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.     

Structural genomics

Structural genomics can be defined as structural biology on a large number of target proteins in parallel. This approach plays an important role in modern structure-based drug design. Although a number of structural genomics initiatives have been initiated, relatively few are associated with integral membrane proteins. This indicates the difficulties in expression, purification, and crystallization of membrane proteins, which has also been confirmed by the existence of some 100 high-resolution structures of membrane proteins among the more than 30,000 entries in public databases. Paradoxically, membrane proteins represent 60–70% of current drug targets and structural knowledge could both improve and speed up the drug discovery process. In order to improve the sucess rate for structure resolution of membrane proteins structural genomics networks have been established.     

Structural RNAs of known and unknown function identified in malaria parasites by comparative genomics and RNA analysis

As the genomes of more eukaryotic pathogens are sequenced, understanding how molecular differences between parasite and host might be exploited to provide new therapies has become a major focus. Central to cell function are RNA-containing complexes involved in gene expression, such as the ribosome, the spliceosome, snoRNAs, RNase P, and telomerase, among others. In this article we identify by comparative genomics and validate by RNA analysis numerous previously unknown structural RNAs encoded by the Plasmodium falciparum genome, including the telomerase RNA, U3, 31 snoRNAs, as well as previously predicted spliceosomal snRNAs, SRP RNA, MRP RNA, and RNAse P RNA. Furthermore, we identify six new RNA coding genes of unknown function. To investigate the relationships of the RNA coding genes to other genomic features in related parasites, we developed a genome browser for P. falciparum (http://areslab.ucsc.edu/cgi-bin/hgGateway). Additional experiments provide evidence supporting the prediction that snoRNAs guide methylation of a specific position on U4 snRNA, as well as predicting an snRNA promoter element particular to Plasmodium sp. These findings should allow detailed structural comparisons between the RNA components of the gene expression machinery of the parasite and its vertebrate hosts.     

Structural genomics for Caenorhabditis elegans: high throughput protein expression analysis

The structural genomics initiatives have begun with the aim to create a so-called "basic set library" of protein folds that will be used to improve protein prediction methods. Such a library is thought to require the determination of up to 10,000 new structures, including representative structures of several sequence variants from each protein fold. To meet this goal in a reasonable time frame and cost, automated systems must be utilized to clone and to identify the soluble recombinant proteins contained in multiple genomes. This paper presents such a system, developed using the genome of Caenorhabditis elegans (19,099 genes) as a model eukaryotic organism for structural genomics. This system successfully automates nearly all aspects of recombinant protein expression analysis including subcloning, bacterial growth, recombinant protein expression, protein purification, and scoring protein solubility.     

The importance of phase information for human genomics

Contemporary sequencing studies often ignore the diploid nature of the human genome because they do not routinely separate or 'phase' maternally and paternally derived sequence information. However, many findings - both from recent studies and in the more established medical genetics literature - indicate that relationships between human DNA sequence and phenotype, including disease, can be more fully understood with phase information. Thus, the existing technological impediments to obtaining phase information must be overcome if human genomics is to reach its full potential.     

Structural genomics and drug discovery

Structure determination has already proven useful for lead optimization and direct drug design. The number of high-resolution structures available in public databases today exceeds 30,000 and will definitely aid in structure-based drug design. Structural genomics approaches covering whole genomes, topologically similar proteins or gene families are great assets for further progress in the development of new drugs. However, membrane proteins representing 70% of current drug targets are poorly characterized structurally. The problems have been related to difficulties in obtaining large amount of recombinant membrane proteins as well as their purification and structure determination. Structural genomics has proven successful in developing new methods in areas from expression to structure determination by studying a large number of target proteins in parallel.     

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.     

Medaka genomics: a bridge between mutant phenotype and gene function

Recent advances in medaka genetics have proven that the medakafish is an excellent model system for developmental and evolutionary biology studies and that it can complement similar studies in zebrafish. Large-scale mutagenesis projects are now being conducted by several groups in Japan and are delivering a vastly expanded pool of medaka mutant stocks. This growing availability of genomic resources will greatly accelerate progress in moving from mutant phenotypes to the elucidation of gene function. This phenotype-driven approach can be expected to lead to the identification and characterization of novel genes and pathways in vertebrate genomes. This review discusses the current state of medaka genomic resources, the state of medaka gene mapping and medaka genome sequencing projects.     

Virus-induced gene silencing and its application in plant functional genomics

Virus-induced gene silencing is regarded as a powerful and efficient tool for the analysis of gene function in plants because it is simple, rapid and transformation-free. It has been used to perform both forward and reverse genetics to identify plant functional genes. Many viruses have been developed into virus-induced gene silencing vectors and gene functions involved in development, biotic and abiotic stresses, metabolism, and cellular signaling have been reported. In this review, we discuss the development and application of virus-induced gene silencing in plant functional genomics.     

Structural genomics of GPCRs

G protein-coupled receptors (GPCRs) are targets for 60-70% of drugs in development today. Traditionally, the drug discovery process has relied on screening of chemical compounds to identify novel and more-efficient drug molecules. Structure-based drug design, however, provides a targeted approach but has been severely hampered by limited knowledge of high-resolution structures of GPCRs owing to the difficulties encountered in their expression, purification and crystallization. In addition to individual laboratories studying specific GPCRs, structural genomics initiatives have been established as large networks with a wide range of expertise in protein expression, purification and crystallography. Several of these national and international consortia have included GPCRs in their programs. Milligram quantities of GPCRs can now be expressed in several expression systems and purified to high homogeneity. However, success in crystallization still requires major technological improvement.     

Structural genomics and signaling domains.

Many novel signal transduction domains are being identified in the wake of genome sequencing projects and improved sensitivity in homology-detection techniques. The functions of these domains are being discovered by hypothesis-driven experiments and structural genomics approaches. This article reviews the recent highlights of research on modular signaling domains, and the relative contributions and limitations of the various approaches being used.     

Ecological genomics: understanding gene and genome function in the natural environment

The field of ecological genomics seeks to understand the genetic mechanisms underlying responses of organisms to their natural environments. This is being achieved through the application of functional genomic approaches to identify and characterize genes with ecological and evolutionary relevance. By its very nature, ecological genomics is an interdisciplinary field. In this review, we consider the significance of this new area of study from both an ecological and genomic perspective using examples from the recent literature. We submit that by considering more fully an ecological context, researchers may gain additional insights into the underlying genetic basis of ecologically relevant phenotypic variation. Likewise, genomic approaches are beginning to offer new insights into higher-level biological phenomena that previously occupied the realm of ecological investigation only. We discuss various approaches that are likely to be useful in ecological genomic studies and offer thoughts on where this field is headed in the future.