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Domain-based small molecule binding site annotation

BMC BIOINFORMATICS 2006年第1期7卷 152-152页

作者： Snyder, KA Feldman, HJ Dumontier, M Salama, JJ Hogue, CWV Blueprint Initiat Toronto ON M5T 1K4 Canada Carleton Univ Dept Biol Ottawa ON K1S 5B6 Canada Mt Sinai Hosp Samuel Lunenfeld Res Inst Toronto ON M5G 1X5 Canada

Background: Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction database ( SMID), a database of protein domain-small molecule interactions, was created using structural data from the protein data bank (PDB). More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overprediction binding sites. Description: Using a set of co-crystallized protein-small molecule structures as a starting point, SMID interactions were generated by identifying protein domains that bind to small molecules, using NCBI's Reverse Position Specific BLAST (RPS-BLAST) algorithm. SMID records are available for viewing at http:// smid. blueprint. org. The SMID-BLAST tool provides accurate transitive annotation of small-molecule binding sites for proteins not found in the PDB. Given a protein sequence, SMID-BLAST identifies domains using RPS-BLAST and then lists potential small molecule ligands based on SMID records, as well as their aligned binding sites. A heuristic ligand score is calculated based on E-value, ligand residue identity and domain entropy to assign a level of confidence to hits found. SMID-BLAST predictions were validated against a set of 793 experimental small molecule interactions from the PDB, of which 472 (60%) of predicted interactions identically matched the experimental small molecule and of these, 344 had greater than 80% of the binding site residues correctly identified. Further, we estimate that 45% of predictions which were not observed in the PDB validation set may be true positives. Conclusion: By focusing on protein doma

关键词： protein data bank Conserve Domain database Position Specific Scoring Matrix protein data bank file Bind Site Residue

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Potentials 'R'Us web-server for protein energy estimations with coarse-grained knowledge-based potentials

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BMC BIOINFORMATICS 2010年第1期11卷 92-92页

作者： Feng, Yaping Kloczkowski, Andrzej Jernigan, Robert L. Iowa State Univ Dept Biochem Biophys & Mol Biol Ames IA 50011 USA Iowa State Univ LH Baker Ctr Bioinformat & Biol Stat Ames IA 50011 USA

Background: Knowledge-based potentials have been widely used in the last 20 years for fold recognition, protein structure prediction from amino acid sequence, ligand binding, protein design, and many other purposes. However generally these are not readily accessible online. Results: Our new knowledge-based potential server makes available many of these potentials for easy use to automatically compute the energies of protein structures or models supplied. Our web server for protein energy estimation uses four-body potentials, short-range potentials, and 23 different two-body potentials. Users can select potentials according to their needs and preferences. files containing the coordinates of protein atoms in the PDB format can be uploaded as input. The results will be returned to the user's email address. Conclusions: Our Potentials 'R'Us server is an easily accessible, freely available tool with a web interface that collects all existing and future protein coarse-grained potentials and computes energies of multiple structural models.

关键词： protein data bank protein Structure Prediction Fold Recognition Nuclear Magnetic Resonance Structure protein data bank file

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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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Automated functional classification of experimental and predicted protein structures

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BMC BIOINFORMATICS 2006年第1期7卷 278-278页

作者： Wang, Kai Samudrala, Ram Univ Washington Dept Microbiol Computat Genom Grp Seattle WA 98195 USA

Background: proteins that are similar in sequence or structure may perform different functions in nature. In such cases, function cannot be inferred from sequence or structural similarity. Results: We analyzed experimental structures belonging to the Structural Classification of proteins ( SCOP) database and showed that about half of them belong to multi-functional fold families for which protein similarity alone is not adequate to assign function. We also analyzed predicted structures from the LiveBench and the PDB-CAFASP experiments and showed that accurate homology-based functional assignments cannot be achieved approximately one third of the time, when the protein is a member of a multi-functional fold family. We then conducted extended performance evaluation and comparisons on both experimental and predicted structures using our Functional Signatures from Structural Alignments (FSSA) algorithm that we previously developed to handle the problem of classifying proteins belonging to multi-functional fold families. Conclusion: The results indicate that the FSSA algorithm has better accuracy when compared to homology-based approaches for functional classification of both experimental and predicted protein structures, in part due to its use of local, as opposed to global, information for classifying function. The FSSA algorithm has also been implemented as a webserver and is available at http://***/fssa.

关键词： protein data bank Fold Recognition Functional Assignment protein data bank file Fold Family

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Accessibility and partner number of protein residues, their relationship and a webserver, ContPlot for their display

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BMC BIOINFORMATICS 2009年第1期10卷 103-103页

作者： Pal, Arumay Bahadur, Ranjit Prasad Ray, Partha Sarathi Chakrabarti, Pinak Bose Inst Dept Biochem Kolkata 700054 India Bose Inst Bioinformat Ctr Kolkata 700054 India

Background: Depending on chemical features residues have preferred locations-interior or exterior-in protein structures, which also determine how many other residues are found around them. The close packing of residues is the hallmark of protein interior and protein-protein interaction sites. Results: The average values of accessible surface area (ASA) and partner number (PN, the number of other residues within a distance of 4.5 angstrom from any atom of a given residue) of different residues have been determined and a webserver, ContPlot has been designed to display these values (relative to the average values) along the protein sequence. This would be useful to visually identify residues that are densely packed, or those involved in protein-protein interactions. The skewness observed in the distribution of PNs is indicative of the hydrophobic or hydrophilic nature of the residue. The variation of ASA with PN can be analytically expressed in terms of a cubic equation. These equations (one for each residue) can be used to estimate the ASA of a polypeptide chain using the PNs of the individual residues in the structure. Conclusion: The atom-based PNs (obtained by counting surrounding atoms) are highly correlated to the residue-based PN, indicating that the latter can adequately capture the atomic details of packing. The average values of ASA and PN associated with each residue should be useful in protein structure prediction or fold-recognition algorithm. ContPlot would provide a handy tool to assess the importance of a residue in the protein structure or interaction site.

关键词： protein data bank Hydrophobic Residue Accessible Surface Area Solvent Accessible Surface Area protein data bank file

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The protein-DNA Interface database

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BMC BIOINFORMATICS 2010年第1期11卷 262-262页

作者： Norambuena, Tomas Melo, Francisco Pontificia Univ Catolica Chile Fac Ciencias Biol Dept Mol Genet & Microbiol Santiago Chile

The protein-DNA Interface database (PDIdb) is a repository containing relevant structural information of protein-DNA complexes solved by X-ray crystallography and available at the protein data bank. The database includes a simple functional classification of the protein-DNA complexes that consists of three hierarchical levels: Class, Type and Subtype. This classification has been defined and manually curated by humans based on the information gathered from several sources that include PDB, PubMed, CATH, SCOP and COPS. The current version of the database contains only structures with resolution of 2.5 angstrom or higher, accounting for a total of 922 entries. The major aim of this database is to contribute to the understanding of the main rules that underlie the molecular recognition process between DNA and proteins. To this end, the database is focused on each specific atomic interface rather than on the separated binding partners. Therefore, each entry in this database consists of a single and independent protein-DNA interface. We hope that PDIdb will be useful to many researchers working in fields such as the prediction of transcription factor binding sites in DNA, the study of specificity determinants that mediate enzyme recognition events, engineering and design of new DNA binding proteins with distinct binding specificity and affinity, among others. Finally, due to its friendly and easy-to-use web interface, we hope that PDIdb will also serve educational and teaching purposes.

关键词： protein data bank protein data bank Code Interaction Class Biological Unit protein data bank file

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RNA FRABASE 2.0: an advanced web-accessible database with the capacity to search the three-dimensional fragments within RNA structures

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BMC BIOINFORMATICS 2010年第1期11卷 231-231页

作者： Popenda, Mariusz Szachniuk, Marta Blazewicz, Marek Wasik, Szymon Burke, Edmund K. Blazewicz, Jacek Adamiak, Ryszard W. Polish Acad Sci Inst Bioorgan Chem Poznan Poland Poznan Univ Tech Inst Comp Sci Poznan Poland Poznan Supercomp & Networking Ctr Poznan Poland Univ Nottingham Automated Scheduling Optimisat & Planning Grp Sch Comp Sci Nottingham NG7 2RD England

Background: Recent discoveries concerning novel functions of RNA, such as RNA interference, have contributed towards the growing importance of the field. In this respect, a deeper knowledge of complex three-dimensional RNA structures is essential to understand their new biological functions. A number of bioinformatic tools have been proposed to explore two major structural databases (PDB, NDB) in order to analyze various aspects of RNA tertiary structures. One of these tools is RNA FRABASE 1.0, the first web-accessible database with an engine for automatic search of 3D fragments within PDB-derived RNA structures. This search is based upon the user-defined RNA secondary structure pattern. In this paper, we present and discuss RNA FRABASE 2.0. This second version of the system represents a major extension of this tool in terms of providing new data and a wide spectrum of novel functionalities. An intuitionally operated web server platform enables very fast user-tailored search of three-dimensional RNA fragments, their multi-parameter conformational analysis and visualization. Description: RNA FRABASE 2.0 has stored information on 1565 PDB-deposited RNA structures, including all NMR models. The RNA FRABASE 2.0 search engine algorithms operate on the database of the RNA sequences and the new library of RNA secondary structures, coded in the dot-bracket format extended to hold multi-stranded structures and to cover residues whose coordinates are missing in the PDB files. The library of RNA secondary structures (and their graphics) is made available. A high level of efficiency of the 3D search has been achieved by introducing novel tools to formulate advanced searching patterns and to screen highly populated tertiary structure elements. RNA FRABASE 2.0 also stores data and conformational parameters in order to provide "on the spot" structural filters to explore the three-dimensional RNA structures. An instant visualization of the 3D RNA structures is provided. RNA FRABASE

关键词： protein data bank Menu Item Conformational Parameter protein data bank file Dinucleotide Step

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STING Millennium Suite: integrated software for extensive analyses of 3d structures of proteins and their complexes

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BMC BIOINFORMATICS 2004年第1期5卷 107-107页

作者： Higa, RH Togawa, RC Montagner, AJ Palandrani, JCF Okimoto, IKS Kuser, PR Yamagishi, MEB Mancini, AL Neshich, G Empresa Brasileira Pesquisa Agropecuaria Ctr Nacl Pesquisa Agropecuaria Campinas SP Brazil Empresa Brasileira Pesquisa Agropecuaria Embrapa Recursos Genet & Biotecnol Lab Bioinformat Brasilia DF Brazil

Background: The integration of many aspects of protein/DNA structure analysis is an important requirement for software products in general area of structural bioinformatics. In fact, there are too few software packages on the internet which can be described as successful in this respect. We might say that what is still missing is publicly available, web based software for interactive analysis of the sequence/structure/ function of proteins and their complexes with DNA and ligands. Some of existing software packages do have certain level of integration and do offer analysis of several structure related parameters, however not to the extent generally demanded by a user. Results: We are reporting here about new Sting Millennium Suite (SMS) version which is fully accessible ( including for local files at client end), web based software for molecular structure and sequence/structure/ function analysis. The new SMS client version is now operational also on Linux boxes and it works with non-public pdb formatted files (structures not deposited at the RCSB/ PDB), eliminating earlier requirement for the registration if SMS components were to be used with user's local files. At the same time the new SMS offers some important additions and improvements such as link to ProTherm as well as significant re-engineering of SMS component ConSSeq. Also, we have added 3 new SMS mirror sites to existing network of global SMS servers: Argentina, Japan and Spain. Conclusion: SMS is already established software package and many key data base and software servers worldwide, do offer either a link to, or host the SMS. SMS ((s) under bar ting (m) under bar illennium (s) under bar uite) is web-based publicly available software developed to aid researches in their quest for translating information about the structures of macromolecules into knowledge. SMS allows to a user to interactively analyze molecular structures, cross-referencing visualized information with a correlated one, available acro

关键词： protein data bank Local file Atomic Contact Java Programming Language protein data bank file

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Indel PDB: A database of structural insertions and deletions derived from sequence alignments of closely related proteins

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BMC BIOINFORMATICS 2008年第1期9卷 293-293页

作者： Hsing, Michael Cherkasov, Artem Univ British Columbia Fac Grad Studies Bioinformat Grad Program Vancouver BC V5T 4S6 Canada Univ British Columbia Dept Med Div Infect Dis Fac Med Vancouver BC V5Z 3J5 Canada

Background: Insertions and deletions (indels) represent a common type of sequence variations, which are less studied and pose many important biological questions. Recent research has shown that the presence of sizable indels in protein sequences may be indicative of protein essentiality and their role in protein interaction networks. Examples of utilization of indels for structure-based drug design have also been recently demonstrated. Nonetheless many structural and functional characteristics of indels remain less researched or unknown. Description: We have created a web- based resource, Indel PDB, representing a structural database of insertions/ deletions identified from the sequence alignments of highly similar proteins found in the protein data bank (PDB). Indel PDB utilized large amounts of available structural information to characterize 1-, 2- and 3- dimensional features of indel sites. Indel PDB contains 117,266 non- redundant indel sites extracted from 11,294 indel- containing proteins. Unlike loop databases, Indel PDB features more indel sequences with secondary structures including alpha- helices and beta- sheets in addition to loops. The insertion fragments have been characterized by their sequences, lengths, locations, secondary structure composition, solvent accessibility, protein domain association and three dimensional structures. Conclusion: By utilizing the data available in Indel PDB, we have studied and presented here several sequence and structural features of indels. We anticipate that Indel PDB will not only enable future functional studies of indels, but will also assist protein modeling efforts and identification of indel- directed drug binding sites.

关键词： protein data bank Length Distribution Solvent Accessibility protein data bank file Amino Acid Usage

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PDB-UF: database of predicted enzymatic functions for unannotated protein structures from structural genomics

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BMC BIOINFORMATICS 2006年第1期7卷 53-53页

作者： von Grotthuss, M Plewczynski, D Ginalski, K Rychlewski, L Shakhnovich, EI Harvard Univ Dept Chem & Biol Chem Cambridge MA 02138 USA BioInfoBank Inst PL-60744 Poznan Poland Adam Mickiewicz Univ Dept Phys Bioinformat Unit PL-61614 Poznan Poland

Background: The number of protein structures from structural genomics centers dramatically increases in the protein data bank (PDB). Many of these structures are functionally unannotated because they have no sequence similarity to proteins of known function. However, it is possible to successfully infer function using only structural similarity. Results: Here we present the PDB-UF database, a web-accessible collection of predictions of enzymatic properties using structure-function relationship. The assignments were conducted for three-dimensional protein structures of unknown function that come from structural genomics initiatives. We show that 4 hypothetical proteins ( with PDB accession codes: 1VH0, 1NS5, 1O6D, and 1TO0), for which standard BLAST tools such as PSI-BLAST or RPS-BLAST failed to assign any function, are probably methyltransferase enzymes. Conclusion: We suggest that the structure-based prediction of an EC number should be conducted having the different similarity score cutoff for different protein folds. Moreover, performing the annotation using two different algorithms can reduce the rate of false positive assignments. We believe, that the presented web-based repository will help to decrease the number of protein structures that have functions marked as "unknown" in the PDB file.

关键词： protein data bank protein data bank file Enzymatic Classification protein data bank Chain Structural Genomic Initiative

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