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Comprehensive inventory of protein complexes in the protein data bank from consistent classification of interfaces

BMC BIOINFORMATICS 2008年第1期9卷 234-234页

作者： Bordner, Andrew J. Gorin, Andrey A. Oak Ridge Natl Lab Computat Sci & Math Div Oak Ridge TN 37831 USA Oak Ridge Natl Lab BioEnergy Sci Ctr Oak Ridge TN 37831 USA Mayo Clin Scottsdale AZ 85259 USA

Background: protein-protein interactions are ubiquitous and essential for all cellular processes. High-resolution X-ray crystallographic structures of protein complexes can reveal the details of their function and provide a basis for many computational and experimental approaches. Differentiation between biological and non-biological contacts and reconstruction of the intact complex is a challenging computational problem. A successful solution can provide additional insights into the fundamental principles of biological recognition and reduce errors in many algorithms and databases utilizing interaction information extracted from the protein data bank (PDB). Results: We have developed a method for identifying protein complexes in the PDB X-ray structures by a four step procedure: (1) comprehensively collecting all protein-protein interfaces;(2) clustering similar protein-protein interfaces together;(3) estimating the probability that each cluster is relevant based on a diverse set of properties;and (4) combining these scores for each PDB entry in order to predict the complex structure. The resulting clusters of biologically relevant interfaces provide a reliable catalog of evolutionary conserved protein-protein interactions. These interfaces, as well as the predicted protein complexes, are available from the protein Interface Server (PInS) website (see Availability and requirements section). Conclusion: Our method demonstrates an almost two-fold reduction of the annotation error rate as evaluated on a large benchmark set of complexes validated from the literature. We also estimate relative contributions of each interface property to the accurate discrimination of biologically relevant interfaces and discuss possible directions for further improving the prediction method.

关键词： protein data bank Solvent Accessible Surface Area Random Forest Classifier protein data bank Entry protein data bank structure

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Integration of open access literature into the RCSB protein data bank using BioLit

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BMC BIOINFORMATICS 2010年第1期11卷 220-220页

作者： Prlic, Andreas Martinez, Marco A. Dimitropoulos, Dimitris Beran, Bojan Yukich, Benjamin T. Rose, Peter W. Bourne, Philip E. Fink, J. Lynn Univ Calif San Diego San Diego Supercomp Ctr La Jolla CA 92093 USA Univ Calif San Diego Skaggs Sch Pharm & Pharmaceut Sci La Jolla CA 92093 USA

Background: Biological data have traditionally been stored and made publicly available through a variety of on-line databases, whereas biological knowledge has traditionally been found in the printed literature. With journals now on-line and providing an increasing amount of open access content, often free of copyright restriction, this distinction between database and literature is blurring. To exploit this opportunity we present the integration of open access literature with the RCSB protein data bank (PDB). Results: BioLit provides an enhanced view of articles with markup of semantic data and links to biological databases, based on the content of the article. For example, words matching to existing biological ontologies are highlighted and database identifiers are linked to their database of origin. Among other functions, it identifies PDB IDs that are mentioned in the open access literature, by parsing the full text for all research articles in PubMed Central (PMC) and exposing the results as simple XML Web Services. Here, we integrate BioLit results with the RCSB PDB website by using these services to find PDB IDs that are mentioned in research articles and subsequently retrieving abstract, figures, and text excerpts for those articles. A new RCSB PDB literature view permits browsing through the figures and abstracts of the articles that mention a given structure. The BioLit Web Services that are providing the underlying data are publicly accessible. A client library is provided that supports querying these services ( Java). Conclusions: The integration between literature and websites, as demonstrated here with the RCSB PDB, provides a broader view for how a given structure has been analyzed and used. This approach detects the mention of a PDB structure even if it is not formally cited in the paper. Other structures related through the same literature references can also be identified, possibly providing new scientific insight. To our knowledge this is the firs

关键词： protein data bank Biological database Document Type Definition protein data bank structure PubMed Central

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MSDmotif: exploring protein sites and motifs

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BMC BIOINFORMATICS 2008年第1期9卷 1-11页

作者： Golovin, Adel Henrick, Kim European Bioinformat Inst EMBL Outstn Cambridge England

Background: protein structures have conserved features - motifs, which have a sufficient influence on the protein function. These motifs can be found in sequence as well as in 3D space. Understanding of these fragments is essential for 3D structure prediction, modelling and drug-design. The protein data bank (PDB) is the source of this information however present search tools have limited 3D options to integrate protein sequence with its 3D structure. Results: We describe here a web application for querying the PDB for ligands, binding sites, small 3D structural and sequence motifs and the underlying database. Novel algorithms for chemical fragments, 3D motifs, phi/psi sequences, super-secondary structure motifs and for small 3D structural motif associations searches are incorporated. The interface provides functionality for visualization, search criteria creation, sequence and 3D multiple alignment options. MSDmotif is an integrated system where a results page is also a search form. A set of motif statistics is available for analysis. This set includes molecule and motif binding statistics, distribution of motif sequences, occurrence of an amino-acid within a motif, correlation of amino-acids side-chain charges within a motif and Ramachandran plots for each residue. The binding statistics are presented in association with properties that include a ligand fragment library. Access is also provided through the distributed Annotation System (DAS) protocol. An additional entry point facilitates XML requests with XML responses. Conclusion: MSDmotif is unique by combining chemical, sequence and 3D data in a single search engine with a range of search and visualisation options. It provides multiple views of data found in the PDB archive for exploring protein structures.

关键词： protein data bank Secondary structure Element Execution Plan protein data bank Entry protein data bank structure

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A study on the flexibility of enzyme active sites

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BMC BIOINFORMATICS 2011年第s1期12卷 1-11页

作者： Weng, Yi-Zhong Chang, Darby Tien-Hao Huang, Yu-Feng Lin, Chih-Wei Natl Cheng Kung Univ Dept Elect Engn Tainan 701 Taiwan Natl Taiwan Univ Dept Comp Sci & Informat Engn Taipei 106 Taiwan

Background: A common assumption about enzyme active sites is that their structures are highly conserved to specifically distinguish between closely similar compounds. However, with the discovery of distinct enzymes with similar reaction chemistries, more and more studies discussing the structural flexibility of the active site have been conducted. Results: Most of the existing works on the flexibility of active sites focuses on a set of pre-selected active sites that were already known to be flexible. This study, on the other hand, proposes an analysis framework composed of a new data collecting strategy, a local structure alignment tool and several physicochemical measures derived from the alignments. The method proposed to identify flexible active sites is highly automated and robust so that more extensive studies will be feasible in the future. The experimental results show the proposed method is (a) consistent with previous works based on manually identified flexible active sites and (b) capable of identifying potentially new flexible active sites. Conclusions: This proposed analysis framework and the former analyses on flexibility have their own advantages and disadvantage, depending on the cause of the flexibility. In this regard, this study proposes an alternative that complements previous studies and helps to construct a more comprehensive view of the flexibility of enzyme active sites.

关键词： structure Alignment Catalytic Residue Enzyme Active Site protein data bank structure Zinc Site

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The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation

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GENOME BIOLOGY 2008年第1期9卷 R8-R8页

作者： Wu, Shirley Liang, Mike P. Altman, Russ B. Stanford Univ Program Biomed Informat Stanford CA 94305 USA Google Inc Mountain View CA 94043 USA Stanford Univ Dept Genet Stanford CA 94305 USA Stanford Univ Dept Bioengn Stanford CA 94305 USA

Structural genomics efforts have led to increasing numbers of novel, uncharacterized protein structures with low sequence identity to known proteins, resulting in a growing need for structure-based function recognition tools. Our method, SeqFEATURE, robustly models protein functions described by sequence motifs using a structural representation. We built a library of models that shows good performance compared to other methods. In particular, SeqFEATURE demonstrates significant improvement over other methods when sequence and structural similarity are low.

关键词： Positive Predictive Value protein data bank Functional Site Enzyme Commission Number protein data bank structure

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PubNet: a flexible system for visualizing literature derived networks

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GENOME BIOLOGY 2005年第9期6卷 R80-R80页

作者： Douglas, SM Montelione, GT Gerstein, M Yale Univ Dept Mol Biophys & Biochem New Haven CT 06520 USA Rutgers State Univ Dept Mol Biol & Biochem Ctr Adv Biotechnol & Med Piscataway NJ 08854 USA Robert Wood Johnson Med Sch Piscataway NJ 08854 USA Yale Univ Dept Comp Sci New Haven CT 06520 USA

We have developed PubNet, a web-based tool that extracts several types of relationships returned by PubMed queries and maps them into networks, allowing for graphical visualization, textual navigation, and topological analysis. PubNet supports the creation of complex networks derived from the contents of individual citations, such as genes, proteins, protein data bank (PDB) IDs, Medical Subject Headings (MeSH) terms, and authors. This feature allows one to, for example, examine a literature derived network of genes based on functional similarity.

关键词： protein data bank Scalable Vector Graphic protein data bank structure protein structure Initiative structure Publication

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Large-scale reverse docking profiles and their applications

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BMC BIOINFORMATICS 2012年第Sup17期13卷 1-10页

作者： Lee, Minho Kim, Dongsup Korea Adv Inst Sci & Technol Dept Bio & Brain Engn Taejon 305701 South Korea

Background: Reverse docking approaches have been explored in previous studies on drug discovery to overcome some problems in traditional virtual screening. However, current reverse docking approaches are problematic in that the target spaces of those studies were rather small, and their applications were limited to identifying new drug targets. In this study, we expanded the scope of target space to a set of all protein structures currently available and developed several new applications of reverse docking method. Results: We generated 2D Matrix of docking scores among all the possible protein structures in yeast and human and 35 famous drugs. By clustering the docking profile data and then comparing them with fingerprint-based clustering of drugs, we first showed that our data contained accurate information on their chemical properties. Next, we showed that our method could be used to predict the druggability of target proteins. We also showed that a combination of sequence similarity and docking profile similarity could predict the enzyme EC numbers more accurately than sequence similarity alone. In two case studies, 5-flurouracil and cycloheximide, we showed that our method can successfully find identifying target proteins. Conclusions: By using a large number of protein structures, we improved the sensitivity of reverse docking and showed that using as many protein structure as possible was important in finding real binding targets.

关键词： protein data bank Virtual Screening Docking Score protein data bank structure Drug Repositioning

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SE: an algorithm for deriving sequence alignment from a pair of superimposed structures

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BMC BIOINFORMATICS 2009年第1-Sup期10卷 S4-S4页

作者： Tai, Chin-Hsien Vincent, James J. Kim, Changhoon Lee, Byungkook NCI Mol Modeling & Bioinformat Sect Mol Biol Lab Ctr Canc ResNIH Bethesda MD 20892 USA Univ Vermont Dept Biol Vermont Genet Network Burlington VT 05405 USA

Background: Generating sequence alignments from superimposed structures is an important part of many structure comparison programs. The accuracy of the alignment affects structure recognition, classification and possibly function prediction. Many programs use a dynamic programming algorithm to generate the sequence alignment from superimposed structures. However, this procedure requires using a gap penalty and, depending on the value of the penalty used, can introduce spurious gaps and misalignments. Here we present a new algorithm, Seed Extension (SE), for generating the sequence alignment from a pair of superimposed structures. The SE algorithm first finds "seeds", which are the pairs of residues, one from each structure, that meet certain stringent criteria for being structurally equivalent. Three consecutive seeds form a seed segment, which is extended along the diagonal of the alignment matrix in both directions. Distance and the amino acid type similarity between the residues are used to resolve conflicts that arise during extension of more than one diagonal. The manually curated alignments in the Conserved Domain database were used as the standard to assess the quality of the sequence alignments. Results: SE gave an average accuracy of 95.9% over 582 pairs of superimposed proteins tested, while CHIMERA, LSQMAN, and DP extracted from SHEBA, which all use a dynamic programming algorithm, yielded 89.9%, 90.2% and 91.0%, respectively. For pairs of proteins with low sequence or structural similarity, SE produced alignments up to 18% more accurate on average than the next best scoring program. Improvement was most pronounced when the two superimposed structures contained equivalent helices or beta-strands that crossed at an angle. When the SE algorithm was implemented in SHEBA to replace the dynamic programming routine, the alignment accuracy improved by 10% on average for structure pairs with RMSD between 2 and 4 angstrom. SE also used considerably less CPU time t

关键词： Dynamic Programming Algorithm Conserve Domain database Residue Pair Reference Alignment protein data bank structure

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BSSF: a fingerprint based ultrafast binding site similarity search and function analysis server

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BMC BIOINFORMATICS 2010年第1期11卷 1-11页

作者： Xiong, Bing Wu, Jie Burk, David L. Xue, Mengzhu Jiang, Hualiang Shen, Jingkang Chinese Acad Sci Shanghai Inst Mat Med State Key Lab Drug Res Shanghai 201203 Peoples R China SUNY Stony Brook Dept Appl Math & Stat Stony Brook NY 11794 USA McGill Univ Dept Biochem Montreal PQ H3A 1A4 Canada

Background: Genome sequencing and post-genomics projects such as structural genomics are extending the frontier of the study of sequence-structure-function relationship of genes and their products. Although many sequence/structure-based methods have been devised with the aim of deciphering this delicate relationship, there still remain large gaps in this fundamental problem, which continuously drives researchers to develop novel methods to extract relevant information from sequences and structures and to infer the functions of newly identified genes by genomics technology. Results: Here we present an ultrafast method, named BSSF(Binding Site Similarity & Function), which enables researchers to conduct similarity searches in a comprehensive three-dimensional binding site database extracted from PDB structures. This method utilizes a fingerprint representation of the binding site and a validated statistical Z-score function scheme to judge the similarity between the query and database items, even if their similarities are only constrained in a sub-pocket. This fingerprint based similarity measurement was also validated on a known binding site dataset by comparing with geometric hashing, which is a standard 3D similarity method. The comparison clearly demonstrated the utility of this ultrafast method. After conducting the database searching, the hit list is further analyzed to provide basic statistical information about the occurrences of Gene Ontology terms and Enzyme Commission numbers, which may benefit researchers by helping them to design further experiments to study the query proteins. Conclusions: This ultrafast web-based system will not only help researchers interested in drug design and structural genomics to identify similar binding sites, but also assist them by providing further analysis of hit list from database searching.

关键词： protein data bank protein data bank Entry protein data bank structure Dissimilarity Score Fragment Number

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MolTalk - a programming library for protein structures and structure analysis

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BMC BIOINFORMATICS 2004年第1期5卷 39-39页

作者： Diemand, AV Scheib, H Univ Lausanne CH-1066 Epalinges Switzerland Swiss Inst Bioinformat CH-1066 Epalinges Switzerland Univ Geneva CH-1211 Geneva 4 Switzerland Ctr Med Univ Geneva Swiss Inst Bioinformat CH-1211 Geneva 4 Switzerland

Background: Two of the mostly unsolved but increasingly urgent problems for modern biologists are a) to quickly and easily analyse protein structures and b) to comprehensively mine the wealth of information, which is distributed along with the 3D co-ordinates by the protein data bank (PDB). Tools which address this issue need to be highly flexible and powerful but at the same time must be freely available and easy to learn. Results: We present MolTalk, an elaborate programming language, which consists of the programming library libmoltalk implemented in Objective-C and the Smalltalk-based interpreter MolTalk. MolTalk combines the advantages of an easy to learn and programmable procedural scripting with the flexibility and power of a full programming language. An overview of currently available applications of MolTalk is given and with PDBChainSaw one such application is described in more detail. PDBChainSaw is a MolTalk-based parser and information extraction utility of PDB files. Weekly updates of the PDB are synchronised with PDBChainSaw and are available for free download from the MolTalk project page http://*** following the link to PDBChainSaw. For each chain in a protein structure, PDBChainSaw extracts the sequence from its coordinates and provides additional information from the PDB-file header section, such as scientific organism, compound name, and EC code. Conclusion: MolTalk provides a rich set of methods to analyse and even modify experimentally determined or modelled protein structures. These methods vary in complexity and are thus suitable for beginners and advanced programmers alike. We envision MolTalk to be most valuable in the following applications:

关键词： protein data bank Class Diagram Programming Library protein data bank File protein data bank structure

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