PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “genomic structure”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources
PubMed2006

Comprehensive genome analysis of 203 genomes provides structural genomics with new insights into protein family space.

We present an analysis of 203 completed genomes in the Gene3D resource (including 17 eukaryotes), which demonstrates that the number of protein families is continually expanding over time and that singleton-sequences appear to be an intrinsic part of the genomes. A significant proportion of the proteomes can be assigned to fewer than 6000 well-characterized domain families with the remaining domain-like regions belonging to a much larger number of small uncharacterized families that are largely species specific. Our comprehensive domain annotation of 203 genomes enables us to provide more accurate estimates of the number of multi-domain proteins found in the three kingdoms of life than previous calculations. We find that 67% of eukaryotic sequences are multi-domain compared with 56% of sequences in prokaryotes. By measuring the domain coverage of genome sequences, we show that the structural genomics initiatives should aim to provide structures for less than a thousand structurally uncharacterized Pfam families to achieve reasonable structural annotation of the genomes. However, in large families, additional structures should be determined as these would reveal more about the evolution of the family and enable a greater understanding of how function evolves.

Algorithms↗
PubMed1999

A phylogenetic approach to target selection for structural genomics: solution structure of YciH.

Structural genomics presents an enormous challenge with up to 100 000 protein targets in the human genome alone. At current rates of structure deter-mination, judicious selection of targets is necessary. Here, a phylogenetic approach to target selection is described which makes use of the National Center for Biotechnology Information database of Clusters of Orthologous Groups (COGS). The strategy is designed so that each new protein structure is likely to provide novel sequence-fold information. To demonstrate this approach, the NMR solution structure of YciH (COG0023), a putative translation initiation factor from Escherichia coli, has been determined and its fold classified. YciH is an ortholog of eIF-1/SUI1, an integral component of the translation initiation complex in eukaryotes. The structure consists of two antiparallel alpha-helices packed against the same side of a five-stranded beta-sheet. The first 31 residues of the 11.5 kDa protein are unstructured in solution. Comparative analysis indicates that the folded portion of YciH resembles a number of structures with the alpha-beta plait topology, though its sequence is not homologous to any of them. Thus, the phylogenetic approach to target selection described here was used successfully to identify a new homologous superfamily within this topology.

Amino Acid Sequence↗
PubMed2005

Expectations from structural genomics revisited: an analysis of structural genomics targets.

BACKGROUND: Current structural genomics projects are being driven by two main goals; to produce a representative set of protein folds that could be used as templates for comparative modeling purposes, and to provide insight into the function of the currently unannotated protein sequences. Such projects may reveal that a newly determined protein structure shares structural similarity with a previously observed structure or that it is a novel fold. The manner in which structure can be used to suggest the function of a protein will depend on the number and diversity of homologous sequences and the extent to which these sequences are functionally characterized. METHOD AND RESULTS: Using sequence searching methods, we analyzed structural genomics target sequences to ascertain if they were members of functionally characterized protein families, protein families of unknown function, or orphan sequences. This analysis provided an indication of what could be expected to emerge from structural genomics projects. Matches were found to approximately 25% of the current functionally unannotated protein families in the PFAM database (protein families database of alignments and hidden Markov models). The 16% of strict orphan sequences will be the most problematic if their structures reveal novel folds. However, out of the remaining target sequences that match families whose members are largely of unknown function, 28% are particularly interesting in that they are part of protein families with considerable sequence diversity. CONCLUSION: The determination of a new structure of a member of these families is likely to offer considerable insight into possible functional roles of these proteins even if it is a new fold. Mapping the sequence conservation onto the structure may reveal functionally important residues for further study by experimental methods.

Databases, Protein↗
PubMed2003

Overview of structural genomics: from structure to function.

The unprecedented increase in the number of new protein sequences arising from genomics and proteomics highlights directly the need for methods to rapidly and reliably determine the molecular and cellular functions of these proteins. One such approach, structural genomics, aims to delineate the total repertoire of protein folds, thereby providing three-dimensional portraits for all proteins in a living organism and to infer molecular functions of the proteins. The goal of obtaining protein structures on a genomic scale has motivated the development of high-throughput technologies for macromolecular structure determination, which have begun to produce structures at a greater rate than previously possible. These new structures have revealed many unexpected functional and evolution relationships that were hidden at the sequence level.

Amino Acid Sequence↗
PubMed1998

Mycobacterial genome structure.

Genome maps have been constructed for the mycobacterial pathogens Mycobacterium leprae and Mycobacterium tuberculosis, as well as for the attenuated vaccine strain Mycobacterium bovis BCG Pasteur. While the chromosomes of M. tuberculosis and M. bovis BCG Pasteur show extensive conservation at the gross level, comparison with M. leprae revealed a high degree of diversification, with a mosaic-like pattern apparent. The ordered libraries of M. tuberculosis and M. leprae produced during the course of these studies played a central role in the genome sequencing projects of these two bacilli, showing the utility of this approach for systematic sequencing of bacterial genomes.

Chromosome Mapping↗
PubMed2002

Structural genomics: bridging functional genomics and structure-based drug design.

Considerable advances in structural genomics have been witnessed in the last year. Several pilot studies have begun to report their initial results, and new centers have been funded to join the endeavor. The legacies of the genome sequencing efforts, namely high-throughput molecular biology and whole-organism genome sequences, have been integrated as front-end modules for structural genomics pipelines. Impressive advances have been made in NMR spectroscopy and X-ray crystallography. New methods in structural bioinformatics and computational chemistry have been published that provide the means to exploit the wealth of new information in drug discovery. Not surprisingly, the biopharmaceutical industry has been quick to recognize the benefits of these new developments and has begun to adopt them. This article reviews recent results from structural genomics initiatives and the potential applications of new information and technologies in the drug discovery process.

Drug Design↗
PubMed2005

Functional coverage of the human genome by existing structures, structural genomics targets, and homology models.

The bias in protein structure and function space resulting from experimental limitations and targeting of particular functional classes of proteins by structural biologists has long been recognized, but never continuously quantified. Using the Enzyme Commission and the Gene Ontology classifications as a reference frame, and integrating structure data from the Protein Data Bank (PDB), target sequences from the structural genomics projects, structure homology derived from the SUPERFAMILY database, and genome annotations from Ensembl and NCBI, we provide a quantified view, both at the domain and whole-protein levels, of the current and projected coverage of protein structure and function space relative to the human genome. Protein structures currently provide at least one domain that covers 37% of the functional classes identified in the genome; whole structure coverage exists for 25% of the genome. If all the structural genomics targets were solved (twice the current number of structures in the PDB), it is estimated that structures of one domain would cover 69% of the functional classes identified and complete structure coverage would be 44%. Homology models from existing experimental structures extend the 37% coverage to 56% of the genome as single domains and 25% to 31% for complete structures. Coverage from homology models is not evenly distributed by protein family, reflecting differing degrees of sequence and structure divergence within families. While these data provide coverage, conversely, they also systematically highlight functional classes of proteins for which structures should be determined. Current key functional families without structure representation are highlighted here; updated information on the "most wanted list" that should be solved is available on a weekly basis from http://function.rcsb.org:8080/pdb/function_distribution/index.html.

Databases, Protein↗
PubMed2007

Evaluating protein structures determined by structural genomics consortia.

Structural genomics projects are providing large quantities of new 3D structural data for proteins. To monitor the quality of these data, we have developed the protein structure validation software suite (PSVS), for assessment of protein structures generated by NMR or X-ray crystallographic methods. PSVS is broadly applicable for structure quality assessment in structural biology projects. The software integrates under a single interface analyses from several widely-used structure quality evaluation tools, including PROCHECK (Laskowski et al., J Appl Crystallog 1993;26:283-291), MolProbity (Lovell et al., Proteins 2003;50:437-450), Verify3D (Luthy et al., Nature 1992;356:83-85), ProsaII (Sippl, Proteins 1993;17: 355-362), the PDB validation software, and various structure-validation tools developed in our own laboratory. PSVS provides standard constraint analyses, statistics on goodness-of-fit between structures and experimental data, and knowledge-based structure quality scores in standardized format suitable for database integration. The analysis provides both global and site-specific measures of protein structure quality. Global quality measures are reported as Z scores, based on calibration with a set of high-resolution X-ray crystal structures. PSVS is particularly useful in assessing protein structures determined by NMR methods, but is also valuable for assessing X-ray crystal structures or homology models. Using these tools, we assessed protein structures generated by the Northeast Structural Genomics Consortium and other international structural genomics projects, over a 5-year period. Protein structures produced from structural genomics projects exhibit quality score distributions similar to those of structures produced in traditional structural biology projects during the same time period. However, while some NMR structures have structure quality scores similar to those seen in higher-resolution X-ray crystal structures, the majority of NMR structures have lower scores. Potential reasons for this "structure quality score gap" between NMR and X-ray crystal structures are discussed.

Computational Biology↗
PubMed2004

A data management system for structural genomics.

BACKGROUND: Structural genomics (SG) projects aim to determine thousands of protein structures by the development of high-throughput techniques for all steps of the experimental structure determination pipeline. Crucial to the success of such endeavours is the careful tracking and archiving of experimental and external data on protein targets. RESULTS: We have developed a sophisticated data management system for structural genomics. Central to the system is an Oracle-based, SQL-interfaced database. The database schema deals with all facets of the structure determination process, from target selection to data deposition. Users access the database via any web browser. Experimental data is input by users with pre-defined web forms. Data can be displayed according to numerous criteria. A list of all current target proteins can be viewed, with links for each target to associated entries in external databases. To avoid unnecessary work on targets, our data management system matches protein sequences weekly using BLAST to entries in the Protein Data Bank and to targets of other SG centers worldwide. CONCLUSION: Our system is a working, effective and user-friendly data management tool for structural genomics projects. In this report we present a detailed summary of the various capabilities of the system, using real target data as examples, and indicate our plans for future enhancements.

Journal Article↗
PubMed2005

Protein surface analysis for function annotation in high-throughput structural genomics pipeline.

Structural genomics (SG) initiatives are expanding the universe of protein fold space by rapidly determining structures of proteins that were intentionally selected on the basis of low sequence similarity to proteins of known structure. Often these proteins have no associated biochemical or cellular functions. The SG success has resulted in an accelerated deposition of novel structures. In some cases the structural bioinformatics analysis applied to these novel structures has provided specific functional assignment. However, this approach has also uncovered limitations in the functional analysis of uncharacterized proteins using traditional sequence and backbone structure methodologies. A novel method, named pvSOAR (pocket and void Surface of Amino Acid Residues), of comparing the protein surfaces of geometrically defined pockets and voids was developed. pvSOAR was able to detect previously unrecognized and novel functional relationships between surface features of proteins. In this study, pvSOAR is applied to several structural genomics proteins. We examined the surfaces of YecM, BioH, and RpiB from Escherichia coli as well as the CBS domains from inosine-5'-monosphate dehydrogenase from Streptococcus pyogenes, conserved hypothetical protein Ta549 from Thermoplasm acidophilum, and CBS domain protein mt1622 from Methanobacterium thermoautotrophicum with the goal to infer information about their biochemical function.

Adenine Nucleotides↗
PubMed2004

Backbone solution structures of proteins using residual dipolar couplings: application to a novel structural genomics target.

Structural genomics (or proteomics) activities are critically dependent on the availability of high-throughput structure determination methodology. Development of such methodology has been a particular challenge for NMR based structure determination because of the demands for isotopic labeling of proteins and the requirements for very long data acquisition times. We present here a methodology that gains efficiency from a focus on determination of backbone structures of proteins as opposed to full structures with all sidechains in place. This focus is appropriate given the presumption that many protein structures in the future will be built using computational methods that start from representative fold family structures and replace as many as 70% of the sidechains in the course of structure determination. The methodology we present is based primarily on residual dipolar couplings (RDCs), readily accessible NMR observables that constrain the orientation of backbone fragments irrespective of separation in space. A new software tool is described for the assembly of backbone fragments under RDC constraints and an application to a structural genomics target is presented. The target is an 8.7 kDa protein from Pyrococcus furiosus, PF1061, that was previously not well annotated, and had a nearest structurally characterized neighbor with only 33% sequence identity. The structure produced shows structural similarity to this sequence homologue, but also shows similarity to other proteins, which suggests a functional role in sulfur transfer. Given the backbone structure and a possible functional link this should be an ideal target for development of modeling methods.

Amino Acid Sequence↗
PubMed2002

Genomic structure of mouse SPI-C and genomic structure and expression pattern of human SPI-C.

Erythroblast transformation-specific domain (ETS) transcription factors regulate some of the critical molecular mechanisms controlling the differentiation of multipotent haematopoietic progenitor cells into effector B-lymphocytes. The SPI-group ETS-protein transcription factors PU.1 and SPI-B play essential and, although coexpressed and binding to similar DNA sequences, unique roles in B-cell differentiation in mice. Mouse SPI-C is an SPI-group ETS protein expressed temporarily during B-cell development and in macrophages. Here we present the genomic organization of the mouse SPI-C gene, and show by rapid amplification of cDNA ends (5'-RACE) analysis that transcription of the mouse SPI-C mRNA starts at a single site producing a single processed transcript. We have also isolated a cDNA clone encoding the human SPI-C homologue, which displays 65% amino acid identity to the murine protein. In addition, we show that the genomic structure of the human and mouse genes are similar, containing a 5' non-coding exon followed by five coding exons. Human SPI-C mRNA is preferentially detected in foetal and adult spleen, lymph nodes and at lower levels in bone marrow and foetal liver. Finally a phylogenetic prediction analysis of SPI-group protein sequences suggest that the SPI-C proteins form a distinct subgroup, with human SPI-C being closest related to the mouse SPI-C protein.

Amino Acid Sequence↗
PubMed2003

Structural genomics: computational methods for structure analysis.

The success of structural genomics initiatives requires the development and application of tools for structure analysis, prediction, and annotation. In this paper we review recent developments in these areas; specifically structure alignment, the detection of remote homologs and analogs, homology modeling and the use of structures to predict function. We also discuss various rationales for structural genomics initiatives. These include the structure-based clustering of sequence space and genome-wide function assignment. It is also argued that structural genomics can be integrated into more traditional biological research if specific biological questions are included in target selection strategies.

Amino Acid Motifs↗
PubMed2006

Toward the structural genomics of complexes: crystal structure of a PE/PPE protein complex from Mycobacterium tuberculosis.

The developing science called structural genomics has focused to date mainly on high-throughput expression of individual proteins, followed by their purification and structure determination. In contrast, the term structural biology is used to denote the determination of structures, often complexes of several macromolecules, that illuminate aspects of biological function. Here we bridge structural genomics to structural biology with a procedure for determining protein complexes of previously unknown function from any organism with a sequenced genome. From computational genomic analysis, we identify functionally linked proteins and verify their interaction in vitro by coexpression/copurification. We illustrate this procedure by the structural determination of a previously unknown complex between a PE and PPE protein from the Mycobacterium tuberculosis genome, members of protein families that constitute approximately 10% of the coding capacity of this genome. The predicted complex was readily expressed, purified, and crystallized, although we had previously failed in expressing individual PE and PPE proteins on their own. The reason for the failure is clear from the structure, which shows that the PE and PPE proteins mate along an extended apolar interface to form a four-alpha-helical bundle, where two of the alpha-helices are contributed by the PE protein and two by the PPE protein. Our entire procedure for the identification, characterization, and structural determination of protein complexes can be scaled to a genome-wide level.

Bacterial Proteins↗
PubMed2002

Target space for structural genomics revisited.

MOTIVATION: Structural genomics eventually aims at determining structures for all proteins. However, in the beginning experimentalists are likely to focus on globular proteins to achieve a rapid basic coverage of protein sequence space. How many proteins will structural genomics have to target? How many proteins will be excluded since we already have structural information for these or since they are not globular? We have to answer these questions in the context of our target selection for the North-East Structural Genomics Consortium (NESG). RESULTS: We estimated that structural information is available for about 6-38% of all proteins; 6% if we require high accuracy in comparative modelling, 38% if we are satisfied with having a rough idea about the fold. Excluding all regions that are not globular, we found that structural genomics may have to target about 48% of all proteins. This corresponded to a similar percentage of residues of the entire proteomes (52%). We explored a number of different strategies to cluster protein space in order to find the number of families representing these 48% of structurally unknown proteins. For the subset of all entirely sequenced eukaryotes, we found over 18 000 fragment clusters each of which may be a suitable target for structural genomics. AVAILABILITY: All data are available from the authors, most results are summarized at: http://cubic.bioc.columbia.edu/genomes/RES/2002_bioinformatics/

Algorithms↗
PubMed2002

The TB structural genomics consortium: providing a structural foundation for drug discovery.

Structural genomics, the large-scale determination of protein structures, promises to provide a broad structural foundation for drug discovery. The tuberculosis (TB) Structural Genomics Consortium is devoted to encouraging, coordinating, and facilitating the determination of structures of proteins from Mycobacterium tuberculosis and hopes to determine 400 TB protein structures over 5 years. The Consortium has determined structures of 28 proteins from TB to date. These protein structures are already providing a basis for drug discovery efforts.

Acyltransferases↗