Structural Genomics

SUMMARY Grapevine fanleaf virus (GFLV) is responsible for fan- leaf degeneration, which is one of the most severe virus diseases of grapevines worldwide. GFLV causes substan- tial crop losses, reduces fruit quality and shortens the longevity of grapevines in the vineyard. GFLV is trans- mitted specifically from grapevine to grapevine by the ectoparasitic nematode Xiphinema index, and belongs to the

Background: Many characterised proteins contain metal ions, small organic molecules or modified residues. In contrast, the huge amount of data generated by genome projects consists exclusively of sequences with almost no annotation. One of the goals of the structural genomics initiative is to provide representative three-dimensional (3-D) structures for as many protein/domain folds as possible to allow successful homology modelling. However, important functional features such as metal co-ordination or a type of prosthetic group are not always conserved in homologous proteins. So far, the problem of correct annotation of bioinorganic proteins has been largely ignored by the bioinformatics community and information on bioinorganic centres obtained by methods other than crystallography or NMR is only available in literature databases.

Results: COMe (Co-Ordination of Metals) represents the ontology for bioinorganic and other small molecule centres in complex proteins. COMe consists of three types of entities: 'bioinorganic motif' (BIM), 'molecule' (MOL), and 'complex proteins' (PRX), with each entity being assigned a unique identifier. A BIM consists of at least one centre (metal atom, inorganic cluster, organic molecule) and two or more endogenous and/or exogenous ligands. BIMs are represented as one-dimensional (1-D) strings and 2-D diagrams. A MOL entity represents a 'small molecule' which, when in complex with one or more polypeptides, forms a functional protein. The PRX entities refer to the functional proteins as well as to separate protein domains and subunits. The complex proteins in COMe are subdivided into three categories: (i) metalloproteins, (ii) organic prosthetic group proteins and (iii) modified amino acid proteins. The data are currently stored in both XML format and a relational database and are available at http://www.ebi.ac.uk/come/.

Conclusion: COMe provides the classification of proteins according to their 'bioinorganic' features and thus is orthogonal to other classification schemes, such as those based on sequence similarity, 3-D fold, enzyme activity, or biological process. The hierarchical organisation of the controlled vocabulary allows both for annotation and querying at different levels of granularity.

Homology modeling is a powerful technique that greatly increases the value of experimental structure determination by using the structural information of one protein to predict the structures of homologous proteins. We have previously described a method of homology modeling by satisfaction of spatial restraints (Li et al., Protein Sci 1997;6:956–970). The Homology Modeling Automatically (HOMA) web site, <http://www-nmr.cabm.rutgers.edu/HOMA>, is a new tool, using this method to predict 3D structure of a target protein based on the sequence alignment of the target protein to a template protein and the structure coordinates of the template. The user is presented with the resulting models, together with an extensive structure validation report providing critical assessments of the quality of the resulting homology models. The homology modeling method employed by HOMA was assessed and validated using twenty-four groups of homologous proteins. Using HOMA, homology models were generated for 510 proteins, including 264 proteins modeled with correct folds and 246 modeled with incorrect folds. Accuracies of these models were assessed by superimposition on the corresponding experimentally determined structures. A subset of these results was compared with parallel studies of modeling accuracy using several other automated homology modeling approaches. Overall, HOMA provides prediction accuracies similar to other state-of-the-art homology modeling methods. We also provide an evaluation of several structure quality validation tools in assessing the accuracy of homology models generated with HOMA. This study demonstrates that Verify3D (Luthy et al., Nature 1992;356:83–85) and ProsaII (Sippl, Proteins 1993;17:355–362) are most sensitive in distinguishing between homology models with correct or incorrect folds. For homology models that have the correct fold, the steric conformational energy (including primarily the Van der Waals energy), MolProbity clashscore (Word et al., Protein Sci 2000;9:2251–2259), and the PROCHECK G-factors (Laskowski et al., J Biomol NMR 1996;8:477–486) provide sensitive and consistent methods for assessing accuracy and can distinguish between homology models of higher and lower accuracy. As demonstrated in the accompanying paper (Bhattacharya et al., accompanying paper), combinations of these scores for models generated with HOMA provide a basis for distinguishing low from high accuracy models. Proteins 2008. © 2007 Wiley-Liss, Inc.

In this capstone, I describe various state-of-the-art tools in detail to “annotate” conserved hypothetical genes in whole genome sequences. Genetic annotation refers to the designation of function to biological sequences. This approach can be either experimental or bioinformatics based, the latter starting with identification, followed by structural and functional analyses using the RAST server, GLIMMER, and the SEED and KEGG databases. Eventually, gene expression studies should be carried out to experimentally test for gene function in a biochemical pathway and examples of this will be described. Bacterial operonic structure lends clues to gene function based on the surrounding genes if they are known, shows a putative biochemical function for a target gene of interest, and identifies regulator or operator sequences. First, identification by the GLIMMER system uses a computational gene finder to find genes using algorithms and models that rely on probability. Structural genomics approaches, such as protein production and crystallization, can then be carried out to give clues into biological function. The RAST server similarly creates metabolic networks and determines the role of a gene in a subsystem. Functional genomics then generates functional linkage maps and 3D structures and links proteins that have a similar function called Rosetta-Stone proteins. Lastly, gene expression, explained by a seven-category model, helps to assign function in addition to either a microarray or a gene knockout experiment where function is assessed before and after mutagenesis or gene fusions. Using all of these tools collectively aids in deducing function in hypothetical genes. This capstone report will document a number of case studies where functional identity has been determined by the above approaches.

The alphaviruses were amongst the first arboviruses to be isolated, characterized and assigned a taxonomic status. They are globally very widespread, infecting a large variety of terrestrial animals, insects and even fish, and circulate both in the sylvatic and urban/peri-urban environment, causing considerable human morbidity and mortality. Nevertheless, despite their obvious importance as pathogens, there are currently no effective antiviral drugs with which to treat humans or animals infected by any of these viruses. The EU-supported project—VIZIER (Comparative Structural Genomics of Viral Enzymes Involved in Replication, FP6 Project: 2004-511960) was instigated with an ultimate view of contributing to the development of antiviral therapies for RNA viruses, including the alphaviruses [Coutard, B., Gorbalenya, A.E., Snijder, E.J., Leontovich, A.M., Poupon, A., De Lamballerie, X., Charrel, R., Gould, E.A., Gunther, S., Norder, H., Klempa, B., Bourhy, H., Rohayemj, J., L’hermite, E., Nordlund, P., Stuart, D.I., Owens, R.J., Grimes, J.M., Tuckerm, P.A., Bolognesi, M., Mattevi, A., Coll, M., Jones, T.A., Åqvist, J., Unger, T., Hilgenfeld, R., Bricogne, G., Neyts, J., La Colla, P., Puerstinger, G., Gonzalez, J.P., Leroy, E., Cambillau, C., Romette, J.L., Canard, B., 2008. The VIZIER project: preparedness against pathogenic RNA viruses. Antiviral Res. 78, 37–46]. This review highlights some of the major features of alphaviruses that have been investigated during recent years. After describing their classification, epidemiology and evolutionary history and the expanding geographic distribution of Chikungunya virus, we review progress in understanding the structure and function of alphavirus replicative enzymes achieved under the VIZIER programme and the development of new disease control strategies.

The shapes of most protein sequences will be modeled based on their similarity to experimentally determined protein structures. The current role, limitations, challenges and prospects for protein structure modeling (using information about genes and genomes) are discussed in the context of structural genomics.

In order to support the structural genomic initiatives, both by rapidly classifying newly determined structures and by suggesting suitable targets for structure determination, we have recently developed several new protocols for classifying structures in the CATH domain database (http://www. biochem. ucl. ac. uk/bsm/cath). These aim to increase the speed of classification of new structures using fast algorithms for structure comparison (GRATH) and to improve the sensitivity in recognising distant structural relatives by ...

This study focuses on the 5-year Protein 3000 Project launched in 2002, the largest biological
project in Japan. The project aimed to overcome Japan’s alleged failure to contribute fully to
the Human Genome Project, by determining 3000 protein structures, 30 percent of the global
target. Despite its achievement of this goal, the project was fiercely criticized in various sectors of
society and was often branded an awkward failure. This article tries to solve the mystery of why
such failure discourse was prevalent. Three explanatory factors are offered: first, because some
goals were excluded during project development, there was a dynamic of failed expectations;
second, structural genomics, while promoting collaboration with the international community,
became an ‘anti-boundary object’, only the absence of which bound heterogeneous domestic
actors; third, there developed an urgent sense of international competition in order to obtain
patents on such structural information.