The interplay between chromosome stability and cell cycle control explored through gene-gene interaction and computational simulation.

Chromosome stability models are usually qualitative models derived from molecular-genetic mechanisms for DNA repair, DNA synthesis, and cell division. While qualitative models are informative, they are also challenging to reformulate as precise quantitative models. In this report we explore how (A) laboratory experiments, (B) quantitative simulation, and (C) seriation algorithms can inform models of chromosome stability. Laboratory experiments were used to identify 19 genes that when over-expressed cause chromosome instability in the yeast Saccharomyces cerevisiae To better understand the molecular mechanisms by which these genes act, we explored their genetic interactions with 18 deletion mutations known to cause chromosome instability. Quantitative simulations based on a mathematical model of the cell cycle were used to predict the consequences of several genetic interactions. These simulations lead us to suspect that the chromosome instability genes cause cell-cycle perturbations. Cell-cycle involvement was confirmed using a seriation algorithm, which was used to analyze the genetic interaction matrix to reveal an underlying cyclical pattern. The seriation algorithm searched over 10(14) possible arrangements of rows and columns to find one optimal arrangement, which correctly reflects events during cell cycle phases. To conclude, we illustrate how the molecular mechanisms behind these cell cycle events are consistent with established molecular interaction maps.

Mode of action, in vitro activity, and in vivo efficacy of AFN-1252, a selective antistaphylococcal FabI inhibitor.

The mechanism of action of AFN-1252, a selective inhibitor of Staphylococcus aureus enoyl-acyl carrier protein reductase (FabI), which is involved in fatty acid biosynthesis, was confirmed by using biochemistry, macromolecular synthesis, genetics, and cocrystallization of an AFN-1252-FabI complex. AFN-1252 demonstrated a low propensity for spontaneous resistance development and a time-dependent reduction of the viability of both methicillin-susceptible and methicillin-resistant S. aureus, achieving a ≥2-log(10) reduction in S. aureus counts over 24 h, and was extremely potent against clinical isolates of S. aureus (MIC(90), 0.015 µg/ml) and coagulase-negative staphylococci (MIC(90), 0.12 µg/ml), regardless of their drug resistance, hospital- or community-associated origin, or other clinical subgroup. AFN-1252 was orally available in mouse pharmacokinetic studies, and a single oral dose of 1 mg/kg AFN-1252 was efficacious in a mouse model of septicemia, providing 100% protection from an otherwise lethal peritoneal infection of S. aureus Smith. A median effective dose of 0.15 mg/kg indicated that AFN-1252 was 12 to 24 times more potent than linezolid in the model. These studies, demonstrating a selective mode of action, potent in vitro activity, and in vivo efficacy, support the continued investigation of AFN-1252 as a targeted therapeutic for staphylococcal infections.

Crystallizing new approaches for antimicrobial drug discovery.

Over the past decade, the sequences of microbial genomes have accumulated, changing the strategies for the discovery of novel anti-infective agents. Targets have become plentiful, yet new antimicrobial agents have been slow to emerge from this effort. In part, this reflects the long discovery and development times needed to bring new drugs to market. In addition, bottlenecks have been revealed in the antimicrobial drug discovery process at the steps of identifying good leads, and optimizing those leads into drug candidates. The fruit of structural genomics may provide opportunities to overcome these bottlenecks and fill the antimicrobial pipeline, by using the tools of structure guided drug discovery (SGDD).

Large-scale identification of genes required for full virulence of Staphylococcus aureus.

Gene products required for in vivo growth and survival of microbial pathogens comprise a unique functional class and may represent new targets for antimicrobial chemotherapy, vaccine construction, or diagnostics. Although some factors governing Staphylococcus aureus pathogenicity have been identified and studied, a comprehensive genomic analysis of virulence functions will be a prerequisite for developing a global understanding of interactions between this pathogen and its human host. In this study, we describe a genetic screening strategy and demonstrate its use in screening a collection of 6,300 S. aureus insertion mutants for virulence attenuation in a murine model of systemic infection. Ninety-five attenuated mutants were identified, reassembled into new pools, and rescreened using the same murine model. This effort identified 24 highly attenuated mutants, each of which was further characterized for virulence attenuation in vivo and for growth phenotypes in vitro. Mutants were recovered in numbers up to 1,200-fold less than wild type in the spleens of systemically infected animals and up to 4,000-fold less than wild type in localized abscess infections. Genetic analysis of the mutants identified insertions in 23 unique genes. The largest gene classes represented by these mutants encoded enzymes involved in small-molecule biosynthesis and cell surface transmembrane proteins involved in small-molecule binding and transport. Additionally, three insertions defined two histidine kinase sensor-response regulator gene pairs important for S. aureus in vivo survival. Our findings extend the understanding of pathogenic mechanisms employed by S. aureus to ensure its successful growth and survival in vivo. Many of the gene products we have identified represent attractive new targets for antibacterial chemotherapy.

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.

Reduced triclosan susceptibility in methicillin-resistant Staphylococcus epidermidis.

Triclosan MIC determination showed that recent Staphylococcus aureus clinical isolates (n = 100) were highly susceptible to triclosan, with a 50% minimal inhibitory concentration (MIC(50)) of 0.12 microg/ml and a MIC(90) of 0.25 microg/ml. Staphylococcus epidermidis isolates (n = 96) were less susceptible, with a MIC(50) of 0.12 microg/ml and a MIC(90) of 8 microg/ml. Decreased susceptibility to triclosan was more prevalent among methicillin-resistant S. epidermidis than among methicillin-sensitive S. epidermidis isolates.

Structural proteomics: the potential of high-throughput structure determination.

The pharmaceutical industry has embraced genomics as a means to identify new biological targets for target-based drug discovery approaches. Now, genomics is driving a substantial effort in protein structure determination and structure prediction. These structures will provide the opportunity to undertake structure-guided drug discovery programs in the search for new classes of broad-spectrum antibiotics. In addition, these structures could provide structure-based criteria to prioritize certain targets for focused drug discovery programs.

Microbial genomics - new targets, new drugs.

Genomics has changed our view of the biological world in the past decade, providing both new information and new tools to characterise biological systems. Over 100 microbial genomes - including many of substantial clinical importance - have been fully or partially sequenced, pushing the search for novel antimicrobial compounds into the post-genomic era. Genomic information and associated new technologies have the potential to revolutionise the drug discovery process. Genomic methods have created a wealth of potential new antimicrobial targets; strategies are evolving to provide validation for these targets before chemical inhibitors are identified. The ability to obtain large amounts of purified target proteins and advances in X-ray crystallography have caused significant increases in available protein structures, which may foreshadow an increased effort in structure-based drug design. The post-genomics strategies used in antimicrobial drug discovery may have application for small molecule drug discovery in numerous therapeutic areas.