structures in the PDB, allowing users to browse these structures by protein-protein interaction and providing a platform for quantitative analysis of structural features. We used UbSRD to define the recognition features of ubiquitin (UBQ) and SUMO observed in the PDB and the orientation of the UBQ tail while interacting with certain types of proteins. While some of the interaction surfaces on UBQ and SUMO overlap, each molecule has distinct features that aid in molecular discrimination. Additionally, we find that the UBQ tail is malleable and can adopt a variety of conformations upon binding. UbSRD is accessible as an online resource at rosettadesign.med.unc.edu/ubsrd. Copyright © 2015 Elsevier Ltd. All rights reserved.

MiCroKit 3.0: an integrated database of midbody, centrosome and kinetochore.

Science.gov (United States)

Ren, Jian; Liu, Zexian; Gao, Xinjiao; Jin, Changjiang; Ye, Mingliang; Zou, Hanfa; Wen, Longping; Zhang, Zhaolei; Xue, Yu; Yao, Xuebiao

2010-01-01

During cell division/mitosis, a specific subset of proteins is spatially and temporally assembled into protein super complexes in three distinct regions, i.e. centrosome/spindle pole, kinetochore/centromere and midbody/cleavage furrow/phragmoplast/bud neck, and modulates cell division process faithfully. Although many experimental efforts have been carried out to investigate the characteristics of these proteins, no integrated database was available. Here, we present the MiCroKit database (http://microkit.biocuckoo.org) of proteins that localize in midbody, centrosome and/or kinetochore. We collected into the MiCroKit database experimentally verified microkit proteins from the scientific literature that have unambiguous supportive evidence for subcellular localization under fluorescent microscope. The current version of MiCroKit 3.0 provides detailed information for 1489 microkit proteins from seven model organisms, including Saccharomyces cerevisiae, Schizasaccharomyces pombe, Caenorhabditis elegans, Drosophila melanogaster, Xenopus laevis, Mus musculus and Homo sapiens. Moreover, the orthologous information was provided for these microkit proteins, and could be a useful resource for further experimental identification. The online service of MiCroKit database was implemented in PHP + MySQL + JavaScript, while the local packages were developed in JAVA 1.5 (J2SE 5.0).

HippDB: a database of readily targeted helical protein-protein interactions.

Science.gov (United States)

Bergey, Christina M; Watkins, Andrew M; Arora, Paramjit S

2013-11-01

HippDB catalogs every protein-protein interaction whose structure is available in the Protein Data Bank and which exhibits one or more helices at the interface. The Web site accepts queries on variables such as helix length and sequence, and it provides computational alanine scanning and change in solvent-accessible surface area values for every interfacial residue. HippDB is intended to serve as a starting point for structure-based small molecule and peptidomimetic drug development. HippDB is freely available on the web at http://www.nyu.edu/projects/arora/hippdb. The Web site is implemented in PHP, MySQL and Apache. Source code freely available for download at http://code.google.com/p/helidb, implemented in Perl and supported on Linux. arora@nyu.edu.

MIPS: analysis and annotation of proteins from whole genomes.

Science.gov (United States)

Mewes, H W; Amid, C; Arnold, R; Frishman, D; Güldener, U; Mannhaupt, G; Münsterkötter, M; Pagel, P; Strack, N; Stümpflen, V; Warfsmann, J; Ruepp, A

2004-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF), Neuherberg, Germany, provides protein sequence-related information based on whole-genome analysis. The main focus of the work is directed toward the systematic organization of sequence-related attributes as gathered by a variety of algorithms, primary information from experimental data together with information compiled from the scientific literature. MIPS maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the database of complete cDNAs (German Human Genome Project, NGFN), the database of mammalian protein-protein interactions (MPPI), the database of FASTA homologies (SIMAP), and the interface for the fast retrieval of protein-associated information (QUIPOS). The Arabidopsis thaliana database, the rice database, the plant EST databases (MATDB, MOsDB, SPUTNIK), as well as the databases for the comprehensive set of genomes (PEDANT genomes) are described elsewhere in the 2003 and 2004 NAR database issues, respectively. All databases described, and the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de).

GMDD: a database of GMO detection methods.

Science.gov (United States)

Dong, Wei; Yang, Litao; Shen, Kailin; Kim, Banghyun; Kleter, Gijs A; Marvin, Hans J P; Guo, Rong; Liang, Wanqi; Zhang, Dabing

2008-06-04

Since more than one hundred events of genetically modified organisms (GMOs) have been developed and approved for commercialization in global area, the GMO analysis methods are essential for the enforcement of GMO labelling regulations. Protein and nucleic acid-based detection techniques have been developed and utilized for GMOs identification and quantification. However, the information for harmonization and standardization of GMO analysis methods at global level is needed. GMO Detection method Database (GMDD) has collected almost all the previous developed and reported GMOs detection methods, which have been grouped by different strategies (screen-, gene-, construct-, and event-specific), and also provide a user-friendly search service of the detection methods by GMO event name, exogenous gene, or protein information, etc. In this database, users can obtain the sequences of exogenous integration, which will facilitate PCR primers and probes design. Also the information on endogenous genes, certified reference materials, reference molecules, and the validation status of developed methods is included in this database. Furthermore, registered users can also submit new detection methods and sequences to this database, and the newly submitted information will be released soon after being checked. GMDD contains comprehensive information of GMO detection methods. The database will make the GMOs analysis much easier.

Annotation error in public databases: misannotation of molecular function in enzyme superfamilies.

Directory of Open Access Journals (Sweden)

Alexandra M Schnoes

2009-12-01

Full Text Available Due to the rapid release of new data from genome sequencing projects, the majority of protein sequences in public databases have not been experimentally characterized; rather, sequences are annotated using computational analysis. The level of misannotation and the types of misannotation in large public databases are currently unknown and have not been analyzed in depth. We have investigated the misannotation levels for molecular function in four public protein sequence databases (UniProtKB/Swiss-Prot, GenBank NR, UniProtKB/TrEMBL, and KEGG for a model set of 37 enzyme families for which extensive experimental information is available. The manually curated database Swiss-Prot shows the lowest annotation error levels (close to 0% for most families; the two other protein sequence databases (GenBank NR and TrEMBL and the protein sequences in the KEGG pathways database exhibit similar and surprisingly high levels of misannotation that average 5%-63% across the six superfamilies studied. For 10 of the 37 families examined, the level of misannotation in one or more of these databases is >80%. Examination of the NR database over time shows that misannotation has increased from 1993 to 2005. The types of misannotation that were found fall into several categories, most associated with "overprediction" of molecular function. These results suggest that misannotation in enzyme superfamilies containing multiple families that catalyze different reactions is a larger problem than has been recognized. Strategies are suggested for addressing some of the systematic problems contributing to these high levels of misannotation.

Annotation error in public databases: misannotation of molecular function in enzyme superfamilies.

Science.gov (United States)

Schnoes, Alexandra M; Brown, Shoshana D; Dodevski, Igor; Babbitt, Patricia C

2009-12-01

Due to the rapid release of new data from genome sequencing projects, the majority of protein sequences in public databases have not been experimentally characterized; rather, sequences are annotated using computational analysis. The level of misannotation and the types of misannotation in large public databases are currently unknown and have not been analyzed in depth. We have investigated the misannotation levels for molecular function in four public protein sequence databases (UniProtKB/Swiss-Prot, GenBank NR, UniProtKB/TrEMBL, and KEGG) for a model set of 37 enzyme families for which extensive experimental information is available. The manually curated database Swiss-Prot shows the lowest annotation error levels (close to 0% for most families); the two other protein sequence databases (GenBank NR and TrEMBL) and the protein sequences in the KEGG pathways database exhibit similar and surprisingly high levels of misannotation that average 5%-63% across the six superfamilies studied. For 10 of the 37 families examined, the level of misannotation in one or more of these databases is >80%. Examination of the NR database over time shows that misannotation has increased from 1993 to 2005. The types of misannotation that were found fall into several categories, most associated with "overprediction" of molecular function. These results suggest that misannotation in enzyme superfamilies containing multiple families that catalyze different reactions is a larger problem than has been recognized. Strategies are suggested for addressing some of the systematic problems contributing to these high levels of misannotation.

Efficient Disk-Based Techniques for Manipulating Very Large String Databases

KAUST Repository

Allam, Amin

2017-01-01

Indexing and processing strings are very important topics in database management. Strings can be database records, DNA sequences, protein sequences, or plain text. Various string operations are required for several application categories

Medicago truncatula transporter database: a comprehensive database resource for M. truncatula transporters

Directory of Open Access Journals (Sweden)

Miao Zhenyan

2012-02-01

Full Text Available Abstract Background Medicago truncatula has been chosen as a model species for genomic studies. It is closely related to an important legume, alfalfa. Transporters are a large group of membrane-spanning proteins. They deliver essential nutrients, eject waste products, and assist the cell in sensing environmental conditions by forming a complex system of pumps and channels. Although studies have effectively characterized individual M. truncatula transporters in several databases, until now there has been no available systematic database that includes all transporters in M. truncatula. Description The M. truncatula transporter database (MTDB contains comprehensive information on the transporters in M. truncatula. Based on the TransportTP method, we have presented a novel prediction pipeline. A total of 3,665 putative transporters have been annotated based on International Medicago Genome Annotated Group (IMGAG V3.5 V3 and the M. truncatula Gene Index (MTGI V10.0 releases and assigned to 162 families according to the transporter classification system. These families were further classified into seven types according to their transport mode and energy coupling mechanism. Extensive annotations referring to each protein were generated, including basic protein function, expressed sequence tag (EST mapping, genome locus, three-dimensional template prediction, transmembrane segment, and domain annotation. A chromosome distribution map and text-based Basic Local Alignment Search Tools were also created. In addition, we have provided a way to explore the expression of putative M. truncatula transporter genes under stress treatments. Conclusions In summary, the MTDB enables the exploration and comparative analysis of putative transporters in M. truncatula. A user-friendly web interface and regular updates make MTDB valuable to researchers in related fields. The MTDB is freely available now to all users at http://bioinformatics.cau.edu.cn/MtTransporter/.

MIPS: curated databases and comprehensive secondary data resources in 2010.

Science.gov (United States)

Mewes, H Werner; Ruepp, Andreas; Theis, Fabian; Rattei, Thomas; Walter, Mathias; Frishman, Dmitrij; Suhre, Karsten; Spannagl, Manuel; Mayer, Klaus F X; Stümpflen, Volker; Antonov, Alexey

2011-01-01

The Munich Information Center for Protein Sequences (MIPS at the Helmholtz Center for Environmental Health, Neuherberg, Germany) has many years of experience in providing annotated collections of biological data. Selected data sets of high relevance, such as model genomes, are subjected to careful manual curation, while the bulk of high-throughput data is annotated by automatic means. High-quality reference resources developed in the past and still actively maintained include Saccharomyces cerevisiae, Neurospora crassa and Arabidopsis thaliana genome databases as well as several protein interaction data sets (MPACT, MPPI and CORUM). More recent projects are PhenomiR, the database on microRNA-related phenotypes, and MIPS PlantsDB for integrative and comparative plant genome research. The interlinked resources SIMAP and PEDANT provide homology relationships as well as up-to-date and consistent annotation for 38,000,000 protein sequences. PPLIPS and CCancer are versatile tools for proteomics and functional genomics interfacing to a database of compilations from gene lists extracted from literature. A novel literature-mining tool, EXCERBT, gives access to structured information on classified relations between genes, proteins, phenotypes and diseases extracted from Medline abstracts by semantic analysis. All databases described here, as well as the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.helmholtz-muenchen.de).

Expediting topology data gathering for the TOPDB database.

Science.gov (United States)

Dobson, László; Langó, Tamás; Reményi, István; Tusnády, Gábor E

2015-01-01

The Topology Data Bank of Transmembrane Proteins (TOPDB, http://topdb.enzim.ttk.mta.hu) contains experimentally determined topology data of transmembrane proteins. Recently, we have updated TOPDB from several sources and utilized a newly developed topology prediction algorithm to determine the most reliable topology using the results of experiments as constraints. In addition to collecting the experimentally determined topology data published in the last couple of years, we gathered topographies defined by the TMDET algorithm using 3D structures from the PDBTM. Results of global topology analysis of various organisms as well as topology data generated by high throughput techniques, like the sequential positions of N- or O-glycosylations were incorporated into the TOPDB database. Moreover, a new algorithm was developed to integrate scattered topology data from various publicly available databases and a new method was introduced to measure the reliability of predicted topologies. We show that reliability values highly correlate with the per protein topology accuracy of the utilized prediction method. Altogether, more than 52,000 new topology data and more than 2600 new transmembrane proteins have been collected since the last public release of the TOPDB database. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

VKCDB: Voltage-gated potassium channel database

Directory of Open Access Journals (Sweden)

Gallin Warren J

2004-01-01

Full Text Available Abstract Background The family of voltage-gated potassium channels comprises a functionally diverse group of membrane proteins. They help maintain and regulate the potassium ion-based component of the membrane potential and are thus central to many critical physiological processes. VKCDB (Voltage-gated potassium [K] Channel DataBase is a database of structural and functional data on these channels. It is designed as a resource for research on the molecular basis of voltage-gated potassium channel function. Description Voltage-gated potassium channel sequences were identified by using BLASTP to search GENBANK and SWISSPROT. Annotations for all voltage-gated potassium channels were selectively parsed and integrated into VKCDB. Electrophysiological and pharmacological data for the channels were collected from published journal articles. Transmembrane domain predictions by TMHMM and PHD are included for each VKCDB entry. Multiple sequence alignments of conserved domains of channels of the four Kv families and the KCNQ family are also included. Currently VKCDB contains 346 channel entries. It can be browsed and searched using a set of functionally relevant categories. Protein sequences can also be searched using a local BLAST engine. Conclusions VKCDB is a resource for comparative studies of voltage-gated potassium channels. The methods used to construct VKCDB are general; they can be used to create specialized databases for other protein families. VKCDB is accessible at http://vkcdb.biology.ualberta.ca.

Database of ligand-induced domain movements in enzymes

Directory of Open Access Journals (Sweden)

Hayward Steven

2009-03-01

Full Text Available Abstract Background Conformational change induced by the binding of a substrate or coenzyme is a poorly understood stage in the process of enzyme catalysed reactions. For enzymes that exhibit a domain movement, the conformational change can be clearly characterized and therefore the opportunity exists to gain an understanding of the mechanisms involved. The development of the non-redundant database of protein domain movements contains examples of ligand-induced domain movements in enzymes, but this valuable data has remained unexploited. Description The domain movements in the non-redundant database of protein domain movements are those found by applying the DynDom program to pairs of crystallographic structures contained in Protein Data Bank files. For each pair of structures cross-checking ligands in their Protein Data Bank files with the KEGG-LIGAND database and using methods that search for ligands that contact the enzyme in one conformation but not the other, the non-redundant database of protein domain movements was refined down to a set of 203 enzymes where a domain movement is apparently triggered by the binding of a functional ligand. For these cases, ligand binding information, including hydrogen bonds and salt-bridges between the ligand and specific residues on the enzyme is presented in the context of dynamical information such as the regions that form the dynamic domains, the hinge bending residues, and the hinge axes. Conclusion The presentation at a single website of data on interactions between a ligand and specific residues on the enzyme alongside data on the movement that these interactions induce, should lead to new insights into the mechanisms of these enzymes in particular, and help in trying to understand the general process of ligand-induced domain closure in enzymes. The website can be found at: http://www.cmp.uea.ac.uk/dyndom/enzymeList.do

Accelerating Information Retrieval from Profile Hidden Markov Model Databases.

Science.gov (United States)

Tamimi, Ahmad; Ashhab, Yaqoub; Tamimi, Hashem

2016-01-01

Profile Hidden Markov Model (Profile-HMM) is an efficient statistical approach to represent protein families. Currently, several databases maintain valuable protein sequence information as profile-HMMs. There is an increasing interest to improve the efficiency of searching Profile-HMM databases to detect sequence-profile or profile-profile homology. However, most efforts to enhance searching efficiency have been focusing on improving the alignment algorithms. Although the performance of these algorithms is fairly acceptable, the growing size of these databases, as well as the increasing demand for using batch query searching approach, are strong motivations that call for further enhancement of information retrieval from profile-HMM databases. This work presents a heuristic method to accelerate the current profile-HMM homology searching approaches. The method works by cluster-based remodeling of the database to reduce the search space, rather than focusing on the alignment algorithms. Using different clustering techniques, 4284 TIGRFAMs profiles were clustered based on their similarities. A representative for each cluster was assigned. To enhance sensitivity, we proposed an extended step that allows overlapping among clusters. A validation benchmark of 6000 randomly selected protein sequences was used to query the clustered profiles. To evaluate the efficiency of our approach, speed and recall values were measured and compared with the sequential search approach. Using hierarchical, k-means, and connected component clustering techniques followed by the extended overlapping step, we obtained an average reduction in time of 41%, and an average recall of 96%. Our results demonstrate that representation of profile-HMMs using a clustering-based approach can significantly accelerate data retrieval from profile-HMM databases.

O-GLYCBASE version 2.0: a revised database of O-glycosylated proteins

DEFF Research Database (Denmark)

Hansen, Jan; Lund, Ole; Rapacki, Kristoffer

1997-01-01

O-GLYCBASE is an updated database of information on glycoproteins and their O-linked glycosylation sites. Entries are compiled and revised from the literature, and from the SWISS-PROT database. Entries include information about species, sequence, glycosylation sites and glycan type. O-GLYCBASE is...... patterns for the GalNAc, mannose and GlcNAc transferases are shown. The O-GLYCBASE database is available through WWW or by anonymous FTP....

FARE-CAFE: a database of functional and regulatory elements of cancer-associated fusion events.

Science.gov (United States)

Korla, Praveen Kumar; Cheng, Jack; Huang, Chien-Hung; Tsai, Jeffrey J P; Liu, Yu-Hsuan; Kurubanjerdjit, Nilubon; Hsieh, Wen-Tsong; Chen, Huey-Yi; Ng, Ka-Lok

2015-01-01

Chromosomal translocation (CT) is of enormous clinical interest because this disorder is associated with various major solid tumors and leukemia. A tumor-specific fusion gene event may occur when a translocation joins two separate genes. Currently, various CT databases provide information about fusion genes and their genomic elements. However, no database of the roles of fusion genes, in terms of essential functional and regulatory elements in oncogenesis, is available. FARE-CAFE is a unique combination of CTs, fusion proteins, protein domains, domain-domain interactions, protein-protein interactions, transcription factors and microRNAs, with subsequent experimental information, which cannot be found in any other CT database. Genomic DNA information including, for example, manually collected exact locations of the first and second break points, sequences and karyotypes of fusion genes are included. FARE-CAFE will substantially facilitate the cancer biologist's mission of elucidating the pathogenesis of various types of cancer. This database will ultimately help to develop 'novel' therapeutic approaches. Database URL: http://ppi.bioinfo.asia.edu.tw/FARE-CAFE. © The Author(s) 2015. Published by Oxford University Press.

LRRML: a conformational database and an XML description of leucine-rich repeats (LRRs).

Science.gov (United States)

Wei, Tiandi; Gong, Jing; Jamitzky, Ferdinand; Heckl, Wolfgang M; Stark, Robert W; Rössle, Shaila C

2008-11-05

Leucine-rich repeats (LRRs) are present in more than 6000 proteins. They are found in organisms ranging from viruses to eukaryotes and play an important role in protein-ligand interactions. To date, more than one hundred crystal structures of LRR containing proteins have been determined. This knowledge has increased our ability to use the crystal structures as templates to model LRR proteins with unknown structures. Since the individual three-dimensional LRR structures are not directly available from the established databases and since there are only a few detailed annotations for them, a conformational LRR database useful for homology modeling of LRR proteins is desirable. We developed LRRML, a conformational database and an extensible markup language (XML) description of LRRs. The release 0.2 contains 1261 individual LRR structures, which were identified from 112 PDB structures and annotated manually. An XML structure was defined to exchange and store the LRRs. LRRML provides a source for homology modeling and structural analysis of LRR proteins. In order to demonstrate the capabilities of the database we modeled the mouse Toll-like receptor 3 (TLR3) by multiple templates homology modeling and compared the result with the crystal structure. LRRML is an information source for investigators involved in both theoretical and applied research on LRR proteins. It is available at http://zeus.krist.geo.uni-muenchen.de/~lrrml.

LRRML: a conformational database and an XML description of leucine-rich repeats (LRRs

Directory of Open Access Journals (Sweden)

Stark Robert W

2008-11-01

Full Text Available Abstract Background Leucine-rich repeats (LRRs are present in more than 6000 proteins. They are found in organisms ranging from viruses to eukaryotes and play an important role in protein-ligand interactions. To date, more than one hundred crystal structures of LRR containing proteins have been determined. This knowledge has increased our ability to use the crystal structures as templates to model LRR proteins with unknown structures. Since the individual three-dimensional LRR structures are not directly available from the established databases and since there are only a few detailed annotations for them, a conformational LRR database useful for homology modeling of LRR proteins is desirable. Description We developed LRRML, a conformational database and an extensible markup language (XML description of LRRs. The release 0.2 contains 1261 individual LRR structures, which were identified from 112 PDB structures and annotated manually. An XML structure was defined to exchange and store the LRRs. LRRML provides a source for homology modeling and structural analysis of LRR proteins. In order to demonstrate the capabilities of the database we modeled the mouse Toll-like receptor 3 (TLR3 by multiple templates homology modeling and compared the result with the crystal structure. Conclusion LRRML is an information source for investigators involved in both theoretical and applied research on LRR proteins. It is available at http://zeus.krist.geo.uni-muenchen.de/~lrrml.

YPED: an integrated bioinformatics suite and database for mass spectrometry-based proteomics research.

Science.gov (United States)

Colangelo, Christopher M; Shifman, Mark; Cheung, Kei-Hoi; Stone, Kathryn L; Carriero, Nicholas J; Gulcicek, Erol E; Lam, TuKiet T; Wu, Terence; Bjornson, Robert D; Bruce, Can; Nairn, Angus C; Rinehart, Jesse; Miller, Perry L; Williams, Kenneth R

2015-02-01

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography-tandem mass spectrometry (LC-MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED's database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

Database activities at Brookhaven National Laboratory

International Nuclear Information System (INIS)

Trahern, C.G.

1995-01-01

Brookhaven National Laboratory is a multi-disciplinary lab in the DOE system of research laboratories. Database activities are correspondingly diverse within the restrictions imposed by the dominant relational database paradigm. The authors discuss related activities and tools used in RHIC and in the other major projects at BNL. The others are the Protein Data Bank being maintained by the Chemistry department, and a Geographical Information System (GIS)--a Superfund sponsored environmental monitoring project under development in the Office of Environmental Restoration

Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria

International Nuclear Information System (INIS)

Fritzsching, Keith J.; Hong, Mei; Schmidt-Rohr, Klaus

2016-01-01

We have determined refined multidimensional chemical shift ranges for intra-residue correlations ( 13 C– 13 C, 15 N– 13 C, etc.) in proteins, which can be used to gain type-assignment and/or secondary-structure information from experimental NMR spectra. The chemical-shift ranges are the result of a statistical analysis of the PACSY database of >3000 proteins with 3D structures (1,200,207 13 C chemical shifts and >3 million chemical shifts in total); these data were originally derived from the Biological Magnetic Resonance Data Bank. Using relatively simple non-parametric statistics to find peak maxima in the distributions of helix, sheet, coil and turn chemical shifts, and without the use of limited “hand-picked” data sets, we show that ∼94 % of the 13 C NMR data and almost all 15 N data are quite accurately referenced and assigned, with smaller standard deviations (0.2 and 0.8 ppm, respectively) than recognized previously. On the other hand, approximately 6 % of the 13 C chemical shift data in the PACSY database are shown to be clearly misreferenced, mostly by ca. −2.4 ppm. The removal of the misreferenced data and other outliers by this purging by intrinsic quality criteria (PIQC) allows for reliable identification of secondary maxima in the two-dimensional chemical-shift distributions already pre-separated by secondary structure. We demonstrate that some of these correspond to specific regions in the Ramachandran plot, including left-handed helix dihedral angles, reflect unusual hydrogen bonding, or are due to the influence of a following proline residue. With appropriate smoothing, significantly more tightly defined chemical shift ranges are obtained for each amino acid type in the different secondary structures. These chemical shift ranges, which may be defined at any statistical threshold, can be used for amino-acid type assignment and secondary-structure analysis of chemical shifts from intra-residue cross peaks by inspection or by using a

Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria

Energy Technology Data Exchange (ETDEWEB)

Fritzsching, Keith J., E-mail: kfritzsc@brandeis.edu [Brandeis University, Department of Chemistry (United States); Hong, Mei [Massachusetts Institute of Technology, Department of Chemistry (United States); Schmidt-Rohr, Klaus, E-mail: srohr@brandeis.edu [Brandeis University, Department of Chemistry (United States)

2016-02-15

We have determined refined multidimensional chemical shift ranges for intra-residue correlations ({sup 13}C–{sup 13}C, {sup 15}N–{sup 13}C, etc.) in proteins, which can be used to gain type-assignment and/or secondary-structure information from experimental NMR spectra. The chemical-shift ranges are the result of a statistical analysis of the PACSY database of >3000 proteins with 3D structures (1,200,207 {sup 13}C chemical shifts and >3 million chemical shifts in total); these data were originally derived from the Biological Magnetic Resonance Data Bank. Using relatively simple non-parametric statistics to find peak maxima in the distributions of helix, sheet, coil and turn chemical shifts, and without the use of limited “hand-picked” data sets, we show that ∼94 % of the {sup 13}C NMR data and almost all {sup 15}N data are quite accurately referenced and assigned, with smaller standard deviations (0.2 and 0.8 ppm, respectively) than recognized previously. On the other hand, approximately 6 % of the {sup 13}C chemical shift data in the PACSY database are shown to be clearly misreferenced, mostly by ca. −2.4 ppm. The removal of the misreferenced data and other outliers by this purging by intrinsic quality criteria (PIQC) allows for reliable identification of secondary maxima in the two-dimensional chemical-shift distributions already pre-separated by secondary structure. We demonstrate that some of these correspond to specific regions in the Ramachandran plot, including left-handed helix dihedral angles, reflect unusual hydrogen bonding, or are due to the influence of a following proline residue. With appropriate smoothing, significantly more tightly defined chemical shift ranges are obtained for each amino acid type in the different secondary structures. These chemical shift ranges, which may be defined at any statistical threshold, can be used for amino-acid type assignment and secondary-structure analysis of chemical shifts from intra

Accelerating Information Retrieval from Profile Hidden Markov Model Databases.

Directory of Open Access Journals (Sweden)

Ahmad Tamimi

Full Text Available Profile Hidden Markov Model (Profile-HMM is an efficient statistical approach to represent protein families. Currently, several databases maintain valuable protein sequence information as profile-HMMs. There is an increasing interest to improve the efficiency of searching Profile-HMM databases to detect sequence-profile or profile-profile homology. However, most efforts to enhance searching efficiency have been focusing on improving the alignment algorithms. Although the performance of these algorithms is fairly acceptable, the growing size of these databases, as well as the increasing demand for using batch query searching approach, are strong motivations that call for further enhancement of information retrieval from profile-HMM databases. This work presents a heuristic method to accelerate the current profile-HMM homology searching approaches. The method works by cluster-based remodeling of the database to reduce the search space, rather than focusing on the alignment algorithms. Using different clustering techniques, 4284 TIGRFAMs profiles were clustered based on their similarities. A representative for each cluster was assigned. To enhance sensitivity, we proposed an extended step that allows overlapping among clusters. A validation benchmark of 6000 randomly selected protein sequences was used to query the clustered profiles. To evaluate the efficiency of our approach, speed and recall values were measured and compared with the sequential search approach. Using hierarchical, k-means, and connected component clustering techniques followed by the extended overlapping step, we obtained an average reduction in time of 41%, and an average recall of 96%. Our results demonstrate that representation of profile-HMMs using a clustering-based approach can significantly accelerate data retrieval from profile-HMM databases.

Protein - Trypanosomes Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data List Contact us Trypanoso...nhibitor of the protein. Data file File name: trypanosome.zip File URL: ftp://ftp....biosciencedbc.jp/archive/trypanosome/LATEST/trypanosome.zip File size: 1.4 KB Simple search URL http://togo...db.biosciencedbc.jp/togodb/view/trypanosome#en Data acquisition method - Data analysis method - Number of da...ndelian inheritance in Man ) map Location of the gene on a chromosome or its chromosome number pdb PDB ID (P

RAIN: RNA-protein Association and Interaction Networks

DEFF Research Database (Denmark)

Junge, Alexander; Refsgaard, Jan Christian; Garde, Christian

2017-01-01

is challenging due to data heterogeneity. Here, we present a database of ncRNA-RNA and ncRNA-protein interactions and its integration with the STRING database of protein-protein interactions. These ncRNA associations cover four organisms and have been established from curated examples, experimental data...

Intelligent Access to Sequence and Structure Databases (IASSD) - an interface for accessing information from major web databases.

Science.gov (United States)

Ganguli, Sayak; Gupta, Manoj Kumar; Basu, Protip; Banik, Rahul; Singh, Pankaj Kumar; Vishal, Vineet; Bera, Abhisek Ranjan; Chakraborty, Hirak Jyoti; Das, Sasti Gopal

2014-01-01

With the advent of age of big data and advances in high throughput technology accessing data has become one of the most important step in the entire knowledge discovery process. Most users are not able to decipher the query result that is obtained when non specific keywords or a combination of keywords are used. Intelligent access to sequence and structure databases (IASSD) is a desktop application for windows operating system. It is written in Java and utilizes the web service description language (wsdl) files and Jar files of E-utilities of various databases such as National Centre for Biotechnology Information (NCBI) and Protein Data Bank (PDB). Apart from that IASSD allows the user to view protein structure using a JMOL application which supports conditional editing. The Jar file is freely available through e-mail from the corresponding author.

Identification of proteins similar to AvrE type III effector proteins from ...

African Journals Online (AJOL)

Stephen Opiyo

GSE22274), and AraCyc databases, we highlighted 16 protein candidates from Arabidopsidis genome .... projection method similar to principal component analysis (PCA) .... RIN4 RIN4 (RPM1 INTERACTING PROTEIN 4); protein binding.

HitPredict version 4: comprehensive reliability scoring of physical protein-protein interactions from more than 100 species.

Science.gov (United States)

López, Yosvany; Nakai, Kenta; Patil, Ashwini

2015-01-01

HitPredict is a consolidated resource of experimentally identified, physical protein-protein interactions with confidence scores to indicate their reliability. The study of genes and their inter-relationships using methods such as network and pathway analysis requires high quality protein-protein interaction information. Extracting reliable interactions from most of the existing databases is challenging because they either contain only a subset of the available interactions, or a mixture of physical, genetic and predicted interactions. Automated integration of interactions is further complicated by varying levels of accuracy of database content and lack of adherence to standard formats. To address these issues, the latest version of HitPredict provides a manually curated dataset of 398 696 physical associations between 70 808 proteins from 105 species. Manual confirmation was used to resolve all issues encountered during data integration. For improved reliability assessment, this version combines a new score derived from the experimental information of the interactions with the original score based on the features of the interacting proteins. The combined interaction score performs better than either of the individual scores in HitPredict as well as the reliability score of another similar database. HitPredict provides a web interface to search proteins and visualize their interactions, and the data can be downloaded for offline analysis. Data usability has been enhanced by mapping protein identifiers across multiple reference databases. Thus, the latest version of HitPredict provides a significantly larger, more reliable and usable dataset of protein-protein interactions from several species for the study of gene groups. Database URL: http://hintdb.hgc.jp/htp. © The Author(s) 2015. Published by Oxford University Press.

O-GLYCBASE version 3.0: a revised database of O-glycosylated proteins

DEFF Research Database (Denmark)

Hansen, Jan; Lund, Ole; Nilsson, Jette

1998-01-01

O-GLYCBASE is a revised database of information on glycoproteins and their O-linked glycosylation sites. Entries are compiled and revised from the literature, and from the sequence databases. Entries include informations about species, sequence, glycosylation sites and glycan type and is fully cr...

dbEM: A database of epigenetic modifiers curated from cancerous and normal genomes

Science.gov (United States)

Singh Nanda, Jagpreet; Kumar, Rahul; Raghava, Gajendra P. S.

2016-01-01

We have developed a database called dbEM (database of Epigenetic Modifiers) to maintain the genomic information of about 167 epigenetic modifiers/proteins, which are considered as potential cancer targets. In dbEM, modifiers are classified on functional basis and comprise of 48 histone methyl transferases, 33 chromatin remodelers and 31 histone demethylases. dbEM maintains the genomic information like mutations, copy number variation and gene expression in thousands of tumor samples, cancer cell lines and healthy samples. This information is obtained from public resources viz. COSMIC, CCLE and 1000-genome project. Gene essentiality data retrieved from COLT database further highlights the importance of various epigenetic proteins for cancer survival. We have also reported the sequence profiles, tertiary structures and post-translational modifications of these epigenetic proteins in cancer. It also contains information of 54 drug molecules against different epigenetic proteins. A wide range of tools have been integrated in dbEM e.g. Search, BLAST, Alignment and Profile based prediction. In our analysis, we found that epigenetic proteins DNMT3A, HDAC2, KDM6A, and TET2 are highly mutated in variety of cancers. We are confident that dbEM will be very useful in cancer research particularly in the field of epigenetic proteins based cancer therapeutics. This database is available for public at URL: http://crdd.osdd.net/raghava/dbem.

Development of Pharmacophore Model for Indeno[1,2-b]indoles as Human Protein Kinase CK2 Inhibitors and Database Mining

Directory of Open Access Journals (Sweden)

Samer Haidar

2017-01-01

Full Text Available Protein kinase CK2, initially designated as casein kinase 2, is an ubiquitously expressed serine/threonine kinase. This enzyme, implicated in many cellular processes, is highly expressed and active in many tumor cells. A large number of compounds has been developed as inhibitors comprising different backbones. Beside others, structures with an indeno[1,2-b]indole scaffold turned out to be potent new leads. With the aim of developing new inhibitors of human protein kinase CK2, we report here on the generation of common feature pharmacophore model to further explain the binding requirements for human CK2 inhibitors. Nine common chemical features of indeno[1,2-b]indole-type CK2 inhibitors were determined using MOE software (Chemical Computing Group, Montreal, Canada. This pharmacophore model was used for database mining with the aim to identify novel scaffolds for developing new potent and selective CK2 inhibitors. Using this strategy several structures were selected by searching inside the ZINC compound database. One of the selected compounds was bikaverin (6,11-dihydroxy-3,8-dimethoxy-1-methylbenzo[b]xanthene-7,10,12-trione, a natural compound which is produced by several kinds of fungi. This compound was tested on human recombinant CK2 and turned out to be an active inhibitor with an IC50 value of 1.24 µM.

1.15 - Structural Chemogenomics Databases to Navigate Protein–Ligand Interaction Space

NARCIS (Netherlands)

Kanev, G.K.; Kooistra, A.J.; de Esch, I.J.P.; de Graaf, C.

2017-01-01

Structural chemogenomics databases allow the integration and exploration of heterogeneous genomic, structural, chemical, and pharmacological data in order to extract useful information that is applicable for the discovery of new protein targets and biologically active molecules. Integrated databases

Sequence protein identification by randomized sequence database and transcriptome mass spectrometry (SPIDER-TMS): from manual to automatic application of a 'de novo sequencing' approach.

Science.gov (United States)

Pascale, Raffaella; Grossi, Gerarda; Cruciani, Gabriele; Mecca, Giansalvatore; Santoro, Donatello; Sarli Calace, Renzo; Falabella, Patrizia; Bianco, Giuliana

Sequence protein identification by a randomized sequence database and transcriptome mass spectrometry software package has been developed at the University of Basilicata in Potenza (Italy) and designed to facilitate the determination of the amino acid sequence of a peptide as well as an unequivocal identification of proteins in a high-throughput manner with enormous advantages of time, economical resource and expertise. The software package is a valid tool for the automation of a de novo sequencing approach, overcoming the main limits and a versatile platform useful in the proteomic field for an unequivocal identification of proteins, starting from tandem mass spectrometry data. The strength of this software is that it is a user-friendly and non-statistical approach, so protein identification can be considered unambiguous.

Databases in the Area of Pharmacogenetics

Science.gov (United States)

Sim, Sarah C.; Altman, Russ B.; Ingelman-Sundberg, Magnus

2012-01-01

In the area of pharmacogenetics and personalized health care it is obvious that databases, providing important information of the occurrence and consequences of variant genes encoding drug metabolizing enzymes, drug transporters, drug targets, and other proteins of importance for drug response or toxicity, are of critical value for scientists, physicians, and industry. The primary outcome of the pharmacogenomic field is the identification of biomarkers that can predict drug toxicity and drug response, thereby individualizing and improving drug treatment of patients. The drug in question and the polymorphic gene exerting the impact are the main issues to be searched for in the databases. Here, we review the databases that provide useful information in this respect, of benefit for the development of the pharmacogenomic field. PMID:21309040

Bioinformatics and moonlighting proteins

Directory of Open Access Journals (Sweden)

Sergio eHernández

2015-06-01

Full Text Available Multitasking or moonlighting is the capability of some proteins to execute two or more biochemical functions. Usually, moonlighting proteins are experimentally revealed by serendipity. For this reason, it would be helpful that Bioinformatics could predict this multifunctionality, especially because of the large amounts of sequences from genome projects. In the present work, we analyse and describe several approaches that use sequences, structures, interactomics and current bioinformatics algorithms and programs to try to overcome this problem. Among these approaches are: a remote homology searches using Psi-Blast, b detection of functional motifs and domains, c analysis of data from protein-protein interaction databases (PPIs, d match the query protein sequence to 3D databases (i.e., algorithms as PISITE, e mutation correlation analysis between amino acids by algorithms as MISTIC. Programs designed to identify functional motif/domains detect mainly the canonical function but usually fail in the detection of the moonlighting one, Pfam and ProDom being the best methods. Remote homology search by Psi-Blast combined with data from interactomics databases (PPIs have the best performance. Structural information and mutation correlation analysis can help us to map the functional sites. Mutation correlation analysis can only be used in very specific situations –it requires the existence of multialigned family protein sequences - but can suggest how the evolutionary process of second function acquisition took place. The multitasking protein database MultitaskProtDB (http://wallace.uab.es/multitask/, previously published by our group, has been used as a benchmark for the all of the analyses.

The Importance of Biological Databases in Biological Discovery.

Science.gov (United States)

Baxevanis, Andreas D; Bateman, Alex

2015-06-19

Biological databases play a central role in bioinformatics. They offer scientists the opportunity to access a wide variety of biologically relevant data, including the genomic sequences of an increasingly broad range of organisms. This unit provides a brief overview of major sequence databases and portals, such as GenBank, the UCSC Genome Browser, and Ensembl. Model organism databases, including WormBase, The Arabidopsis Information Resource (TAIR), and those made available through the Mouse Genome Informatics (MGI) resource, are also covered. Non-sequence-centric databases, such as Online Mendelian Inheritance in Man (OMIM), the Protein Data Bank (PDB), MetaCyc, and the Kyoto Encyclopedia of Genes and Genomes (KEGG), are also discussed. Copyright © 2015 John Wiley & Sons, Inc.

Analysis of high accuracy, quantitative proteomics data in the MaxQB database.

Science.gov (United States)

Schaab, Christoph; Geiger, Tamar; Stoehr, Gabriele; Cox, Juergen; Mann, Matthias

2012-03-01

MS-based proteomics generates rapidly increasing amounts of precise and quantitative information. Analysis of individual proteomic experiments has made great strides, but the crucial ability to compare and store information across different proteome measurements still presents many challenges. For example, it has been difficult to avoid contamination of databases with low quality peptide identifications, to control for the inflation in false positive identifications when combining data sets, and to integrate quantitative data. Although, for example, the contamination with low quality identifications has been addressed by joint analysis of deposited raw data in some public repositories, we reasoned that there should be a role for a database specifically designed for high resolution and quantitative data. Here we describe a novel database termed MaxQB that stores and displays collections of large proteomics projects and allows joint analysis and comparison. We demonstrate the analysis tools of MaxQB using proteome data of 11 different human cell lines and 28 mouse tissues. The database-wide false discovery rate is controlled by adjusting the project specific cutoff scores for the combined data sets. The 11 cell line proteomes together identify proteins expressed from more than half of all human genes. For each protein of interest, expression levels estimated by label-free quantification can be visualized across the cell lines. Similarly, the expression rank order and estimated amount of each protein within each proteome are plotted. We used MaxQB to calculate the signal reproducibility of the detected peptides for the same proteins across different proteomes. Spearman rank correlation between peptide intensity and detection probability of identified proteins was greater than 0.8 for 64% of the proteome, whereas a minority of proteins have negative correlation. This information can be used to pinpoint false protein identifications, independently of peptide database

PRIDE and "Database on Demand" as valuable tools for computational proteomics.

Science.gov (United States)

Vizcaíno, Juan Antonio; Reisinger, Florian; Côté, Richard; Martens, Lennart

2011-01-01

The Proteomics Identifications Database (PRIDE, http://www.ebi.ac.uk/pride ) provides users with the ability to explore and compare mass spectrometry-based proteomics experiments that reveal details of the protein expression found in a broad range of taxonomic groups, tissues, and disease states. A PRIDE experiment typically includes identifications of proteins, peptides, and protein modifications. Additionally, many of the submitted experiments also include the mass spectra that provide the evidence for these identifications. Finally, one of the strongest advantages of PRIDE in comparison with other proteomics repositories is the amount of metadata it contains, a key point to put the above-mentioned data in biological and/or technical context. Several informatics tools have been developed in support of the PRIDE database. The most recent one is called "Database on Demand" (DoD), which allows custom sequence databases to be built in order to optimize the results from search engines. We describe the use of DoD in this chapter. Additionally, in order to show the potential of PRIDE as a source for data mining, we also explore complex queries using federated BioMart queries to integrate PRIDE data with other resources, such as Ensembl, Reactome, or UniProt.

Database citation in full text biomedical articles.

Science.gov (United States)

Kafkas, Şenay; Kim, Jee-Hyub; McEntyre, Johanna R

2013-01-01

Molecular biology and literature databases represent essential infrastructure for life science research. Effective integration of these data resources requires that there are structured cross-references at the level of individual articles and biological records. Here, we describe the current patterns of how database entries are cited in research articles, based on analysis of the full text Open Access articles available from Europe PMC. Focusing on citation of entries in the European Nucleotide Archive (ENA), UniProt and Protein Data Bank, Europe (PDBe), we demonstrate that text mining doubles the number of structured annotations of database record citations supplied in journal articles by publishers. Many thousands of new literature-database relationships are found by text mining, since these relationships are also not present in the set of articles cited by database records. We recommend that structured annotation of database records in articles is extended to other databases, such as ArrayExpress and Pfam, entries from which are also cited widely in the literature. The very high precision and high-throughput of this text-mining pipeline makes this activity possible both accurately and at low cost, which will allow the development of new integrated data services.

Deep Time Data Infrastructure: Integrating Our Current Geologic and Biologic Databases

Science.gov (United States)

Kolankowski, S. M.; Fox, P. A.; Ma, X.; Prabhu, A.

2016-12-01

As our knowledge of Earth's geologic and mineralogical history grows, we require more efficient methods of sharing immense amounts of data. Databases across numerous disciplines have been utilized to offer extensive information on very specific Epochs of Earth's history up to its current state, i.e. Fossil record, rock composition, proteins, etc. These databases could be a powerful force in identifying previously unseen correlations such as relationships between minerals and proteins. Creating a unifying site that provides a portal to these databases will aid in our ability as a collaborative scientific community to utilize our findings more effectively. The Deep-Time Data Infrastructure (DTDI) is currently being defined as part of a larger effort to accomplish this goal. DTDI will not be a new database, but an integration of existing resources. Current geologic and related databases were identified, documentation of their schema was established and will be presented as a stage by stage progression. Through conceptual modeling focused around variables from their combined records, we will determine the best way to integrate these databases using common factors. The Deep-Time Data Infrastructure will allow geoscientists to bridge gaps in data and further our understanding of our Earth's history.

Creating a specialist protein resource network: a meeting report for the protein bioinformatics and community resources retreat.

Science.gov (United States)

Babbitt, Patricia C; Bagos, Pantelis G; Bairoch, Amos; Bateman, Alex; Chatonnet, Arnaud; Chen, Mark Jinan; Craik, David J; Finn, Robert D; Gloriam, David; Haft, Daniel H; Henrissat, Bernard; Holliday, Gemma L; Isberg, Vignir; Kaas, Quentin; Landsman, David; Lenfant, Nicolas; Manning, Gerard; Nagano, Nozomi; Srinivasan, Narayanaswamy; O'Donovan, Claire; Pruitt, Kim D; Sowdhamini, Ramanathan; Rawlings, Neil D; Saier, Milton H; Sharman, Joanna L; Spedding, Michael; Tsirigos, Konstantinos D; Vastermark, Ake; Vriend, Gerrit

2015-01-01

During 11-12 August 2014, a Protein Bioinformatics and Community Resources Retreat was held at the Wellcome Trust Genome Campus in Hinxton, UK. This meeting brought together the principal investigators of several specialized protein resources (such as CAZy, TCDB and MEROPS) as well as those from protein databases from the large Bioinformatics centres (including UniProt and RefSeq). The retreat was divided into five sessions: (1) key challenges, (2) the databases represented, (3) best practices for maintenance and curation, (4) information flow to and from large data centers and (5) communication and funding. An important outcome of this meeting was the creation of a Specialist Protein Resource Network that we believe will improve coordination of the activities of its member resources. We invite further protein database resources to join the network and continue the dialogue.

Membrane's Eleven: heavy-atom derivatives of membrane-protein crystals

DEFF Research Database (Denmark)

Morth, Jens Preben; Sørensen, Thomas Lykke-Møller; Nissen, Poul

2006-01-01

A database has been assembled of heavy-atom derivatives used in the structure determination of membrane proteins. The database can serve as a guide to the design of experiments in the search for heavy-atom derivatives of new membrane-protein crystals. The database pinpoints organomercurials...

Protein Annotation from Protein Interaction Networks and Gene Ontology

OpenAIRE

Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

2011-01-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

Database Description - SKIP Stemcell Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us SKIP Stemcell Database Database Description General information of database Database name SKIP Stemcell Database...rsity Journal Search: Contact address http://www.skip.med.keio.ac.jp/en/contact/ Database classification Human Genes and Diseases Dat...abase classification Stemcell Article Organism Taxonomy Name: Homo sapiens Taxonomy ID: 9606 Database...ks: Original website information Database maintenance site Center for Medical Genetics, School of medicine, ...lable Web services Not available URL of Web services - Need for user registration Not available About This Database Database

Database Description - Arabidopsis Phenome Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Arabidopsis Phenome Database Database Description General information of database Database n... BioResource Center Hiroshi Masuya Database classification Plant databases - Arabidopsis thaliana Organism T...axonomy Name: Arabidopsis thaliana Taxonomy ID: 3702 Database description The Arabidopsis thaliana phenome i...heir effective application. We developed the new Arabidopsis Phenome Database integrating two novel database...seful materials for their experimental research. The other, the “Database of Curated Plant Phenome” focusing

GenoMycDB: a database for comparative analysis of mycobacterial genes and genomes.

Science.gov (United States)

Catanho, Marcos; Mascarenhas, Daniel; Degrave, Wim; Miranda, Antonio Basílio de

2006-03-31

Several databases and computational tools have been created with the aim of organizing, integrating and analyzing the wealth of information generated by large-scale sequencing projects of mycobacterial genomes and those of other organisms. However, with very few exceptions, these databases and tools do not allow for massive and/or dynamic comparison of these data. GenoMycDB (http://www.dbbm.fiocruz.br/GenoMycDB) is a relational database built for large-scale comparative analyses of completely sequenced mycobacterial genomes, based on their predicted protein content. Its central structure is composed of the results obtained after pair-wise sequence alignments among all the predicted proteins coded by the genomes of six mycobacteria: Mycobacterium tuberculosis (strains H37Rv and CDC1551), M. bovis AF2122/97, M. avium subsp. paratuberculosis K10, M. leprae TN, and M. smegmatis MC2 155. The database stores the computed similarity parameters of every aligned pair, providing for each protein sequence the predicted subcellular localization, the assigned cluster of orthologous groups, the features of the corresponding gene, and links to several important databases. Tables containing pairs or groups of potential homologs between selected species/strains can be produced dynamically by user-defined criteria, based on one or multiple sequence similarity parameters. In addition, searches can be restricted according to the predicted subcellular localization of the protein, the DNA strand of the corresponding gene and/or the description of the protein. Massive data search and/or retrieval are available, and different ways of exporting the result are offered. GenoMycDB provides an on-line resource for the functional classification of mycobacterial proteins as well as for the analysis of genome structure, organization, and evolution.

AtlasT4SS: a curated database for type IV secretion systems.

Science.gov (United States)

Souza, Rangel C; del Rosario Quispe Saji, Guadalupe; Costa, Maiana O C; Netto, Diogo S; Lima, Nicholas C B; Klein, Cecília C; Vasconcelos, Ana Tereza R; Nicolás, Marisa F

2012-08-09

The type IV secretion system (T4SS) can be classified as a large family of macromolecule transporter systems, divided into three recognized sub-families, according to the well-known functions. The major sub-family is the conjugation system, which allows transfer of genetic material, such as a nucleoprotein, via cell contact among bacteria. Also, the conjugation system can transfer genetic material from bacteria to eukaryotic cells; such is the case with the T-DNA transfer of Agrobacterium tumefaciens to host plant cells. The system of effector protein transport constitutes the second sub-family, and the third one corresponds to the DNA uptake/release system. Genome analyses have revealed numerous T4SS in Bacteria and Archaea. The purpose of this work was to organize, classify, and integrate the T4SS data into a single database, called AtlasT4SS - the first public database devoted exclusively to this prokaryotic secretion system. The AtlasT4SS is a manual curated database that describes a large number of proteins related to the type IV secretion system reported so far in Gram-negative and Gram-positive bacteria, as well as in Archaea. The database was created using the RDBMS MySQL and the Catalyst Framework based in the Perl programming language and using the Model-View-Controller (MVC) design pattern for Web. The current version holds a comprehensive collection of 1,617 T4SS proteins from 58 Bacteria (49 Gram-negative and 9 Gram-Positive), one Archaea and 11 plasmids. By applying the bi-directional best hit (BBH) relationship in pairwise genome comparison, it was possible to obtain a core set of 134 clusters of orthologous genes encoding T4SS proteins. In our database we present one way of classifying orthologous groups of T4SSs in a hierarchical classification scheme with three levels. The first level comprises four classes that are based on the organization of genetic determinants, shared homologies, and evolutionary relationships: (i) F-T4SS, (ii) P-T4SS, (iii

Cluster (Viridiplantae) - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available 0”. This cluster ID is uniquely-assigned by the PGDBj Ortholog Database. Cluster size Number of proteins aff...r About This Database Database Description Download License Update History of This Database Site Policy | Contact Us Cluster (Viridiplantae) - PGDBj - Ortholog DB | LSDB Archive ... ...List Contact us PGDBj - Ortholog DB Cluster (Viridiplantae) Data detail Data name Cluster (Viridiplantae) DO...switchLanguage; BLAST Search Image Search Home About Archive Update History Data

Cluster (Cyanobacteria) - PGDBj - Ortholog DB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available 3090”. This cluster ID is uniquely-assigned by the PGDBj Ortholog Database. Cluster size Number of proteins ...ster About This Database Database Description Download License Update History of This Database Site Policy | Contact Us Cluster (Cyanobacteria) - PGDBj - Ortholog DB | LSDB Archive ... ...List Contact us PGDBj - Ortholog DB Cluster (Cyanobacteria) Data detail Data name Cluster (Cyanobacteria) DO...switchLanguage; BLAST Search Image Search Home About Archive Update History Data

GPCR & company: databases and servers for GPCRs and interacting partners.

Science.gov (United States)

Kowalsman, Noga; Niv, Masha Y

2014-01-01

G-protein-coupled receptors (GPCRs) are a large superfamily of membrane receptors that are involved in a wide range of signaling pathways. To fulfill their tasks, GPCRs interact with a variety of partners, including small molecules, lipids and proteins. They are accompanied by different proteins during all phases of their life cycle. Therefore, GPCR interactions with their partners are of great interest in basic cell-signaling research and in drug discovery.Due to the rapid development of computers and internet communication, knowledge and data can be easily shared within the worldwide research community via freely available databases and servers. These provide an abundance of biological, chemical and pharmacological information.This chapter describes the available web resources for investigating GPCR interactions. We review about 40 freely available databases and servers, and provide a few sentences about the essence and the data they supply. For simplification, the databases and servers were grouped under the following topics: general GPCR-ligand interactions; particular families of GPCRs and their ligands; GPCR oligomerization; GPCR interactions with intracellular partners; and structural information on GPCRs. In conclusion, a multitude of useful tools are currently available. Summary tables are provided to ease navigation between the numerous and partially overlapping resources. Suggestions for future enhancements of the online tools include the addition of links from general to specialized databases and enabling usage of user-supplied template for GPCR structural modeling.

ProDis-ContSHC: Learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrieval

KAUST Repository

Wang, Jim Jing-Yan; Gao, Xin; Wang, Quanquan; Li, Yongping

2012-01-01

Background: The need to retrieve or classify protein molecules using structure or sequence-based similarity measures underlies a wide range of biomedical applications. Traditional protein search methods rely on a pairwise dissimilarity

PREIMS - AT Atlas | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data ...Targeted Proteins Research Program (TPRP). Data file File name: at_atlas_preims.zip File URL: ftp://ftp.biosciencedbc.jp/archiv...base Database Description Download License Update History of This Database Site Policy | Contact Us PREIMS - AT Atlas | LSDB Archive ...

Real-Time Ligand Binding Pocket Database Search Using Local Surface Descriptors

Science.gov (United States)

Chikhi, Rayan; Sael, Lee; Kihara, Daisuke

2010-01-01

Due to the increasing number of structures of unknown function accumulated by ongoing structural genomics projects, there is an urgent need for computational methods for characterizing protein tertiary structures. As functions of many of these proteins are not easily predicted by conventional sequence database searches, a legitimate strategy is to utilize structure information in function characterization. Of a particular interest is prediction of ligand binding to a protein, as ligand molecule recognition is a major part of molecular function of proteins. Predicting whether a ligand molecule binds a protein is a complex problem due to the physical nature of protein-ligand interactions and the flexibility of both binding sites and ligand molecules. However, geometric and physicochemical complementarity is observed between the ligand and its binding site in many cases. Therefore, ligand molecules which bind to a local surface site in a protein can be predicted by finding similar local pockets of known binding ligands in the structure database. Here, we present two representations of ligand binding pockets and utilize them for ligand binding prediction by pocket shape comparison. These representations are based on mapping of surface properties of binding pockets, which are compactly described either by the two dimensional pseudo-Zernike moments or the 3D Zernike descriptors. These compact representations allow a fast real-time pocket searching against a database. Thorough benchmark study employing two different datasets show that our representations are competitive with the other existing methods. Limitations and potentials of the shape-based methods as well as possible improvements are discussed. PMID:20455259

Profiling of Escherichia coli Chromosome database.

Science.gov (United States)

Yamazaki, Yukiko; Niki, Hironori; Kato, Jun-ichi

2008-01-01

The Profiling of Escherichia coli Chromosome (PEC) database (http://www.shigen.nig.ac.jp/ecoli/pec/) is designed to allow E. coli researchers to efficiently access information from functional genomics studies. The database contains two principal types of data: gene essentiality and a large collection of E. coli genetic research resources. The essentiality data are based on data compilation from published single-gene essentiality studies and on cell growth studies of large-deletion mutants. Using the circular and linear viewers for both whole genomes and the minimal genome, users can not only gain an overview of the genome structure but also retrieve information on contigs, gene products, mutants, deletions, and so forth. In particular, genome-wide exhaustive mutants are an essential resource for studying E. coli gene functions. Although the genomic database was constructed independently from the genetic resources database, users may seamlessly access both types of data. In addition to these data, the PEC database also provides a summary of homologous genes of other bacterial genomes and of protein structure information, with a comprehensive interface. The PEC is thus a convenient and useful platform for contemporary E. coli researchers.

Wiki-pi: a web-server of annotated human protein-protein interactions to aid in discovery of protein function.

Directory of Open Access Journals (Sweden)

Naoki Orii

Full Text Available Protein-protein interactions (PPIs are the basis of biological functions. Knowledge of the interactions of a protein can help understand its molecular function and its association with different biological processes and pathways. Several publicly available databases provide comprehensive information about individual proteins, such as their sequence, structure, and function. There also exist databases that are built exclusively to provide PPIs by curating them from published literature. The information provided in these web resources is protein-centric, and not PPI-centric. The PPIs are typically provided as lists of interactions of a given gene with links to interacting partners; they do not present a comprehensive view of the nature of both the proteins involved in the interactions. A web database that allows search and retrieval based on biomedical characteristics of PPIs is lacking, and is needed. We present Wiki-Pi (read Wiki-π, a web-based interface to a database of human PPIs, which allows users to retrieve interactions by their biomedical attributes such as their association to diseases, pathways, drugs and biological functions. Each retrieved PPI is shown with annotations of both of the participant proteins side-by-side, creating a basis to hypothesize the biological function facilitated by the interaction. Conceptually, it is a search engine for PPIs analogous to PubMed for scientific literature. Its usefulness in generating novel scientific hypotheses is demonstrated through the study of IGSF21, a little-known gene that was recently identified to be associated with diabetic retinopathy. Using Wiki-Pi, we infer that its association to diabetic retinopathy may be mediated through its interactions with the genes HSPB1, KRAS, TMSB4X and DGKD, and that it may be involved in cellular response to external stimuli, cytoskeletal organization and regulation of molecular activity. The website also provides a wiki-like capability allowing users

Use of Graph Database for the Integration of Heterogeneous Biological Data.

Science.gov (United States)

Yoon, Byoung-Ha; Kim, Seon-Kyu; Kim, Seon-Young

2017-03-01

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering

Directory of Open Access Journals (Sweden)

Lei Yang

2014-01-01

Full Text Available Cliques (maximal complete subnets in protein-protein interaction (PPI network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning.

Automated quantitative assessment of proteins' biological function in protein knowledge bases.

Science.gov (United States)

Mayr, Gabriele; Lepperdinger, Günter; Lackner, Peter

2008-01-01

Primary protein sequence data are archived in databases together with information regarding corresponding biological functions. In this respect, UniProt/Swiss-Prot is currently the most comprehensive collection and it is routinely cross-examined when trying to unravel the biological role of hypothetical proteins. Bioscientists frequently extract single entries and further evaluate those on a subjective basis. In lieu of a standardized procedure for scoring the existing knowledge regarding individual proteins, we here report about a computer-assisted method, which we applied to score the present knowledge about any given Swiss-Prot entry. Applying this quantitative score allows the comparison of proteins with respect to their sequence yet highlights the comprehension of functional data. pfs analysis may be also applied for quality control of individual entries or for database management in order to rank entry listings.

Automated Quantitative Assessment of Proteins' Biological Function in Protein Knowledge Bases

Directory of Open Access Journals (Sweden)

Gabriele Mayr

2008-01-01

Full Text Available Primary protein sequence data are archived in databases together with information regarding corresponding biological functions. In this respect, UniProt/Swiss-Prot is currently the most comprehensive collection and it is routinely cross-examined when trying to unravel the biological role of hypothetical proteins. Bioscientists frequently extract single entries and further evaluate those on a subjective basis. In lieu of a standardized procedure for scoring the existing knowledge regarding individual proteins, we here report about a computer-assisted method, which we applied to score the present knowledge about any given Swiss-Prot entry. Applying this quantitative score allows the comparison of proteins with respect to their sequence yet highlights the comprehension of functional data. pfs analysis may be also applied for quality control of individual entries or for database management in order to rank entry listings.

Proteomic analysis of Pinus radiata needles: 2-DE map and protein identification by LC/MS/MS and substitution-tolerant database searching.

Science.gov (United States)

Valledor, Luis; Castillejo, Maria A; Lenz, Christof; Rodríguez, Roberto; Cañal, Maria J; Jorrín, Jesús

2008-07-01

Pinus radiata is one of the most economically important forest tree species, with a worldwide production of around 370 million m (3) of wood per year. Current selection of elite trees to be used in conservation and breeding programes requires the physiological and molecular characterization of available populations. To identify key proteins related to tree growth, productivity and responses to environmental factors, a proteomic approach is being utilized. In this paper, we present the first report of the 2-DE protein reference map of physiologically mature P. radiata needles, as a basis for subsequent differential expression proteomic studies related to growth, development, biomass production and responses to stresses. After TCA/acetone protein extraction of needle tissue, 549 +/- 21 well-resolved spots were detected in Coommassie-stained gels within the 5-8 pH and 10-100 kDa M(r) ranges. The analytical and biological variance determined for 450 spots were of 31 and 42%, respectively. After LC/MS/MS analysis of in-gel tryptic digested spots, proteins were identified by using the novel Paragon algorithm that tolerates amino acid substitution in the first-pass search. It allowed the confident identification of 115 out of the 150 protein spots subjected to MS, quite unusual high percentage for a poor sequence database, as is the case of P. radiata. Proteins were classified into 12 or 18 groups based on their corresponding cell component or biological process/pathway categories, respectively. Carbohydrate metabolism and photosynthetic enzymes predominate in the 2-DE protein profile of P. radiata needles.

The MRC-5 human embryonal lung fibroblast two-dimensional gel cellular protein database: quantitative identification of polypeptides whose relative abundance differs between quiescent, proliferating and SV40 transformed cells

DEFF Research Database (Denmark)

Celis, J E; Dejgaard, K; Madsen, Peder

1990-01-01

interferon-induced proteins, were not detected in the master MRC-5 images. The identity of 36 of the transformation-sensitive proteins whose levels are up or down regulated by two times or more was determined and additional information can be transferred from the master transformed human epithelial amnion......, this comprehensive database will outline an integrated picture of the expression levels and properties of the thousands of protein components of organelles, pathways and cytoskeletal systems that may be directly or indirectly involved in properties associated with the transformed state. Udgivelsesdato: 1990-Dec...

Heterogeneous Biomedical Database Integration Using a Hybrid Strategy: A p53 Cancer Research Database

Directory of Open Access Journals (Sweden)

Vadim Y. Bichutskiy

2006-01-01

Full Text Available Complex problems in life science research give rise to multidisciplinary collaboration, and hence, to the need for heterogeneous database integration. The tumor suppressor p53 is mutated in close to 50% of human cancers, and a small drug-like molecule with the ability to restore native function to cancerous p53 mutants is a long-held medical goal of cancer treatment. The Cancer Research DataBase (CRDB was designed in support of a project to find such small molecules. As a cancer informatics project, the CRDB involved small molecule data, computational docking results, functional assays, and protein structure data. As an example of the hybrid strategy for data integration, it combined the mediation and data warehousing approaches. This paper uses the CRDB to illustrate the hybrid strategy as a viable approach to heterogeneous data integration in biomedicine, and provides a design method for those considering similar systems. More efficient data sharing implies increased productivity, and, hopefully, improved chances of success in cancer research. (Code and database schemas are freely downloadable, http://www.igb.uci.edu/research/research.html.

EchoBASE: an integrated post-genomic database for Escherichia coli.

Science.gov (United States)

Misra, Raju V; Horler, Richard S P; Reindl, Wolfgang; Goryanin, Igor I; Thomas, Gavin H

2005-01-01

EchoBASE (http://www.ecoli-york.org) is a relational database designed to contain and manipulate information from post-genomic experiments using the model bacterium Escherichia coli K-12. Its aim is to collate information from a wide range of sources to provide clues to the functions of the approximately 1500 gene products that have no confirmed cellular function. The database is built on an enhanced annotation of the updated genome sequence of strain MG1655 and the association of experimental data with the E.coli genes and their products. Experiments that can be held within EchoBASE include proteomics studies, microarray data, protein-protein interaction data, structural data and bioinformatics studies. EchoBASE also contains annotated information on 'orphan' enzyme activities from this microbe to aid characterization of the proteins that catalyse these elusive biochemical reactions.

Update of the androgen receptor gene mutations database.

Science.gov (United States)

Gottlieb, B; Beitel, L K; Lumbroso, R; Pinsky, L; Trifiro, M

1999-01-01

The current version of the androgen receptor (AR) gene mutations database is described. The total number of reported mutations has risen from 309 to 374 during the past year. We have expanded the database by adding information on AR-interacting proteins; and we have improved the database by identifying those mutation entries that have been updated. Mutations of unknown significance have now been reported in both the 5' and 3' untranslated regions of the AR gene, and in individuals who are somatic mosaics constitutionally. In addition, single nucleotide polymorphisms, including silent mutations, have been discovered in normal individuals and in individuals with male infertility. A mutation hotspot associated with prostatic cancer has been identified in exon 5. The database is available on the internet (http://www.mcgill.ca/androgendb/), from EMBL-European Bioinformatics Institute (ftp.ebi.ac.uk/pub/databases/androgen), or as a Macintosh FilemakerPro or Word file (MC33@musica.mcgill.ca). Copyright 1999 Wiley-Liss, Inc.

Knowledge discovery in variant databases using inductive logic programming.

Science.gov (United States)

Nguyen, Hoan; Luu, Tien-Dao; Poch, Olivier; Thompson, Julie D

2013-01-01

Understanding the effects of genetic variation on the phenotype of an individual is a major goal of biomedical research, especially for the development of diagnostics and effective therapeutic solutions. In this work, we describe the use of a recent knowledge discovery from database (KDD) approach using inductive logic programming (ILP) to automatically extract knowledge about human monogenic diseases. We extracted background knowledge from MSV3d, a database of all human missense variants mapped to 3D protein structure. In this study, we identified 8,117 mutations in 805 proteins with known three-dimensional structures that were known to be involved in human monogenic disease. Our results help to improve our understanding of the relationships between structural, functional or evolutionary features and deleterious mutations. Our inferred rules can also be applied to predict the impact of any single amino acid replacement on the function of a protein. The interpretable rules are available at http://decrypthon.igbmc.fr/kd4v/.

GPCR-SSFE: A comprehensive database of G-protein-coupled receptor template predictions and homology models

Directory of Open Access Journals (Sweden)

Kreuchwig Annika

2011-05-01

Full Text Available Abstract Background G protein-coupled receptors (GPCRs transduce a wide variety of extracellular signals to within the cell and therefore have a key role in regulating cell activity and physiological function. GPCR malfunction is responsible for a wide range of diseases including cancer, diabetes and hyperthyroidism and a large proportion of drugs on the market target these receptors. The three dimensional structure of GPCRs is important for elucidating the molecular mechanisms underlying these diseases and for performing structure-based drug design. Although structural data are restricted to only a handful of GPCRs, homology models can be used as a proxy for those receptors not having crystal structures. However, many researchers working on GPCRs are not experienced homology modellers and are therefore unable to benefit from the information that can be gleaned from such three-dimensional models. Here, we present a comprehensive database called the GPCR-SSFE, which provides initial homology models of the transmembrane helices for a large variety of family A GPCRs. Description Extending on our previous theoretical work, we have developed an automated pipeline for GPCR homology modelling and applied it to a large set of family A GPCR sequences. Our pipeline is a fragment-based approach that exploits available family A crystal structures. The GPCR-SSFE database stores the template predictions, sequence alignments, identified sequence and structure motifs and homology models for 5025 family A GPCRs. Users are able to browse the GPCR dataset according to their pharmacological classification or search for results using a UniProt entry name. It is also possible for a user to submit a GPCR sequence that is not contained in the database for analysis and homology model building. The models can be viewed using a Jmol applet and are also available for download along with the alignments. Conclusions The data provided by GPCR-SSFE are useful for investigating

GPCR-SSFE: a comprehensive database of G-protein-coupled receptor template predictions and homology models.

Science.gov (United States)

Worth, Catherine L; Kreuchwig, Annika; Kleinau, Gunnar; Krause, Gerd

2011-05-23

G protein-coupled receptors (GPCRs) transduce a wide variety of extracellular signals to within the cell and therefore have a key role in regulating cell activity and physiological function. GPCR malfunction is responsible for a wide range of diseases including cancer, diabetes and hyperthyroidism and a large proportion of drugs on the market target these receptors. The three dimensional structure of GPCRs is important for elucidating the molecular mechanisms underlying these diseases and for performing structure-based drug design. Although structural data are restricted to only a handful of GPCRs, homology models can be used as a proxy for those receptors not having crystal structures. However, many researchers working on GPCRs are not experienced homology modellers and are therefore unable to benefit from the information that can be gleaned from such three-dimensional models. Here, we present a comprehensive database called the GPCR-SSFE, which provides initial homology models of the transmembrane helices for a large variety of family A GPCRs. Extending on our previous theoretical work, we have developed an automated pipeline for GPCR homology modelling and applied it to a large set of family A GPCR sequences. Our pipeline is a fragment-based approach that exploits available family A crystal structures. The GPCR-SSFE database stores the template predictions, sequence alignments, identified sequence and structure motifs and homology models for 5025 family A GPCRs. Users are able to browse the GPCR dataset according to their pharmacological classification or search for results using a UniProt entry name. It is also possible for a user to submit a GPCR sequence that is not contained in the database for analysis and homology model building. The models can be viewed using a Jmol applet and are also available for download along with the alignments. The data provided by GPCR-SSFE are useful for investigating general and detailed sequence-structure-function relationships

A Bayesian method for identifying missing enzymes in predicted metabolic pathway databases

Directory of Open Access Journals (Sweden)

Karp Peter D

2004-06-01

Full Text Available Abstract Background The PathoLogic program constructs Pathway/Genome databases by using a genome's annotation to predict the set of metabolic pathways present in an organism. PathoLogic determines the set of reactions composing those pathways from the enzymes annotated in the organism's genome. Most annotation efforts fail to assign function to 40–60% of sequences. In addition, large numbers of sequences may have non-specific annotations (e.g., thiolase family protein. Pathway holes occur when a genome appears to lack the enzymes needed to catalyze reactions in a pathway. If a protein has not been assigned a specific function during the annotation process, any reaction catalyzed by that protein will appear as a missing enzyme or pathway hole in a Pathway/Genome database. Results We have developed a method that efficiently combines homology and pathway-based evidence to identify candidates for filling pathway holes in Pathway/Genome databases. Our program not only identifies potential candidate sequences for pathway holes, but combines data from multiple, heterogeneous sources to assess the likelihood that a candidate has the required function. Our algorithm emulates the manual sequence annotation process, considering not only evidence from homology searches, but also considering evidence from genomic context (i.e., is the gene part of an operon? and functional context (e.g., are there functionally-related genes nearby in the genome? to determine the posterior belief that a candidate has the required function. The method can be applied across an entire metabolic pathway network and is generally applicable to any pathway database. The program uses a set of sequences encoding the required activity in other genomes to identify candidate proteins in the genome of interest, and then evaluates each candidate by using a simple Bayes classifier to determine the probability that the candidate has the desired function. We achieved 71% precision at a

Dr. PIAS: an integrative system for assessing the druggability of protein-protein interactions

Directory of Open Access Journals (Sweden)

Furuya Toshio

2011-02-01

Full Text Available Abstract Background The amount of data on protein-protein interactions (PPIs available in public databases and in the literature has rapidly expanded in recent years. PPI data can provide useful information for researchers in pharmacology and medicine as well as those in interactome studies. There is urgent need for a novel methodology or software allowing the efficient utilization of PPI data in pharmacology and medicine. Results To address this need, we have developed the 'Druggable Protein-protein Interaction Assessment System' (Dr. PIAS. Dr. PIAS has a meta-database that stores various types of information (tertiary structures, drugs/chemicals, and biological functions associated with PPIs retrieved from public sources. By integrating this information, Dr. PIAS assesses whether a PPI is druggable as a target for small chemical ligands by using a supervised machine-learning method, support vector machine (SVM. Dr. PIAS holds not only known druggable PPIs but also all PPIs of human, mouse, rat, and human immunodeficiency virus (HIV proteins identified to date. Conclusions The design concept of Dr. PIAS is distinct from other published PPI databases in that it focuses on selecting the PPIs most likely to make good drug targets, rather than merely collecting PPI data.

The PANTHER database of protein families, subfamilies, functions and pathways

OpenAIRE

Mi, Huaiyu; Lazareva-Ulitsky, Betty; Loo, Rozina; Kejariwal, Anish; Vandergriff, Jody; Rabkin, Steven; Guo, Nan; Muruganujan, Anushya; Doremieux, Olivier; Campbell, Michael J.; Kitano, Hiroaki; Thomas, Paul D.

2004-01-01

PANTHER is a large collection of protein families that have been subdivided into functionally related subfamilies, using human expertise. These subfamilies model the divergence of specific functions within protein families, allowing more accurate association with function (ontology terms and pathways), as well as inference of amino acids important for functional specificity. Hidden Markov models (HMMs) are built for each family and subfamily for classifying additional protein sequences. The l...

Revisiting the description of Protein-Protein interfaces. Part II: Experimental study

OpenAIRE

Cazals , Frédéric; Proust , Flavien

2006-01-01

This paper provides a detailed experimental study of an interface model developed in the companion article F. Cazals and F. Proust, Revisiting the description of Protein-Protein interfaces. Part I: algorithms. Our experimental study is concerned with the usual database of protein-protein complexes, split into five families (Proteases, Immune system, Enzyme Complexes, Signal transduction, Misc.) Our findings, which bear some contradictions with usual statements are the following: (i)Connectivi...

PPI finder: a mining tool for human protein-protein interactions.

Directory of Open Access Journals (Sweden)

Min He

Full Text Available BACKGROUND: The exponential increase of published biomedical literature prompts the use of text mining tools to manage the information overload automatically. One of the most common applications is to mine protein-protein interactions (PPIs from PubMed abstracts. Currently, most tools in mining PPIs from literature are using co-occurrence-based approaches or rule-based approaches. Hybrid methods (frame-based approaches by combining these two methods may have better performance in predicting PPIs. However, the predicted PPIs from these methods are rarely evaluated by known PPI databases and co-occurred terms in Gene Ontology (GO database. METHODOLOGY/PRINCIPAL FINDINGS: We here developed a web-based tool, PPI Finder, to mine human PPIs from PubMed abstracts based on their co-occurrences and interaction words, followed by evidences in human PPI databases and shared terms in GO database. Only 28% of the co-occurred pairs in PubMed abstracts appeared in any of the commonly used human PPI databases (HPRD, BioGRID and BIND. On the other hand, of the known PPIs in HPRD, 69% showed co-occurrences in the literature, and 65% shared GO terms. CONCLUSIONS: PPI Finder provides a useful tool for biologists to uncover potential novel PPIs. It is freely accessible at http://liweilab.genetics.ac.cn/tm/.

Analysis of commercial and public bioactivity databases.

Science.gov (United States)

Tiikkainen, Pekka; Franke, Lutz

2012-02-27

Activity data for small molecules are invaluable in chemoinformatics. Various bioactivity databases exist containing detailed information of target proteins and quantitative binding data for small molecules extracted from journals and patents. In the current work, we have merged several public and commercial bioactivity databases into one bioactivity metabase. The molecular presentation, target information, and activity data of the vendor databases were standardized. The main motivation of the work was to create a single relational database which allows fast and simple data retrieval by in-house scientists. Second, we wanted to know the amount of overlap between databases by commercial and public vendors to see whether the former contain data complementing the latter. Third, we quantified the degree of inconsistency between data sources by comparing data points derived from the same scientific article cited by more than one vendor. We found that each data source contains unique data which is due to different scientific articles cited by the vendors. When comparing data derived from the same article we found that inconsistencies between the vendors are common. In conclusion, using databases of different vendors is still useful since the data overlap is not complete. It should be noted that this can be partially explained by the inconsistencies and errors in the source data.

Integration of curated databases to identify genotype-phenotype associations

Directory of Open Access Journals (Sweden)

Li Jianrong

2006-10-01

Full Text Available Abstract Background The ability to rapidly characterize an unknown microorganism is critical in both responding to infectious disease and biodefense. To do this, we need some way of anticipating an organism's phenotype based on the molecules encoded by its genome. However, the link between molecular composition (i.e. genotype and phenotype for microbes is not obvious. While there have been several studies that address this challenge, none have yet proposed a large-scale method integrating curated biological information. Here we utilize a systematic approach to discover genotype-phenotype associations that combines phenotypic information from a biomedical informatics database, GIDEON, with the molecular information contained in National Center for Biotechnology Information's Clusters of Orthologous Groups database (NCBI COGs. Results Integrating the information in the two databases, we are able to correlate the presence or absence of a given protein in a microbe with its phenotype as measured by certain morphological characteristics or survival in a particular growth media. With a 0.8 correlation score threshold, 66% of the associations found were confirmed by the literature and at a 0.9 correlation threshold, 86% were positively verified. Conclusion Our results suggest possible phenotypic manifestations for proteins biochemically associated with sugar metabolism and electron transport. Moreover, we believe our approach can be extended to linking pathogenic phenotypes with functionally related proteins.

Mapping and identification of HeLa cell proteins separated by immobilized pH-gradient two-dimensional gel electrophoresis and construction of a two-dimensional polyacrylamide gel electrophoresis database

DEFF Research Database (Denmark)

Shaw, AC; Rossel Larsen, M; Roepstorff, P

1999-01-01

The HeLa cell line, a human adenocarcinoma, is used in many research fields, since it can be infected with a wide range of viruses and intracellular bacteria. Therefore, the mapping of HeLa cell proteins is useful for the investigation of parasite host cell interactions. Because of the recent imp...... these and future data accessible for interlaboratory comparison, we constructed a 2-D PAGE database on the World Wide Web....... the mapping of [35S]methionine/cysteine-labeled HeLa cell proteins with the 2-D PAGE (IPG)-system, using matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS) and N-terminal sequencing for protein identification. To date 21 proteins have been identified and mapped. In order to make...

Update History of This Database - Trypanosomes Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Trypanosomes Database Update History of This Database Date Update contents 2014/05/07 The co...ntact information is corrected. The features and manner of utilization of the database are corrected. 2014/02/04 Trypanosomes Databas...e English archive site is opened. 2011/04/04 Trypanosomes Database ( http://www.tan...paku.org/tdb/ ) is opened. About This Database Database Description Download Lice...nse Update History of This Database Site Policy | Contact Us Update History of This Database - Trypanosomes Database | LSDB Archive ...

Using the TIGR gene index databases for biological discovery.

Science.gov (United States)

Lee, Yuandan; Quackenbush, John

2003-11-01

The TIGR Gene Index web pages provide access to analyses of ESTs and gene sequences for nearly 60 species, as well as a number of resources derived from these. Each species-specific database is presented using a common format with a homepage. A variety of methods exist that allow users to search each species-specific database. Methods implemented currently include nucleotide or protein sequence queries using WU-BLAST, text-based searches using various sequence identifiers, searches by gene, tissue and library name, and searches using functional classes through Gene Ontology assignments. This protocol provides guidance for using the Gene Index Databases to extract information.

Protein annotation from protein interaction networks and Gene Ontology.

Science.gov (United States)

Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

2011-10-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

[Establishment of a comprehensive database for laryngeal cancer related genes and the miRNAs].

Science.gov (United States)

Li, Mengjiao; E, Qimin; Liu, Jialin; Huang, Tingting; Liang, Chuanyu

2015-09-01

By collecting and analyzing the laryngeal cancer related genes and the miRNAs, to build a comprehensive laryngeal cancer-related gene database, which differs from the current biological information database with complex and clumsy structure and focuses on the theme of gene and miRNA, and it could make the research and teaching more convenient and efficient. Based on the B/S architecture, using Apache as a Web server, MySQL as coding language of database design and PHP as coding language of web design, a comprehensive database for laryngeal cancer-related genes was established, providing with the gene tables, protein tables, miRNA tables and clinical information tables of the patients with laryngeal cancer. The established database containsed 207 laryngeal cancer related genes, 243 proteins, 26 miRNAs, and their particular information such as mutations, methylations, diversified expressions, and the empirical references of laryngeal cancer relevant molecules. The database could be accessed and operated via the Internet, by which browsing and retrieval of the information were performed. The database were maintained and updated regularly. The database for laryngeal cancer related genes is resource-integrated and user-friendly, providing a genetic information query tool for the study of laryngeal cancer.

ExtraTrain: a database of Extragenic regions and Transcriptional information in prokaryotic organisms

Science.gov (United States)

Pareja, Eduardo; Pareja-Tobes, Pablo; Manrique, Marina; Pareja-Tobes, Eduardo; Bonal, Javier; Tobes, Raquel

2006-01-01

Background Transcriptional regulation processes are the principal mechanisms of adaptation in prokaryotes. In these processes, the regulatory proteins and the regulatory DNA signals located in extragenic regions are the key elements involved. As all extragenic spaces are putative regulatory regions, ExtraTrain covers all extragenic regions of available genomes and regulatory proteins from bacteria and archaea included in the UniProt database. Description ExtraTrain provides integrated and easily manageable information for 679816 extragenic regions and for the genes delimiting each of them. In addition ExtraTrain supplies a tool to explore extragenic regions, named Palinsight, oriented to detect and search palindromic patterns. This interactive visual tool is totally integrated in the database, allowing the search for regulatory signals in user defined sets of extragenic regions. The 26046 regulatory proteins included in ExtraTrain belong to the families AraC/XylS, ArsR, AsnC, Cold shock domain, CRP-FNR, DeoR, GntR, IclR, LacI, LuxR, LysR, MarR, MerR, NtrC/Fis, OmpR and TetR. The database follows the InterPro criteria to define these families. The information about regulators includes manually curated sets of references specifically associated to regulator entries. In order to achieve a sustainable and maintainable knowledge database ExtraTrain is a platform open to the contribution of knowledge by the scientific community providing a system for the incorporation of textual knowledge. Conclusion ExtraTrain is a new database for exploring Extragenic regions and Transcriptional information in bacteria and archaea. ExtraTrain database is available at . PMID:16539733

Systematization of the protein sequence diversity in enzymes related to secondary metabolic pathways in plants, in the context of big data biology inspired by the KNApSAcK motorcycle database.

Science.gov (United States)

Ikeda, Shun; Abe, Takashi; Nakamura, Yukiko; Kibinge, Nelson; Hirai Morita, Aki; Nakatani, Atsushi; Ono, Naoaki; Ikemura, Toshimichi; Nakamura, Kensuke; Altaf-Ul-Amin, Md; Kanaya, Shigehiko

2013-05-01

Biology is increasingly becoming a data-intensive science with the recent progress of the omics fields, e.g. genomics, transcriptomics, proteomics and metabolomics. The species-metabolite relationship database, KNApSAcK Core, has been widely utilized and cited in metabolomics research, and chronological analysis of that research work has helped to reveal recent trends in metabolomics research. To meet the needs of these trends, the KNApSAcK database has been extended by incorporating a secondary metabolic pathway database called Motorcycle DB. We examined the enzyme sequence diversity related to secondary metabolism by means of batch-learning self-organizing maps (BL-SOMs). Initially, we constructed a map by using a big data matrix consisting of the frequencies of all possible dipeptides in the protein sequence segments of plants and bacteria. The enzyme sequence diversity of the secondary metabolic pathways was examined by identifying clusters of segments associated with certain enzyme groups in the resulting map. The extent of diversity of 15 secondary metabolic enzyme groups is discussed. Data-intensive approaches such as BL-SOM applied to big data matrices are needed for systematizing protein sequences. Handling big data has become an inevitable part of biology.

GIS: a comprehensive source for protein structure similarities.

Science.gov (United States)

Guerler, Aysam; Knapp, Ernst-Walter

2010-07-01

A web service for analysis of protein structures that are sequentially or non-sequentially similar was generated. Recently, the non-sequential structure alignment algorithm GANGSTA+ was introduced. GANGSTA+ can detect non-sequential structural analogs for proteins stated to possess novel folds. Since GANGSTA+ ignores the polypeptide chain connectivity of secondary structure elements (i.e. alpha-helices and beta-strands), it is able to detect structural similarities also between proteins whose sequences were reshuffled during evolution. GANGSTA+ was applied in an all-against-all comparison on the ASTRAL40 database (SCOP version 1.75), which consists of >10,000 protein domains yielding about 55 x 10(6) possible protein structure alignments. Here, we provide the resulting protein structure alignments as a public web-based service, named GANGSTA+ Internet Services (GIS). We also allow to browse the ASTRAL40 database of protein structures with GANGSTA+ relative to an externally given protein structure using different constraints to select specific results. GIS allows us to analyze protein structure families according to the SCOP classification scheme. Additionally, users can upload their own protein structures for pairwise protein structure comparison, alignment against all protein structures of the ASTRAL40 database (SCOP version 1.75) or symmetry analysis. GIS is publicly available at http://agknapp.chemie.fu-berlin.de/gplus.

Creating a specialist protein resource network: a meeting report for the protein bioinformatics and community resources retreat

DEFF Research Database (Denmark)

Babbitt, Patricia C.; Bagos, Pantelis G.; Bairoch, Amos

2015-01-01

During 11–12 August 2014, a Protein Bioinformatics and Community Resources Retreat was held at the Wellcome Trust Genome Campus in Hinxton, UK. This meeting brought together the principal investigators of several specialized protein resources (such as CAZy, TCDB and MEROPS) as well as those from...... protein databases from the large Bioinformatics centres (including UniProt and RefSeq). The retreat was divided into five sessions: (1) key challenges, (2) the databases represented, (3) best practices for maintenance and curation, (4) information flow to and from large data centers and (5) communication...

Targeting protein-protein interactions for parasite control.

Directory of Open Access Journals (Sweden)

Christina M Taylor

2011-04-01

Full Text Available Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank. EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite and B. malayi (H. sapiens parasite, which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly

BSDB: the Biomolecule Stretching Database

Science.gov (United States)

Cieplak, Marek; Sikora, Mateusz; Sulkowska, Joanna I.; Witkowski, Bartlomiej

2011-03-01

Despite more than a decade of experiments on single biomolecule manipulation, mechanical properties of only several scores of proteins have been measured. A characteristic scale of the force of resistance to stretching, Fmax , has been found to range between ~ 10 and 480 pN. The Biomolecule Stretching Data Base (BSDB) described here provides information about expected values of Fmax for, currently, 17 134 proteins. The values and other characteristics of the unfolding proces, including the nature of identified mechanical clamps, are available at www://info.ifpan.edu.pl/BSDB/. They have been obtained through simulations within a structure-based model which correlates satisfactorily with the available experimental data on stretching. BSDB also lists experimental data and results of the existing all-atom simulations. The database offers a Protein-Data-Bank-wide guide to mechano-stability of proteins. Its description is provided by a forthcoming Nucleic Acids Research paper. Supported by EC FUNMOL project FP7-NMP-2007-SMALL-1, and European Regional Development Fund: Innovative Economy (POIG.01.01.02-00-008/08).

Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences.

Science.gov (United States)

Mi, Tian; Merlin, Jerlin Camilus; Deverasetty, Sandeep; Gryk, Michael R; Bill, Travis J; Brooks, Andrew W; Lee, Logan Y; Rathnayake, Viraj; Ross, Christian A; Sargeant, David P; Strong, Christy L; Watts, Paula; Rajasekaran, Sanguthevar; Schiller, Martin R

2012-01-01

Minimotif Miner (MnM available at http://minimotifminer.org or http://mnm.engr.uconn.edu) is an online database for identifying new minimotifs in protein queries. Minimotifs are short contiguous peptide sequences that have a known function in at least one protein. Here we report the third release of the MnM database which has now grown 60-fold to approximately 300,000 minimotifs. Since short minimotifs are by their nature not very complex we also summarize a new set of false-positive filters and linear regression scoring that vastly enhance minimotif prediction accuracy on a test data set. This online database can be used to predict new functions in proteins and causes of disease.

Seed Storage Proteins as a System for Teaching Protein Identification by Mass Spectrometry in Biochemistry Laboratory

Science.gov (United States)

Wilson, Karl A.; Tan-Wilson, Anna

2013-01-01

Mass spectrometry (MS) has become an important tool in studying biological systems. One application is the identification of proteins and peptides by the matching of peptide and peptide fragment masses to the sequences of proteins in protein sequence databases. Often prior protein separation of complex protein mixtures by 2D-PAGE is needed,…

Update History of This Database - Arabidopsis Phenome Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Arabidopsis Phenome Database Update History of This Database Date Update contents 2017/02/27 Arabidopsis Phenome Data...base English archive site is opened. - Arabidopsis Phenome Database (http://jphenom...e.info/?page_id=95) is opened. About This Database Database Description Download License Update History of This Database... Site Policy | Contact Us Update History of This Database - Arabidopsis Phenome Database | LSDB Archive ...

Exploiting genomic data to identify proteins involved in abalone reproduction.

Science.gov (United States)

Mendoza-Porras, Omar; Botwright, Natasha A; McWilliam, Sean M; Cook, Mathew T; Harris, James O; Wijffels, Gene; Colgrave, Michelle L

2014-08-28

Aside from their critical role in reproduction, abalone gonads serve as an indicator of sexual maturity and energy balance, two key considerations for effective abalone culture. Temperate abalone farmers face issues with tank restocking with highly marketable abalone owing to inefficient spawning induction methods. The identification of key proteins in sexually mature abalone will serve as the foundation for a greater understanding of reproductive biology. Addressing this knowledge gap is the first step towards improving abalone aquaculture methods. Proteomic profiling of female and male gonads of greenlip abalone, Haliotis laevigata, was undertaken using liquid chromatography-mass spectrometry. Owing to the incomplete nature of abalone protein databases, in addition to searching against two publicly available databases, a custom database comprising genomic data was used. Overall, 162 and 110 proteins were identified in females and males respectively with 40 proteins common to both sexes. For proteins involved in sexual maturation, sperm and egg structure, motility, acrosomal reaction and fertilization, 23 were identified only in females, 18 only in males and 6 were common. Gene ontology analysis revealed clear differences between the female and male protein profiles reflecting a higher rate of protein synthesis in the ovary and higher metabolic activity in the testis. A comprehensive mass spectrometry-based analysis was performed to profile the abalone gonad proteome providing the foundation for future studies of reproduction in abalone. Key proteins involved in both reproduction and energy balance were identified. Genomic resources were utilised to build a database of molluscan proteins yielding >60% more protein identifications than in a standard workflow employing public protein databases. Copyright © 2014 Elsevier B.V. All rights reserved.

Text mining facilitates database curation - extraction of mutation-disease associations from Bio-medical literature.

Science.gov (United States)

Ravikumar, Komandur Elayavilli; Wagholikar, Kavishwar B; Li, Dingcheng; Kocher, Jean-Pierre; Liu, Hongfang

2015-06-06

Advances in the next generation sequencing technology has accelerated the pace of individualized medicine (IM), which aims to incorporate genetic/genomic information into medicine. One immediate need in interpreting sequencing data is the assembly of information about genetic variants and their corresponding associations with other entities (e.g., diseases or medications). Even with dedicated effort to capture such information in biological databases, much of this information remains 'locked' in the unstructured text of biomedical publications. There is a substantial lag between the publication and the subsequent abstraction of such information into databases. Multiple text mining systems have been developed, but most of them focus on the sentence level association extraction with performance evaluation based on gold standard text annotations specifically prepared for text mining systems. We developed and evaluated a text mining system, MutD, which extracts protein mutation-disease associations from MEDLINE abstracts by incorporating discourse level analysis, using a benchmark data set extracted from curated database records. MutD achieves an F-measure of 64.3% for reconstructing protein mutation disease associations in curated database records. Discourse level analysis component of MutD contributed to a gain of more than 10% in F-measure when compared against the sentence level association extraction. Our error analysis indicates that 23 of the 64 precision errors are true associations that were not captured by database curators and 68 of the 113 recall errors are caused by the absence of associated disease entities in the abstract. After adjusting for the defects in the curated database, the revised F-measure of MutD in association detection reaches 81.5%. Our quantitative analysis reveals that MutD can effectively extract protein mutation disease associations when benchmarking based on curated database records. The analysis also demonstrates that incorporating

Refactoring databases evolutionary database design

CERN Document Server

Ambler, Scott W

2006-01-01

Refactoring has proven its value in a wide range of development projects–helping software professionals improve system designs, maintainability, extensibility, and performance. Now, for the first time, leading agile methodologist Scott Ambler and renowned consultant Pramodkumar Sadalage introduce powerful refactoring techniques specifically designed for database systems. Ambler and Sadalage demonstrate how small changes to table structures, data, stored procedures, and triggers can significantly enhance virtually any database design–without changing semantics. You’ll learn how to evolve database schemas in step with source code–and become far more effective in projects relying on iterative, agile methodologies. This comprehensive guide and reference helps you overcome the practical obstacles to refactoring real-world databases by covering every fundamental concept underlying database refactoring. Using start-to-finish examples, the authors walk you through refactoring simple standalone databas...

PrionHome: a database of prions and other sequences relevant to prion phenomena.

Directory of Open Access Journals (Sweden)

Djamel Harbi

Full Text Available Prions are units of propagation of an altered state of a protein or proteins; prions can propagate from organism to organism, through cooption of other protein copies. Prions contain no necessary nucleic acids, and are important both as both pathogenic agents, and as a potential force in epigenetic phenomena. The original prions were derived from a misfolded form of the mammalian Prion Protein PrP. Infection by these prions causes neurodegenerative diseases. Other prions cause non-Mendelian inheritance in budding yeast, and sometimes act as diseases of yeast. We report the bioinformatic construction of the PrionHome, a database of >2000 prion-related sequences. The data was collated from various public and private resources and filtered for redundancy. The data was then processed according to a transparent classification system of prionogenic sequences (i.e., sequences that can make prions, prionoids (i.e., proteins that propagate like prions between individual cells, and other prion-related phenomena. There are eight PrionHome classifications for sequences. The first four classifications are derived from experimental observations: prionogenic sequences, prionoids, other prion-related phenomena, and prion interactors. The second four classifications are derived from sequence analysis: orthologs, paralogs, pseudogenes, and candidate-prionogenic sequences. Database entries list: supporting information for PrionHome classifications, prion-determinant areas (where relevant, and disordered and compositionally-biased regions. Also included are literature references for the PrionHome classifications, transcripts and genomic coordinates, and structural data (including comparative models made for the PrionHome from manually curated alignments. We provide database usage examples for both vertebrate and fungal prion contexts. Using the database data, we have performed a detailed analysis of the compositional biases in known budding-yeast prionogenic

PrionHome: a database of prions and other sequences relevant to prion phenomena.

Science.gov (United States)

Harbi, Djamel; Parthiban, Marimuthu; Gendoo, Deena M A; Ehsani, Sepehr; Kumar, Manish; Schmitt-Ulms, Gerold; Sowdhamini, Ramanathan; Harrison, Paul M

2012-01-01

Prions are units of propagation of an altered state of a protein or proteins; prions can propagate from organism to organism, through cooption of other protein copies. Prions contain no necessary nucleic acids, and are important both as both pathogenic agents, and as a potential force in epigenetic phenomena. The original prions were derived from a misfolded form of the mammalian Prion Protein PrP. Infection by these prions causes neurodegenerative diseases. Other prions cause non-Mendelian inheritance in budding yeast, and sometimes act as diseases of yeast. We report the bioinformatic construction of the PrionHome, a database of >2000 prion-related sequences. The data was collated from various public and private resources and filtered for redundancy. The data was then processed according to a transparent classification system of prionogenic sequences (i.e., sequences that can make prions), prionoids (i.e., proteins that propagate like prions between individual cells), and other prion-related phenomena. There are eight PrionHome classifications for sequences. The first four classifications are derived from experimental observations: prionogenic sequences, prionoids, other prion-related phenomena, and prion interactors. The second four classifications are derived from sequence analysis: orthologs, paralogs, pseudogenes, and candidate-prionogenic sequences. Database entries list: supporting information for PrionHome classifications, prion-determinant areas (where relevant), and disordered and compositionally-biased regions. Also included are literature references for the PrionHome classifications, transcripts and genomic coordinates, and structural data (including comparative models made for the PrionHome from manually curated alignments). We provide database usage examples for both vertebrate and fungal prion contexts. Using the database data, we have performed a detailed analysis of the compositional biases in known budding-yeast prionogenic sequences, showing

Update History of This Database - SKIP Stemcell Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us SKIP Stemcell Database Update History of This Database Date Update contents 2017/03/13 SKIP Stemcell Database... English archive site is opened. 2013/03/29 SKIP Stemcell Database ( https://www.skip.med.k...eio.ac.jp/SKIPSearch/top?lang=en ) is opened. About This Database Database Description Download License Update History of This Databa...se Site Policy | Contact Us Update History of This Database - SKIP Stemcell Database | LSDB Archive ...

RICD: A rice indica cDNA database resource for rice functional genomics

Directory of Open Access Journals (Sweden)

Zhang Qifa

2008-11-01

Full Text Available Abstract Background The Oryza sativa L. indica subspecies is the most widely cultivated rice. During the last few years, we have collected over 20,000 putative full-length cDNAs and over 40,000 ESTs isolated from various cDNA libraries of two indica varieties Guangluai 4 and Minghui 63. A database of the rice indica cDNAs was therefore built to provide a comprehensive web data source for searching and retrieving the indica cDNA clones. Results Rice Indica cDNA Database (RICD is an online MySQL-PHP driven database with a user-friendly web interface. It allows investigators to query the cDNA clones by keyword, genome position, nucleotide or protein sequence, and putative function. It also provides a series of information, including sequences, protein domain annotations, similarity search results, SNPs and InDels information, and hyperlinks to gene annotation in both The Rice Annotation Project Database (RAP-DB and The TIGR Rice Genome Annotation Resource, expression atlas in RiceGE and variation report in Gramene of each cDNA. Conclusion The online rice indica cDNA database provides cDNA resource with comprehensive information to researchers for functional analysis of indica subspecies and for comparative genomics. The RICD database is available through our website http://www.ncgr.ac.cn/ricd.

Cyclebase 3.0: a multi-organism database on cell-cycle regulation and phenotypes

DEFF Research Database (Denmark)

Santos Delgado, Alberto; Wernersson, Rasmus; Jensen, Lars Juhl

2015-01-01

3.0, we have updated the content of the database to reflect changes to genome annotation, added new mRNAand protein expression data, and integrated cell-cycle phenotype information from high-content screens and model-organism databases. The new version of Cyclebase also features a new web interface...

DMPD: LPS-binding proteins and receptors. [Dynamic Macrophage Pathway CSML Database

Lifescience Database Archive (English)

Full Text Available 9665271 LPS-binding proteins and receptors. Fenton MJ, Golenbock DT. J Leukoc Biol.... 1998 Jul;64(1):25-32. (.png) (.svg) (.html) (.csml) Show LPS-binding proteins and receptors. PubmedID 9665271 Title LPS-binding prot...eins and receptors. Authors Fenton MJ, Golenbock DT. Publication J Leukoc Biol. 199

Database design and database administration for a kindergarten

OpenAIRE

Vítek, Daniel

2009-01-01

The bachelor thesis deals with creation of database design for a standard kindergarten, installation of the designed database into the database system Oracle Database 10g Express Edition and demonstration of the administration tasks in this database system. The verification of the database was proved by a developed access application.

WGDB: Wood Gene Database with search interface.

Science.gov (United States)

Goyal, Neha; Ginwal, H S

2014-01-01

Wood quality can be defined in terms of particular end use with the involvement of several traits. Over the last fifteen years researchers have assessed the wood quality traits in forest trees. The wood quality was categorized as: cell wall biochemical traits, fibre properties include the microfibril angle, density and stiffness in loblolly pine [1]. The user friendly and an open-access database has been developed named Wood Gene Database (WGDB) for describing the wood genes along the information of protein and published research articles. It contains 720 wood genes from species namely Pinus, Deodar, fast growing trees namely Poplar, Eucalyptus. WGDB designed to encompass the majority of publicly accessible genes codes for cellulose, hemicellulose and lignin in tree species which are responsive to wood formation and quality. It is an interactive platform for collecting, managing and searching the specific wood genes; it also enables the data mining relate to the genomic information specifically in Arabidopsis thaliana, Populus trichocarpa, Eucalyptus grandis, Pinus taeda, Pinus radiata, Cedrus deodara, Cedrus atlantica. For user convenience, this database is cross linked with public databases namely NCBI, EMBL & Dendrome with the search engine Google for making it more informative and provides bioinformatics tools named BLAST,COBALT. The database is freely available on www.wgdb.in.

Database Description - Open TG-GATEs Pathological Image Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Open TG-GATEs Pathological Image Database Database Description General information of database Database... name Open TG-GATEs Pathological Image Database Alternative name - DOI 10.18908/lsdba.nbdc00954-0...iomedical Innovation 7-6-8, Saito-asagi, Ibaraki-city, Osaka 567-0085, Japan TEL:81-72-641-9826 Email: Database... classification Toxicogenomics Database Organism Taxonomy Name: Rattus norvegi... Article title: Author name(s): Journal: External Links: Original website information Database

Specialized microbial databases for inductive exploration of microbial genome sequences

Directory of Open Access Journals (Sweden)

Cabau Cédric

2005-02-01

Full Text Available Abstract Background The enormous amount of genome sequence data asks for user-oriented databases to manage sequences and annotations. Queries must include search tools permitting function identification through exploration of related objects. Methods The GenoList package for collecting and mining microbial genome databases has been rewritten using MySQL as the database management system. Functions that were not available in MySQL, such as nested subquery, have been implemented. Results Inductive reasoning in the study of genomes starts from "islands of knowledge", centered around genes with some known background. With this concept of "neighborhood" in mind, a modified version of the GenoList structure has been used for organizing sequence data from prokaryotic genomes of particular interest in China. GenoChore http://bioinfo.hku.hk/genochore.html, a set of 17 specialized end-user-oriented microbial databases (including one instance of Microsporidia, Encephalitozoon cuniculi, a member of Eukarya has been made publicly available. These databases allow the user to browse genome sequence and annotation data using standard queries. In addition they provide a weekly update of searches against the world-wide protein sequences data libraries, allowing one to monitor annotation updates on genes of interest. Finally, they allow users to search for patterns in DNA or protein sequences, taking into account a clustering of genes into formal operons, as well as providing extra facilities to query sequences using predefined sequence patterns. Conclusion This growing set of specialized microbial databases organize data created by the first Chinese bacterial genome programs (ThermaList, Thermoanaerobacter tencongensis, LeptoList, with two different genomes of Leptospira interrogans and SepiList, Staphylococcus epidermidis associated to related organisms for comparison.

PATACSDB—the database of polyA translational attenuators in coding sequences

Directory of Open Access Journals (Sweden)

Malgorzata Habich

2016-02-01

Full Text Available Recent additions to the repertoire of gene expression regulatory mechanisms are polyadenylate (polyA tracks encoding for poly-lysine runs in protein sequences. Such tracks stall the translation apparatus and induce frameshifting independently of the effects of charged nascent poly-lysine sequence on the ribosome exit channel. As such, they substantially influence the stability of mRNA and the amount of protein produced from a given transcript. Single base changes in these regions are enough to exert a measurable response on both protein and mRNA abundance; this makes each of these sequences a potentially interesting case study for the effects of synonymous mutation, gene dosage balance and natural frameshifting. Here we present PATACSDB, a resource that contain a comprehensive list of polyA tracks from over 250 eukaryotic genomes. Our data is based on the Ensembl genomic database of coding sequences and filtered with algorithm of 12A-1 which selects sequences of polyA tracks with a minimal length of 12 A’s allowing for one mismatched base. The PATACSDB database is accessible at: http://sysbio.ibb.waw.pl/patacsdb. The source code is available at http://github.com/habich/PATACSDB, and it includes the scripts with which the database can be recreated.

Brug af en translationel database i en klinisk afdeling

DEFF Research Database (Denmark)

Højfeldt, Anne Dirks; Johnsen, Hans E; Bøgsted, Martin

2010-01-01

In haematology it is assumed that integrative analysis of global gene expression, protein and cell profiles as well as clinical data will lead to the development of new diagnostic, prognostic and predictive methods. A translational database system registering and combining all data and clinical...... observations about the patient is therefore needed. It is expected that along with automated prediction and prognosis tools, such a database system may have the potential to assist the development of new machine-based diagnostic decision-making processes. Udgivelsesdato: 2010-Jul-12...

Fragger: a protein fragment picker for structural queries.

Science.gov (United States)

Berenger, Francois; Simoncini, David; Voet, Arnout; Shrestha, Rojan; Zhang, Kam Y J

2017-01-01

Protein modeling and design activities often require querying the Protein Data Bank (PDB) with a structural fragment, possibly containing gaps. For some applications, it is preferable to work on a specific subset of the PDB or with unpublished structures. These requirements, along with specific user needs, motivated the creation of a new software to manage and query 3D protein fragments. Fragger is a protein fragment picker that allows protein fragment databases to be created and queried. All fragment lengths are supported and any set of PDB files can be used to create a database. Fragger can efficiently search a fragment database with a query fragment and a distance threshold. Matching fragments are ranked by distance to the query. The query fragment can have structural gaps and the allowed amino acid sequences matching a query can be constrained via a regular expression of one-letter amino acid codes. Fragger also incorporates a tool to compute the backbone RMSD of one versus many fragments in high throughput. Fragger should be useful for protein design, loop grafting and related structural bioinformatics tasks.

CTDB: An Integrated Chickpea Transcriptome Database for Functional and Applied Genomics

OpenAIRE

Verma, Mohit; Kumar, Vinay; Patel, Ravi K.; Garg, Rohini; Jain, Mukesh

2015-01-01

Chickpea is an important grain legume used as a rich source of protein in human diet. The narrow genetic diversity and limited availability of genomic resources are the major constraints in implementing breeding strategies and biotechnological interventions for genetic enhancement of chickpea. We developed an integrated Chickpea Transcriptome Database (CTDB), which provides the comprehensive web interface for visualization and easy retrieval of transcriptome data in chickpea. The database fea...

Database Description - RMOS | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available base Description General information of database Database name RMOS Alternative nam...arch Unit Shoshi Kikuchi E-mail : Database classification Plant databases - Rice Microarray Data and other Gene Expression Database...s Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database description The Ric...19&lang=en Whole data download - Referenced database Rice Expression Database (RED) Rice full-length cDNA Database... (KOME) Rice Genome Integrated Map Database (INE) Rice Mutant Panel Database (Tos17) Rice Genome Annotation Database

ProOpDB: Prokaryotic Operon DataBase.

Science.gov (United States)

Taboada, Blanca; Ciria, Ricardo; Martinez-Guerrero, Cristian E; Merino, Enrique

2012-01-01

The Prokaryotic Operon DataBase (ProOpDB, http://operons.ibt.unam.mx/OperonPredictor) constitutes one of the most precise and complete repositories of operon predictions now available. Using our novel and highly accurate operon identification algorithm, we have predicted the operon structures of more than 1200 prokaryotic genomes. ProOpDB offers diverse alternatives by which a set of operon predictions can be retrieved including: (i) organism name, (ii) metabolic pathways, as defined by the KEGG database, (iii) gene orthology, as defined by the COG database, (iv) conserved protein domains, as defined by the Pfam database, (v) reference gene and (vi) reference operon, among others. In order to limit the operon output to non-redundant organisms, ProOpDB offers an efficient method to select the most representative organisms based on a precompiled phylogenetic distances matrix. In addition, the ProOpDB operon predictions are used directly as the input data of our Gene Context Tool to visualize their genomic context and retrieve the sequence of their corresponding 5' regulatory regions, as well as the nucleotide or amino acid sequences of their genes.

Comparing side chain packing in soluble proteins, protein-protein interfaces, and transmembrane proteins.

Science.gov (United States)

Gaines, J C; Acebes, S; Virrueta, A; Butler, M; Regan, L; O'Hern, C S

2018-05-01

We compare side chain prediction and packing of core and non-core regions of soluble proteins, protein-protein interfaces, and transmembrane proteins. We first identified or created comparable databases of high-resolution crystal structures of these 3 protein classes. We show that the solvent-inaccessible cores of the 3 classes of proteins are equally densely packed. As a result, the side chains of core residues at protein-protein interfaces and in the membrane-exposed regions of transmembrane proteins can be predicted by the hard-sphere plus stereochemical constraint model with the same high prediction accuracies (>90%) as core residues in soluble proteins. We also find that for all 3 classes of proteins, as one moves away from the solvent-inaccessible core, the packing fraction decreases as the solvent accessibility increases. However, the side chain predictability remains high (80% within 30°) up to a relative solvent accessibility, rSASA≲0.3, for all 3 protein classes. Our results show that ≈40% of the interface regions in protein complexes are "core", that is, densely packed with side chain conformations that can be accurately predicted using the hard-sphere model. We propose packing fraction as a metric that can be used to distinguish real protein-protein interactions from designed, non-binding, decoys. Our results also show that cores of membrane proteins are the same as cores of soluble proteins. Thus, the computational methods we are developing for the analysis of the effect of hydrophobic core mutations in soluble proteins will be equally applicable to analyses of mutations in membrane proteins. © 2018 Wiley Periodicals, Inc.

KALIMER database development (database configuration and design methodology)

International Nuclear Information System (INIS)

Jeong, Kwan Seong; Kwon, Young Min; Lee, Young Bum; Chang, Won Pyo; Hahn, Do Hee

2001-10-01

KALIMER Database is an advanced database to utilize the integration management for Liquid Metal Reactor Design Technology Development using Web Applicatins. KALIMER Design database consists of Results Database, Inter-Office Communication (IOC), and 3D CAD database, Team Cooperation system, and Reserved Documents, Results Database is a research results database during phase II for Liquid Metal Reactor Design Technology Develpment of mid-term and long-term nuclear R and D. IOC is a linkage control system inter sub project to share and integrate the research results for KALIMER. 3D CAD Database is s schematic design overview for KALIMER. Team Cooperation System is to inform team member of research cooperation and meetings. Finally, KALIMER Reserved Documents is developed to manage collected data and several documents since project accomplishment. This report describes the features of Hardware and Software and the Database Design Methodology for KALIMER

The Universal Protein Resource (UniProt)

Data.gov (United States)

U.S. Department of Health & Human Services — The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt databases are the UniProt Knowledgebase...

SwePep, a database designed for endogenous peptides and mass spectrometry.

Science.gov (United States)

Fälth, Maria; Sköld, Karl; Norrman, Mathias; Svensson, Marcus; Fenyö, David; Andren, Per E

2006-06-01

A new database, SwePep, specifically designed for endogenous peptides, has been constructed to significantly speed up the identification process from complex tissue samples utilizing mass spectrometry. In the identification process the experimental peptide masses are compared with the peptide masses stored in the database both with and without possible post-translational modifications. This intermediate identification step is fast and singles out peptides that are potential endogenous peptides and can later be confirmed with tandem mass spectrometry data. Successful applications of this methodology are presented. The SwePep database is a relational database developed using MySql and Java. The database contains 4180 annotated endogenous peptides from different tissues originating from 394 different species as well as 50 novel peptides from brain tissue identified in our laboratory. Information about the peptides, including mass, isoelectric point, sequence, and precursor protein, is also stored in the database. This new approach holds great potential for removing the bottleneck that occurs during the identification process in the field of peptidomics. The SwePep database is available to the public.

Gene Unprediction with Spurio: A tool to identify spurious protein sequences.

Science.gov (United States)

Höps, Wolfram; Jeffryes, Matt; Bateman, Alex

2018-01-01

We now have access to the sequences of tens of millions of proteins. These protein sequences are essential for modern molecular biology and computational biology. The vast majority of protein sequences are derived from gene prediction tools and have no experimental supporting evidence for their translation.  Despite the increasing accuracy of gene prediction tools there likely exists a large number of spurious protein predictions in the sequence databases.  We have developed the Spurio tool to help identify spurious protein predictions in prokaryotes.  Spurio searches the query protein sequence against a prokaryotic nucleotide database using tblastn and identifies homologous sequences. The tblastn matches are used to score the query sequence's likelihood of being a spurious protein prediction using a Gaussian process model. The most informative feature is the appearance of stop codons within the presumed translation of homologous DNA sequences. Benchmarking shows that the Spurio tool is able to distinguish spurious from true proteins. However, transposon proteins are prone to be predicted as spurious because of the frequency of degraded homologs found in the DNA sequence databases. Our initial experiments suggest that less than 1% of the proteins in the UniProtKB sequence database are likely to be spurious and that Spurio is able to identify over 60 times more spurious proteins than the AntiFam resource. The Spurio software and source code is available under an MIT license at the following URL: https://bitbucket.org/bateman-group/spurio.

DMPD: Post-transcriptional regulation of proinflammatory proteins. [Dynamic Macrophage Pathway CSML Database

Lifescience Database Archive (English)

Full Text Available 15075353 Post-transcriptional regulation of proinflammatory proteins. Anderson P, P...l) (.csml) Show Post-transcriptional regulation of proinflammatory proteins. PubmedID 15075353 Title Post-tr...anscriptional regulation of proinflammatory proteins. Authors Anderson P, Phillip

PreBIND and Textomy – mining the biomedical literature for protein-protein interactions using a support vector machine

Directory of Open Access Journals (Sweden)

Baskin Berivan

2003-03-01

Full Text Available Abstract Background The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate interaction information in the literature. We present an information extraction system that was designed to locate protein-protein interaction data in the literature and present these data to curators and the public for review and entry into BIND. Results Cross-validation estimated the support vector machine's test-set precision, accuracy and recall for classifying abstracts describing interaction information was 92%, 90% and 92% respectively. We estimated that the system would be able to recall up to 60% of all non-high throughput interactions present in another yeast-protein interaction database. Finally, this system was applied to a real-world curation problem and its use was found to reduce the task duration by 70% thus saving 176 days. Conclusions Machine learning methods are useful as tools to direct interaction and pathway database back-filling; however, this potential can only be realized if these techniques are coupled with human review and entry into a factual database such as BIND. The PreBIND system described here is available to the public at http://bind.ca. Current capabilities allow searching for human, mouse and yeast protein-interaction information.

Database Description - ASTRA | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available abase Description General information of database Database name ASTRA Alternative n...tics Journal Search: Contact address Database classification Nucleotide Sequence Databases - Gene structure,...3702 Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database description The database represents classified p...(10):1211-6. External Links: Original website information Database maintenance site National Institute of Ad... for user registration Not available About This Database Database Description Dow

Dictionary-driven protein annotation.

Science.gov (United States)

Rigoutsos, Isidore; Huynh, Tien; Floratos, Aris; Parida, Laxmi; Platt, Daniel

2002-09-01

Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/ bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were

tmRDB (tmRNA database)

DEFF Research Database (Denmark)

Zwieb, Christian; Gorodkin, Jan; Knudsen, Bjarne

2003-01-01

Maintained at the University of Texas Health Science Center at Tyler, Texas, the tmRNA database (tmRDB) is accessible at the URL http://psyche.uthct.edu/dbs/tmRDB/tmRDB.html with mirror sites located at Auburn University, Auburn, Alabama (http://www.ag.auburn.edu/mirror/tmRDB/) and the Bioinforma......Maintained at the University of Texas Health Science Center at Tyler, Texas, the tmRNA database (tmRDB) is accessible at the URL http://psyche.uthct.edu/dbs/tmRDB/tmRDB.html with mirror sites located at Auburn University, Auburn, Alabama (http......://www.ag.auburn.edu/mirror/tmRDB/) and the Bioinformatics Research Center, Aarhus, Denmark (http://www.bioinf.au.dk/tmRDB/). The tmRDB collects and distributes information relevant to the study of tmRNA. In trans-translation, this molecule combines properties of tRNA and mRNA and binds several proteins to form the tmRNP. Related RNPs are likely...

Database Description - RPD | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available ase Description General information of database Database name RPD Alternative name Rice Proteome Database...titute of Crop Science, National Agriculture and Food Research Organization Setsuko Komatsu E-mail: Database... classification Proteomics Resources Plant databases - Rice Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database... description Rice Proteome Database contains information on protei...and entered in the Rice Proteome Database. The database is searchable by keyword,

Database Description - PLACE | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available abase Description General information of database Database name PLACE Alternative name A Database...Kannondai, Tsukuba, Ibaraki 305-8602, Japan National Institute of Agrobiological Sciences E-mail : Databas...e classification Plant databases Organism Taxonomy Name: Tracheophyta Taxonomy ID: 58023 Database...99, Vol.27, No.1 :297-300 External Links: Original website information Database maintenance site National In...- Need for user registration Not available About This Database Database Descripti

Phenome data - High-sugar stress - DGBY | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data ...s.zip File size: 90KB File name: Original file: High-sugar_stress.xls File URL: ftp://ftp.biosciencedbc.jp/archive/dgby/LATEST/Hi... Center for Protein Sequences） About This Database Database Description Download License Update History of Thi...s Database Site Policy | Contact Us Phenome data - High-sugar stress - DGBY | LSDB Archive ... ...List Contact us DGBY Phenome data - High-sugar stress Data detail Data name Phenome data - High-sugar stress

Database Description - JSNP | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available base Description General information of database Database name JSNP Alternative nam...n Science and Technology Agency Creator Affiliation: Contact address E-mail : Database...sapiens Taxonomy ID: 9606 Database description A database of about 197,000 polymorphisms in Japanese populat...1):605-610 External Links: Original website information Database maintenance site Institute of Medical Scien...er registration Not available About This Database Database Description Download License Update History of This Database

Database Description - RED | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available ase Description General information of database Database name RED Alternative name Rice Expression Database...enome Research Unit Shoshi Kikuchi E-mail : Database classification Plant databases - Rice Database classifi...cation Microarray, Gene Expression Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database descripti... Article title: Rice Expression Database: the gateway to rice functional genomics...nt Science (2002) Dec 7 (12):563-564 External Links: Original website information Database maintenance site

SinEx DB: a database for single exon coding sequences in mammalian genomes.

Science.gov (United States)

Jorquera, Roddy; Ortiz, Rodrigo; Ossandon, F; Cárdenas, Juan Pablo; Sepúlveda, Rene; González, Carolina; Holmes, David S

2016-01-01

Eukaryotic genes are typically interrupted by intragenic, noncoding sequences termed introns. However, some genes lack introns in their coding sequence (CDS) and are generally known as 'single exon genes' (SEGs). In this work, a SEG is defined as a nuclear, protein-coding gene that lacks introns in its CDS. Whereas, many public databases of Eukaryotic multi-exon genes are available, there are only two specialized databases for SEGs. The present work addresses the need for a more extensive and diverse database by creating SinEx DB, a publicly available, searchable database of predicted SEGs from 10 completely sequenced mammalian genomes including human. SinEx DB houses the DNA and protein sequence information of these SEGs and includes their functional predictions (KOG) and the relative distribution of these functions within species. The information is stored in a relational database built with My SQL Server 5.1.33 and the complete dataset of SEG sequences and their functional predictions are available for downloading. SinEx DB can be interrogated by: (i) a browsable phylogenetic schema, (ii) carrying out BLAST searches to the in-house SinEx DB of SEGs and (iii) via an advanced search mode in which the database can be searched by key words and any combination of searches by species and predicted functions. SinEx DB provides a rich source of information for advancing our understanding of the evolution and function of SEGs.Database URL: www.sinex.cl. © The Author(s) 2016. Published by Oxford University Press.

The AUDANA algorithm for automated protein 3D structure determination from NMR NOE data

Energy Technology Data Exchange (ETDEWEB)

Lee, Woonghee, E-mail: whlee@nmrfam.wisc.edu [University of Wisconsin-Madison, National Magnetic Resonance Facility at Madison and Biochemistry Department (United States); Petit, Chad M. [University of Alabama at Birmingham, Department of Biochemistry and Molecular Genetics (United States); Cornilescu, Gabriel; Stark, Jaime L.; Markley, John L., E-mail: markley@nmrfam.wisc.edu [University of Wisconsin-Madison, National Magnetic Resonance Facility at Madison and Biochemistry Department (United States)

2016-06-15

We introduce AUDANA (Automated Database-Assisted NOE Assignment), an algorithm for determining three-dimensional structures of proteins from NMR data that automates the assignment of 3D-NOE spectra, generates distance constraints, and conducts iterative high temperature molecular dynamics and simulated annealing. The protein sequence, chemical shift assignments, and NOE spectra are the only required inputs. Distance constraints generated automatically from ambiguously assigned NOE peaks are validated during the structure calculation against information from an enlarged version of the freely available PACSY database that incorporates information on protein structures deposited in the Protein Data Bank (PDB). This approach yields robust sets of distance constraints and 3D structures. We evaluated the performance of AUDANA with input data for 14 proteins ranging in size from 6 to 25 kDa that had 27–98 % sequence identity to proteins in the database. In all cases, the automatically calculated 3D structures passed stringent validation tests. Structures were determined with and without database support. In 9/14 cases, database support improved the agreement with manually determined structures in the PDB and in 11/14 cases, database support lowered the r.m.s.d. of the family of 20 structural models.

The AUDANA algorithm for automated protein 3D structure determination from NMR NOE data

International Nuclear Information System (INIS)

Lee, Woonghee; Petit, Chad M.; Cornilescu, Gabriel; Stark, Jaime L.; Markley, John L.

2016-01-01

We introduce AUDANA (Automated Database-Assisted NOE Assignment), an algorithm for determining three-dimensional structures of proteins from NMR data that automates the assignment of 3D-NOE spectra, generates distance constraints, and conducts iterative high temperature molecular dynamics and simulated annealing. The protein sequence, chemical shift assignments, and NOE spectra are the only required inputs. Distance constraints generated automatically from ambiguously assigned NOE peaks are validated during the structure calculation against information from an enlarged version of the freely available PACSY database that incorporates information on protein structures deposited in the Protein Data Bank (PDB). This approach yields robust sets of distance constraints and 3D structures. We evaluated the performance of AUDANA with input data for 14 proteins ranging in size from 6 to 25 kDa that had 27–98 % sequence identity to proteins in the database. In all cases, the automatically calculated 3D structures passed stringent validation tests. Structures were determined with and without database support. In 9/14 cases, database support improved the agreement with manually determined structures in the PDB and in 11/14 cases, database support lowered the r.m.s.d. of the family of 20 structural models.

Database management systems understanding and applying database technology

CERN Document Server

Gorman, Michael M

1991-01-01

Database Management Systems: Understanding and Applying Database Technology focuses on the processes, methodologies, techniques, and approaches involved in database management systems (DBMSs).The book first takes a look at ANSI database standards and DBMS applications and components. Discussion focus on application components and DBMS components, implementing the dynamic relationship application, problems and benefits of dynamic relationship DBMSs, nature of a dynamic relationship application, ANSI/NDL, and DBMS standards. The manuscript then ponders on logical database, interrogation, and phy

CAZymes Analysis Toolkit (CAT): web service for searching and analyzing carbohydrate-active enzymes in a newly sequenced organism using CAZy database.

Science.gov (United States)

Park, Byung H; Karpinets, Tatiana V; Syed, Mustafa H; Leuze, Michael R; Uberbacher, Edward C

2010-12-01

The Carbohydrate-Active Enzyme (CAZy) database provides a rich set of manually annotated enzymes that degrade, modify, or create glycosidic bonds. Despite rich and invaluable information stored in the database, software tools utilizing this information for annotation of newly sequenced genomes by CAZy families are limited. We have employed two annotation approaches to fill the gap between manually curated high-quality protein sequences collected in the CAZy database and the growing number of other protein sequences produced by genome or metagenome sequencing projects. The first approach is based on a similarity search against the entire nonredundant sequences of the CAZy database. The second approach performs annotation using links or correspondences between the CAZy families and protein family domains. The links were discovered using the association rule learning algorithm applied to sequences from the CAZy database. The approaches complement each other and in combination achieved high specificity and sensitivity when cross-evaluated with the manually curated genomes of Clostridium thermocellum ATCC 27405 and Saccharophagus degradans 2-40. The capability of the proposed framework to predict the function of unknown protein domains and of hypothetical proteins in the genome of Neurospora crassa is demonstrated. The framework is implemented as a Web service, the CAZymes Analysis Toolkit, and is available at http://cricket.ornl.gov/cgi-bin/cat.cgi.

URS DataBase: universe of RNA structures and their motifs.

Science.gov (United States)

Baulin, Eugene; Yacovlev, Victor; Khachko, Denis; Spirin, Sergei; Roytberg, Mikhail

2016-01-01

The Universe of RNA Structures DataBase (URSDB) stores information obtained from all RNA-containing PDB entries (2935 entries in October 2015). The content of the database is updated regularly. The database consists of 51 tables containing indexed data on various elements of the RNA structures. The database provides a web interface allowing user to select a subset of structures with desired features and to obtain various statistical data for a selected subset of structures or for all structures. In particular, one can easily obtain statistics on geometric parameters of base pairs, on structural motifs (stems, loops, etc.) or on different types of pseudoknots. The user can also view and get information on an individual structure or its selected parts, e.g. RNA-protein hydrogen bonds. URSDB employs a new original definition of loops in RNA structures. That definition fits both pseudoknot-free and pseudoknotted secondary structures and coincides with the classical definition in case of pseudoknot-free structures. To our knowledge, URSDB is the first database supporting searches based on topological classification of pseudoknots and on extended loop classification.Database URL: http://server3.lpm.org.ru/urs/. © The Author(s) 2016. Published by Oxford University Press.

Database Description - RMG | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available ase Description General information of database Database name RMG Alternative name ...raki 305-8602, Japan National Institute of Agrobiological Sciences E-mail : Database... classification Nucleotide Sequence Databases Organism Taxonomy Name: Oryza sativa Japonica Group Taxonomy ID: 39947 Database...rnal: Mol Genet Genomics (2002) 268: 434–445 External Links: Original website information Database...available URL of Web services - Need for user registration Not available About This Database Database Descri

PIR search result - KOME | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available e filtered with Expect values lower than 1e-10. Number of data entries 1,549,409 ...he searches. Data analysis method Performed blastx searches against the PIR protein database. The results ar

Relational databases

CERN Document Server

Bell, D A

1986-01-01

Relational Databases explores the major advances in relational databases and provides a balanced analysis of the state of the art in relational databases. Topics covered include capture and analysis of data placement requirements; distributed relational database systems; data dependency manipulation in database schemata; and relational database support for computer graphics and computer aided design. This book is divided into three sections and begins with an overview of the theory and practice of distributed systems, using the example of INGRES from Relational Technology as illustration. The

Construction of an integrated database to support genomic sequence analysis

Energy Technology Data Exchange (ETDEWEB)

Gilbert, W.; Overbeek, R.

1994-11-01

The central goal of this project is to develop an integrated database to support comparative analysis of genomes including DNA sequence data, protein sequence data, gene expression data and metabolism data. In developing the logic-based system GenoBase, a broader integration of available data was achieved due to assistance from collaborators. Current goals are to easily include new forms of data as they become available and to easily navigate through the ensemble of objects described within the database. This report comments on progress made in these areas.

JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles

DEFF Research Database (Denmark)

Portales-Casamar, Elodie; Thongjuea, Supat; Kwon, Andrew T

2009-01-01

JASPAR (http://jaspar.genereg.net) is the leading open-access database of matrix profiles describing the DNA-binding patterns of transcription factors (TFs) and other proteins interacting with DNA in a sequence-specific manner. Its fourth major release is the largest expansion of the core database...... to an active research community. As binding models are refined by newer data, the JASPAR database now uses versioning of matrices: in this release, 12% of the older models were updated to improved versions. Classification of TF families has been improved by adopting a new DNA-binding domain nomenclature...

Database Description - DGBY | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available base Description General information of database Database name DGBY Alternative name Database...EL: +81-29-838-8066 E-mail: Database classification Microarray Data and other Gene Expression Databases Orga...nism Taxonomy Name: Saccharomyces cerevisiae Taxonomy ID: 4932 Database descripti...-called phenomics). We uploaded these data on this website which is designated DGBY(Database for Gene expres...ma J, Ando A, Takagi H. Journal: Yeast. 2008 Mar;25(3):179-90. External Links: Original website information Database

Database Description - KOME | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available base Description General information of database Database name KOME Alternative nam... Sciences Plant Genome Research Unit Shoshi Kikuchi E-mail : Database classification Plant databases - Rice ...Organism Taxonomy Name: Oryza sativa Taxonomy ID: 4530 Database description Information about approximately ...Hayashizaki Y, Kikuchi S. Journal: PLoS One. 2007 Nov 28; 2(11):e1235. External Links: Original website information Database...OS) Rice mutant panel database (Tos17) A Database of Plant Cis-acting Regulatory

MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes.

Science.gov (United States)

Zhang, Yanling; Zhang, Yong; Adachi, Jun; Olsen, Jesper V; Shi, Rong; de Souza, Gustavo; Pasini, Erica; Foster, Leonard J; Macek, Boris; Zougman, Alexandre; Kumar, Chanchal; Wisniewski, Jacek R; Jun, Wang; Mann, Matthias

2007-01-01

Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at http://www.mapuproteome.com using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools.

PROGRAM SYSTEM AND INFORMATION METADATA BANK OF TERTIARY PROTEIN STRUCTURES

Directory of Open Access Journals (Sweden)

T. A. Nikitin

2013-01-01

Full Text Available The article deals with the architecture of metadata storage model for check results of three-dimensional protein structures. Concept database model was built. The service and procedure of database update as well as data transformation algorithms for protein structures and their quality were presented. Most important information about entries and their submission forms to store, access, and delivery to users were highlighted. Software suite was developed for the implementation of functional tasks using Java programming language in the NetBeans v.7.0 environment and JQL to query and interact with the database JavaDB. The service was tested and results have shown system effectiveness while protein structures filtration.

The mining of toxin-like polypeptides from EST database by single residue distribution analysis.

Science.gov (United States)

Kozlov, Sergey; Grishin, Eugene

2011-01-31

Novel high throughput sequencing technologies require permanent development of bioinformatics data processing methods. Among them, rapid and reliable identification of encoded proteins plays a pivotal role. To search for particular protein families, the amino acid sequence motifs suitable for selective screening of nucleotide sequence databases may be used. In this work, we suggest a novel method for simplified representation of protein amino acid sequences named Single Residue Distribution Analysis, which is applicable both for homology search and database screening. Using the procedure developed, a search for amino acid sequence motifs in sea anemone polypeptides was performed, and 14 different motifs with broad and low specificity were discriminated. The adequacy of motifs for mining toxin-like sequences was confirmed by their ability to identify 100% toxin-like anemone polypeptides in the reference polypeptide database. The employment of novel motifs for the search of polypeptide toxins in Anemonia viridis EST dataset allowed us to identify 89 putative toxin precursors. The translated and modified ESTs were scanned using a special algorithm. In addition to direct comparison with the motifs developed, the putative signal peptides were predicted and homology with known structures was examined. The suggested method may be used to retrieve structures of interest from the EST databases using simple amino acid sequence motifs as templates. The efficiency of the procedure for directed search of polypeptides is higher than that of most currently used methods. Analysis of 39939 ESTs of sea anemone Anemonia viridis resulted in identification of five protein precursors of earlier described toxins, discovery of 43 novel polypeptide toxins, and prediction of 39 putative polypeptide toxin sequences. In addition, two precursors of novel peptides presumably displaying neuronal function were disclosed.

Databases

Directory of Open Access Journals (Sweden)

Nick Ryan

2004-01-01

Full Text Available Databases are deeply embedded in archaeology, underpinning and supporting many aspects of the subject. However, as well as providing a means for storing, retrieving and modifying data, databases themselves must be a result of a detailed analysis and design process. This article looks at this process, and shows how the characteristics of data models affect the process of database design and implementation. The impact of the Internet on the development of databases is examined, and the article concludes with a discussion of a range of issues associated with the recording and management of archaeological data.

A Reference Database for Circular Dichroism Spectroscopy Covering Fold and Secondary Structure Space

International Nuclear Information System (INIS)

Lees, J.; Miles, A.; Wien, F.; Wallace, B.

2006-01-01

Circular Dichroism (CD) spectroscopy is a long-established technique for studying protein secondary structures in solution. Empirical analyses of CD data rely on the availability of reference datasets comprised of far-UV CD spectra of proteins whose crystal structures have been determined. This article reports on the creation of a new reference dataset which effectively covers both secondary structure and fold space, and uses the higher information content available in synchrotron radiation circular dichroism (SRCD) spectra to more accurately predict secondary structure than has been possible with existing reference datasets. It also examines the effects of wavelength range, structural redundancy and different means of categorizing secondary structures on the accuracy of the analyses. In addition, it describes a novel use of hierarchical cluster analyses to identify protein relatedness based on spectral properties alone. The databases are shown to be applicable in both conventional CD and SRCD spectroscopic analyses of proteins. Hence, by combining new bioinformatics and biophysical methods, a database has been produced that should have wide applicability as a tool for structural molecular biology

ARAMEMNON, a novel database for Arabidopsis integral membrane proteins

DEFF Research Database (Denmark)

Schwacke, Rainer; Schneider, Anja; van der Graaff, Eric

2003-01-01

spans and are possibly linked to transport functions. The ARAMEMNON DB enables direct comparison of the predictions of seven different TM span computation programs and the predictions of subcellular localization by eight signal peptide recognition programs. A special function displays the proteins...

PharmDB-K: Integrated Bio-Pharmacological Network Database for Traditional Korean Medicine.

Directory of Open Access Journals (Sweden)

Ji-Hyun Lee

Full Text Available Despite the growing attention given to Traditional Medicine (TM worldwide, there is no well-known, publicly available, integrated bio-pharmacological Traditional Korean Medicine (TKM database for researchers in drug discovery. In this study, we have constructed PharmDB-K, which offers comprehensive information relating to TKM-associated drugs (compound, disease indication, and protein relationships. To explore the underlying molecular interaction of TKM, we integrated fourteen different databases, six Pharmacopoeias, and literature, and established a massive bio-pharmacological network for TKM and experimentally validated some cases predicted from the PharmDB-K analyses. Currently, PharmDB-K contains information about 262 TKMs, 7,815 drugs, 3,721 diseases, 32,373 proteins, and 1,887 side effects. One of the unique sets of information in PharmDB-K includes 400 indicator compounds used for standardization of herbal medicine. Furthermore, we are operating PharmDB-K via phExplorer (a network visualization software and BioMart (a data federation framework for convenient search and analysis of the TKM network. Database URL: http://pharmdb-k.org, http://biomart.i-pharm.org.

Database Description - SSBD | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available base Description General information of database Database name SSBD Alternative nam...ss 2-2-3 Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan, RIKEN Quantitative Biology Center Shuichi Onami E-mail: Database... classification Other Molecular Biology Databases Database classification Dynamic databa...elegans Taxonomy ID: 6239 Taxonomy Name: Escherichia coli Taxonomy ID: 562 Database description Systems Scie...i Onami Journal: Bioinformatics/April, 2015/Volume 31, Issue 7 External Links: Original website information Database

Database Description - GETDB | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available abase Description General information of database Database name GETDB Alternative n...ame Gal4 Enhancer Trap Insertion Database DOI 10.18908/lsdba.nbdc00236-000 Creator Creator Name: Shigeo Haya... Chuo-ku, Kobe 650-0047 Tel: +81-78-306-3185 FAX: +81-78-306-3183 E-mail: Database classification Expression... Invertebrate genome database Organism Taxonomy Name: Drosophila melanogaster Taxonomy ID: 7227 Database des...riginal website information Database maintenance site Drosophila Genetic Resource

JICST Factual DatabaseJICST Chemical Substance Safety Regulation Database

Science.gov (United States)

Abe, Atsushi; Sohma, Tohru

JICST Chemical Substance Safety Regulation Database is based on the Database of Safety Laws for Chemical Compounds constructed by Japan Chemical Industry Ecology-Toxicology & Information Center (JETOC) sponsored by the Sience and Technology Agency in 1987. JICST has modified JETOC database system, added data and started the online service through JOlS-F (JICST Online Information Service-Factual database) in January 1990. JICST database comprises eighty-three laws and fourteen hundred compounds. The authors outline the database, data items, files and search commands. An example of online session is presented.

StraPep: a structure database of bioactive peptides

Science.gov (United States)

Wang, Jian; Yin, Tailang; Xiao, Xuwen; He, Dan; Xue, Zhidong; Jiang, Xinnong; Wang, Yan

2018-01-01

Abstract Bioactive peptides, with a variety of biological activities and wide distribution in nature, have attracted great research interest in biological and medical fields, especially in pharmaceutical industry. The structural information of bioactive peptide is important for the development of peptide-based drugs. Many databases have been developed cataloguing bioactive peptides. However, to our knowledge, database dedicated to collect all the bioactive peptides with known structure is not available yet. Thus, we developed StraPep, a structure database of bioactive peptides. StraPep holds 3791 bioactive peptide structures, which belong to 1312 unique bioactive peptide sequences. About 905 out of 1312 (68%) bioactive peptides in StraPep contain disulfide bonds, which is significantly higher than that (21%) of PDB. Interestingly, 150 out of 616 (24%) bioactive peptides with three or more disulfide bonds form a structural motif known as cystine knot, which confers considerable structural stability on proteins and is an attractive scaffold for drug design. Detailed information of each peptide, including the experimental structure, the location of disulfide bonds, secondary structure, classification, post-translational modification and so on, has been provided. A wide range of user-friendly tools, such as browsing, sequence and structure-based searching and so on, has been incorporated into StraPep. We hope that this database will be helpful for the research community. Database URL: http://isyslab.info/StraPep PMID:29688386

gEVE: a genome-based endogenous viral element database provides comprehensive viral protein-coding sequences in mammalian genomes.

Science.gov (United States)

Nakagawa, So; Takahashi, Mahoko Ueda

2016-01-01

In mammals, approximately 10% of genome sequences correspond to endogenous viral elements (EVEs), which are derived from ancient viral infections of germ cells. Although most EVEs have been inactivated, some open reading frames (ORFs) of EVEs obtained functions in the hosts. However, EVE ORFs usually remain unannotated in the genomes, and no databases are available for EVE ORFs. To investigate the function and evolution of EVEs in mammalian genomes, we developed EVE ORF databases for 20 genomes of 19 mammalian species. A total of 736,771 non-overlapping EVE ORFs were identified and archived in a database named gEVE (http://geve.med.u-tokai.ac.jp). The gEVE database provides nucleotide and amino acid sequences, genomic loci and functional annotations of EVE ORFs for all 20 genomes. In analyzing RNA-seq data with the gEVE database, we successfully identified the expressed EVE genes, suggesting that the gEVE database facilitates studies of the genomic analyses of various mammalian species.Database URL: http://geve.med.u-tokai.ac.jp. © The Author(s) 2016. Published by Oxford University Press.

Database Description - KAIKOcDNA | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us KAIKOcDNA Database Description General information of database Database name KAIKOcDNA Alter...National Institute of Agrobiological Sciences Akiya Jouraku E-mail : Database cla...ssification Nucleotide Sequence Databases Organism Taxonomy Name: Bombyx mori Taxonomy ID: 7091 Database des...rnal: G3 (Bethesda) / 2013, Sep / vol.9 External Links: Original website information Database maintenance si...available URL of Web services - Need for user registration Not available About This Database Database

Download - Trypanosomes Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Trypanosomes Database Download First of all, please read the license of this database. Data ...1.4 KB) Simple search and download Downlaod via FTP FTP server is sometimes jammed. If it is, access [here]. About This Database Data...base Description Download License Update History of This Database Site Policy | Contact Us Download - Trypanosomes Database | LSDB Archive ...

A Novel Approach for Protein-Named Entity Recognition and Protein-Protein Interaction Extraction

Directory of Open Access Journals (Sweden)

Meijing Li

2015-01-01

Full Text Available Many researchers focus on developing protein-named entity recognition (Protein-NER or PPI extraction systems. However, the studies about these two topics cannot be merged well; then existing PPI extraction systems’ Protein-NER still needs to improve. In this paper, we developed the protein-protein interaction extraction system named PPIMiner based on Support Vector Machine (SVM and parsing tree. PPIMiner consists of three main models: natural language processing (NLP model, Protein-NER model, and PPI discovery model. The Protein-NER model, which is named ProNER, identifies the protein names based on two methods: dictionary-based method and machine learning-based method. ProNER is capable of identifying more proteins than dictionary-based Protein-NER model in other existing systems. The final discovered PPIs extracted via PPI discovery model are represented in detail because we showed the protein interaction types and the occurrence frequency through two different methods. In the experiments, the result shows that the performances achieved by our ProNER and PPI discovery model are better than other existing tools. PPIMiner applied this protein-named entity recognition approach and parsing tree based PPI extraction method to improve the performance of PPI extraction. We also provide an easy-to-use interface to access PPIs database and an online system for PPIs extraction and Protein-NER.

TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining

Directory of Open Access Journals (Sweden)

Chen Hsin-Hsi

2008-10-01

Full Text Available Abstract Background Traditional Chinese Medicine (TCM, a complementary and alternative medical system in Western countries, has been used to treat various diseases over thousands of years in East Asian countries. In recent years, many herbal medicines were found to exhibit a variety of effects through regulating a wide range of gene expressions or protein activities. As available TCM data continue to accumulate rapidly, an urgent need for exploring these resources systematically is imperative, so as to effectively utilize the large volume of literature. Methods TCM, gene, disease, biological pathway and protein-protein interaction information were collected from public databases. For association discovery, the TCM names, gene names, disease names, TCM ingredients and effects were used to annotate the literature corpus obtained from PubMed. The concept to mine entity associations was based on hypothesis testing and collocation analysis. The annotated corpus was processed with natural language processing tools and rule-based approaches were applied to the sentences for extracting the relations between TCM effecters and effects. Results We developed a database, TCMGeneDIT, to provide association information about TCMs, genes, diseases, TCM effects and TCM ingredients mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information are also available for exploring the regulations of genes associated with TCM curative effects. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in understanding the possible therapeutic mechanisms of TCMs via gene regulations and deducing synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. The database is now available at http://tcm.lifescience.ntu.edu.tw/. Conclusion TCMGeneDIT is a unique database

CellMap visualizes protein-protein interactions and subcellular localization

Science.gov (United States)

Dallago, Christian; Goldberg, Tatyana; Andrade-Navarro, Miguel Angel; Alanis-Lobato, Gregorio; Rost, Burkhard

2018-01-01

Many tools visualize protein-protein interaction (PPI) networks. The tool introduced here, CellMap, adds one crucial novelty by visualizing PPI networks in the context of subcellular localization, i.e. the location in the cell or cellular component in which a PPI happens. Users can upload images of cells and define areas of interest against which PPIs for selected proteins are displayed (by default on a cartoon of a cell). Annotations of localization are provided by the user or through our in-house database. The visualizer and server are written in JavaScript, making CellMap easy to customize and to extend by researchers and developers. PMID:29497493

ProCarDB: a database of bacterial carotenoids.

Science.gov (United States)

Nupur, L N U; Vats, Asheema; Dhanda, Sandeep Kumar; Raghava, Gajendra P S; Pinnaka, Anil Kumar; Kumar, Ashwani

2016-05-26

Carotenoids have important functions in bacteria, ranging from harvesting light energy to neutralizing oxidants and acting as virulence factors. However, information pertaining to the carotenoids is scattered throughout the literature. Furthermore, information about the genes/proteins involved in the biosynthesis of carotenoids has tremendously increased in the post-genomic era. A web server providing the information about microbial carotenoids in a structured manner is required and will be a valuable resource for the scientific community working with microbial carotenoids. Here, we have created a manually curated, open access, comprehensive compilation of bacterial carotenoids named as ProCarDB- Prokaryotic Carotenoid Database. ProCarDB includes 304 unique carotenoids arising from 50 biosynthetic pathways distributed among 611 prokaryotes. ProCarDB provides important information on carotenoids, such as 2D and 3D structures, molecular weight, molecular formula, SMILES, InChI, InChIKey, IUPAC name, KEGG Id, PubChem Id, and ChEBI Id. The database also provides NMR data, UV-vis absorption data, IR data, MS data and HPLC data that play key roles in the identification of carotenoids. An important feature of this database is the extension of biosynthetic pathways from the literature and through the presence of the genes/enzymes in different organisms. The information contained in the database was mined from published literature and databases such as KEGG, PubChem, ChEBI, LipidBank, LPSN, and Uniprot. The database integrates user-friendly browsing and searching with carotenoid analysis tools to help the user. We believe that this database will serve as a major information centre for researchers working on bacterial carotenoids.

License - Arabidopsis Phenome Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us Arabidopsis Phenome Database License License to Use This Database Last updated : 2017/02/27 You may use this database...cense specifies the license terms regarding the use of this database and the requirements you must follow in using this database.... The license for this database is specified in the Creative ...Commons Attribution-Share Alike 4.0 International . If you use data from this database, please be sure attribute this database...ative Commons Attribution-Share Alike 4.0 International is found here . With regard to this database, you ar

HitPredict version 4: comprehensive reliability scoring of physical protein?protein interactions from more than 100 species

OpenAIRE

L?pez, Yosvany; Nakai, Kenta; Patil, Ashwini

2015-01-01

HitPredict is a consolidated resource of experimentally identified, physical protein?protein interactions with confidence scores to indicate their reliability. The study of genes and their inter-relationships using methods such as network and pathway analysis requires high quality protein?protein interaction information. Extracting reliable interactions from most of the existing databases is challenging because they either contain only a subset of the available interactions, or a mixture of p...

Seeds in Chernobyl: the database on proteome response on radioactive environment

Science.gov (United States)

Klubicová, Katarína; Vesel, Martin; Rashydov, Namik M.; Hajduch, Martin

2012-01-01

Two serious nuclear accidents during the last quarter century (Chernobyl, 1986 and Fukushima, 2011) contaminated large agricultural areas with radioactivity. The database “Seeds in Chernobyl” (http://www.chernobylproteomics.sav.sk) contains the information about the abundances of hundreds of proteins from on-going investigation of mature and developing seed harvested from plants grown in radioactive Chernobyl area. This database provides a useful source of information concerning the response of the seed proteome to permanently increased level of ionizing radiation in a user-friendly format. PMID:23087698

Protein identification by peptide mass fingerprinting

DEFF Research Database (Denmark)

Hjernø, Karin

2007-01-01

  Peptide mass fingerprinting is an effective way of identifying, e.g., gel-separated proteins, by matching experimentally obtained peptide mass data against large databases. However, several factors are known to influence the quality of the resulting matches, such as proteins contaminating the s...

Exploring the universe of protein structures beyond the Protein Data Bank.

Science.gov (United States)

Cossio, Pilar; Trovato, Antonio; Pietrucci, Fabio; Seno, Flavio; Maritan, Amos; Laio, Alessandro

2010-11-04

It is currently believed that the atlas of existing protein structures is faithfully represented in the Protein Data Bank. However, whether this atlas covers the full universe of all possible protein structures is still a highly debated issue. By using a sophisticated numerical approach, we performed an exhaustive exploration of the conformational space of a 60 amino acid polypeptide chain described with an accurate all-atom interaction potential. We generated a database of around 30,000 compact folds with at least of secondary structure corresponding to local minima of the potential energy. This ensemble plausibly represents the universe of protein folds of similar length; indeed, all the known folds are represented in the set with good accuracy. However, we discover that the known folds form a rather small subset, which cannot be reproduced by choosing random structures in the database. Rather, natural and possible folds differ by the contact order, on average significantly smaller in the former. This suggests the presence of an evolutionary bias, possibly related to kinetic accessibility, towards structures with shorter loops between contacting residues. Beside their conceptual relevance, the new structures open a range of practical applications such as the development of accurate structure prediction strategies, the optimization of force fields, and the identification and design of novel folds.

Database Description - AcEST | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available abase Description General information of database Database name AcEST Alternative n...hi, Tokyo-to 192-0397 Tel: +81-42-677-1111(ext.3654) E-mail: Database classificat...eneris Taxonomy ID: 13818 Database description This is a database of EST sequences of Adiantum capillus-vene...(3): 223-227. External Links: Original website information Database maintenance site Plant Environmental Res...base Database Description Download License Update History of This Database Site Policy | Contact Us Database Description - AcEST | LSDB Archive ...

The VirusBanker database uses a Java program to allow flexible searching through Bunyaviridae sequences.

Science.gov (United States)

Fourment, Mathieu; Gibbs, Mark J

2008-02-05

Viruses of the Bunyaviridae have segmented negative-stranded RNA genomes and several of them cause significant disease. Many partial sequences have been obtained from the segments so that GenBank searches give complex results. Sequence databases usually use HTML pages to mediate remote sorting, but this approach can be limiting and may discourage a user from exploring a database. The VirusBanker database contains Bunyaviridae sequences and alignments and is presented as two spreadsheets generated by a Java program that interacts with a MySQL database on a server. Sequences are displayed in rows and may be sorted using information that is displayed in columns and includes data relating to the segment, gene, protein, species, strain, sequence length, terminal sequence and date and country of isolation. Bunyaviridae sequences and alignments may be downloaded from the second spreadsheet with titles defined by the user from the columns, or viewed when passed directly to the sequence editor, Jalview. VirusBanker allows large datasets of aligned nucleotide and protein sequences from the Bunyaviridae to be compiled and winnowed rapidly using criteria that are formulated heuristically.

Pancreatic Expression database: a generic model for the organization, integration and mining of complex cancer datasets

Directory of Open Access Journals (Sweden)

Lemoine Nicholas R

2007-11-01

Full Text Available Abstract Background Pancreatic cancer is the 5th leading cause of cancer death in both males and females. In recent years, a wealth of gene and protein expression studies have been published broadening our understanding of pancreatic cancer biology. Due to the explosive growth in publicly available data from multiple different sources it is becoming increasingly difficult for individual researchers to integrate these into their current research programmes. The Pancreatic Expression database, a generic web-based system, is aiming to close this gap by providing the research community with an open access tool, not only to mine currently available pancreatic cancer data sets but also to include their own data in the database. Description Currently, the database holds 32 datasets comprising 7636 gene expression measurements extracted from 20 different published gene or protein expression studies from various pancreatic cancer types, pancreatic precursor lesions (PanINs and chronic pancreatitis. The pancreatic data are stored in a data management system based on the BioMart technology alongside the human genome gene and protein annotations, sequence, homologue, SNP and antibody data. Interrogation of the database can be achieved through both a web-based query interface and through web services using combined criteria from pancreatic (disease stages, regulation, differential expression, expression, platform technology, publication and/or public data (antibodies, genomic region, gene-related accessions, ontology, expression patterns, multi-species comparisons, protein data, SNPs. Thus, our database enables connections between otherwise disparate data sources and allows relatively simple navigation between all data types and annotations. Conclusion The database structure and content provides a powerful and high-speed data-mining tool for cancer research. It can be used for target discovery i.e. of biomarkers from body fluids, identification and analysis

License - SKIP Stemcell Database | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available List Contact us SKIP Stemcell Database License License to Use This Database Last updated : 2017/03/13 You may use this database...specifies the license terms regarding the use of this database and the requirements you must follow in using this database.... The license for this database is specified in the Creative Common...s Attribution-Share Alike 4.0 International . If you use data from this database, please be sure attribute this database...al ... . The summary of the Creative Commons Attribution-Share Alike 4.0 International is found here . With regard to this database

KALIMER database development

Energy Technology Data Exchange (ETDEWEB)