Seeing is believing: the impact of structural genomics on antimicrobial drug discovery

Over the past decade, the availability of complete microbial genome sequences has led to changes in the strategies that are used to search for novel anti-infectives. However, despite the identification of many new potential drug targets, novel antimicrobial agents have been slow to emerge from these efforts. In part, this reflects the long discovery and development times that are needed to bring new drugs to market and the bottlenecks at the stages of identifying good lead compounds and optimizing these leads into drug candidates. Structural genomics will hopefully provide opportunities to overcome these bottlenecks and populate the antimicrobial pipeline.     

The impact of extremophiles on structural genomics (and vice versa)

The advent of the complete genome sequences of various organisms in the mid-1990s raised the issue of how one could determine the function of hypothetical proteins. While insight might be obtained from a 3D structure, the chances of being able to predict such a structure is limited for the deduced amino acid sequence of any uncharacterized gene. A template for modeling is required, but there was only a low probability of finding a protein closely-related in sequence with an available structure. Thus, in the late 1990s, an international effort known as structural genomics (SG) was initiated, its primary goal to “fill sequence-structure space” by determining the 3D structures of representatives of all known protein families. This was to be achieved mainly by X-ray crystallography and it was estimated that at least 5,000 new structures would be required. While the proteins (genes) for SG have subsequently been derived from hundreds of different organisms, extremophiles and particularly thermophiles have been specifically targeted due to the increased stability and ease of handling of their proteins, relative to those from mesophiles. This review summarizes the significant impact that extremophiles and proteins derived from them have had on SG projects worldwide. To what extent SG has influenced the field of extremophile research is also discussed.     

The evolution of structural genomics

Structural genomics began as a global effort in the 1990s to determine the tertiary structures of all protein families as a response to large-scale genome sequencing projects. The immediate outcome was an influx of tens of thousands of protein structures, many of which had unknown functions. At the time, the value of structural genomics was controversial. However, the structures themselves were only the most obvious output. In addition, these newly solved structures motivated the emergence of huge data science and infrastructure efforts, which, together with advances in Deep Learning, have brought about a revolution in computational molecular biology. Here, we review some of the computational research carried out at the Protein Data Bank Japan (PDBj) during the Protein 3000 project under the leadership of Haruki Nakamura, much of which continues to flourish today.     

The success of structural genomics

The International Conference on Structural Genomics (ICSG 2011, ), held in Toronto Canada May 10–14, 2011 was a rich and exciting demonstration of how far structural genomics has come. Structural genomics has now matured into a field that includes both structure and the biology that structure enables. This has allowed targeting based on systematic approaches and on known biological importance and allows biochemical studies to be closely tied to structure determination. The wealth of purified proteins, clones, and chemical probes produced by structural genomics groups will enable a vast amount of follow-on research. The technologies, the structures, and the biology that were described at the meeting were at the cutting edge of science. Structural genomics has become a success.     

The impact of bacteriophage genomics

The discovery of (bacterio)phages revolutionised microbiology and genetics, while phage research has been integral to answering some of the most fundamental biological questions of the twentieth century. The susceptibility of bacteria to bacteriophage attack can be undesirable in some cases, especially in the dairy industry, but can be desirable in others, for example, the use of bacteriophage therapy to eliminate pathogenic bacteria. The relative ease with which entire bacteriophage genome sequences can now be elucidated has had a profound impact on the study of these bacterial parasites.     

Challenges of structural genomics: bioinformatics

Structural genomics projects bring us many challenges, many of which were not anticipated when such initiatives were first planned and introduced. For instance, the huge amount of data generated within the project must be collected, displayed and analyzed to reap the benefits of this huge investment. Projects at the San Diego based Joint Center for Structural Genomics provide an example of how data can be managed within a structural genomics project, and how results can be presented on the web, as well as highlight some of the issues concerning data analysis.     

结构基因组学中的衍射相位问题

简要介绍了结构基因组学研究中,用于测定蛋白质结构的X射线分析在解决衍射相位问题方面的最新进展。     

Glycoprotein structural genomics: solving the glycosylation problem

Glycoproteins present special problems for structural genomic analysis because they often require glycosylation in order to fold correctly, whereas their chemical and conformational heterogeneity generally inhibits crystallization. We show that the "glycosylation problem" can be solved by expressing glycoproteins transiently in mammalian cells in the presence of the N-glycosylation processing inhibitors, kifunensine or swainsonine. This allows the correct folding of the glycoproteins, but leaves them sensitive to enzymes, such as endoglycosidase H, that reduce the N-glycans to single residues, enhancing crystallization. Since the scalability of transient mammalian expression is now comparable to that of bacterial systems, this approach should relieve one of the major bottlenecks in structural genomic analysis.     

The impact of next-generation sequencing on genomics

This article reviews basic concepts,general applications,and the potential impact of next-generation sequencing(NGS)technologies on genomics,with particular reference to currently available and possible future platforms and bioinformatics.NGS technologies have demonstrated the capacity to sequence DNA at unprecedented speed,thereby enabling previously unimaginable scientific achievements and novel biological applications.But,the massive data produced by NGS also presents a significant challenge for data storage,analyses,and management solutions.Advanced bioinformatic tools are essential for the successful application of NGS technology.As evidenced throughout this review,NGS technologies will have a striking impact on genomic research and the entire biological field.With its ability to tackle the unsolved challenges unconquered by previous genomic technologies,NGS is likely to unravel the complexity of the human genome in terms of genetic variations,some of which may be confined to susceptible loci for some common human conditions.The impact of NGS technologies on genomics will be far reaching and likely change the field for years to come.     

The impact of genomics on mammalian neurobiology

The benefit of genomics lies in the speeding up of research efforts in other fields of biology, including neurobiology. Through accelerated progress in positional cloning and genetic mapping, genomics has forced us to confront at a much faster pace the difficult problem of defining gene function. Elucidation of the function of identified disease genes and other genes expressed in the Central nervous system has to await conceptual developments in other fields.     

The PRESAGE database for structural genomics.

The PRESAGE database is a collaborative resource for structural genomics. It provides a database of proteins to which researchers add annotations indicating current experimental status, structural predictions and suggestions. The database is intended to enhance communication among structural genomics researchers and aid dissemination of their results. The PRESAGE database may be accessed at http://presage.stanford.edu/     

The Protein Data Bank and structural genomics

The Protein Data Bank (PDB; http://www.pdb.org/) continues to be actively involved in various aspects of the informatics of structural genomics projects--developing and maintaining the Target Registration Database (TargetDB), organizing data dictionaries that will define the specification for the exchange and deposition of data with the structural genomics centers and creating software tools to capture data from standard structure determination applications.     

Laboratory scale structural genomics

At Lawrence Livermore National Laboratory, the development of the TB structural genomics consortium crystallization facility has paralleled several local proteomics research efforts that have grown out of gene expression microarray and comparative genomics studies. Collective experience gathered from TB consortium labs and other centers involved in the NIH-NIGMS protein structure initiative allows us to explore the possibilities and challenges of pursuing structural genomics on an academic laboratory scale. We discuss our procedures and protocols for genomic targeting approaches, primer design, cloning, small scale expression screening, scale-up and purification, through to automated crystallization screening and data collection. The procedures are carried out by a small group using a combination of traditional approaches, innovative molecular biochemistry approaches, software automation, and a modest investment in robotic equipment.     

Focusing in on structural genomics: the University of Queensland structural biology pipeline

The flood of new genomic sequence information together with technological innovations in protein structure determination have led to worldwide structural genomics (SG) initiatives. The goals of SG initiatives are to accelerate the process of protein structure determination, to fill in protein fold space and to provide information about the function of uncharacterized proteins. In the long-term, these outcomes are likely to impact on medical biotechnology and drug discovery, leading to a better understanding of disease as well as the development of new therapeutics. Here we describe the high throughput pipeline established at the University of Queensland in Australia. In this focused pipeline, the targets for structure determination are proteins that are expressed in mouse macrophage cells and that are inferred to have a role in innate immunity. The aim is to characterize the molecular structure and the biochemical and cellular function of these targets by using a parallel processing pipeline. The pipeline is designed to work with tens to hundreds of target gene products and comprises target selection, cloning, expression, purification, crystallization and structure determination. The structures from this pipeline will provide insights into the function of previously uncharacterized macrophage proteins and could lead to the validation of new drug targets for chronic obstructive pulmonary disease and arthritis.     

Expectations from structural genomics

Structural genomics projects aim to provide an experimental structure or a good model for every protein in all completed genomes. Most of the experimental work for these projects will be directed toward proteins whose fold cannot be readily recognized by simple sequence comparison with proteins of known structure. Based on the history of proteins classified in the SCOP structure database, we expect that only about a quarter of the early structural genomics targets will have a new fold. Among the remaining ones, about half are likely to be evolutionarily related to proteins of known structure, even though the homology could not be readily detected by sequence analysis.     

Completeness in structural genomics

Structural genomics has the goal of obtaining useful, three-dimensional models of all proteins by a combination of experimental structure determination and comparative model building. We evaluate different strategies for optimizing information return on effort. The strategy that maximizes structural coverage requires about seven times fewer structure determinations compared with the strategy in which targets are selected at random. With a choice of reasonable model quality and the goal of 90% coverage, we extrapolate the estimate of the total effort of structural genomics. It would take approximately 16,000 carefully selected structure determinations to construct useful atomic models for the vast majority of all proteins. In practice, unless there is global coordination of target selection, the total effort will likely increase by a factor of three. The task can be accomplished within a decade provided that selection of targets is highly coordinated and significant funding is available.