Chaperone discovery

Molecular chaperones assist de novo protein folding and facilitate the refolding of stress‐denatured proteins. The molecular chaperone concept was coined nearly 35 years ago, and since then, tremendous strides have been made in understanding how these factors support protein folding. Here, we focus on how various chaperone proteins were first identified to play roles in protein folding. Examples are used to illustrate traditional routes of chaperone discovery and point out their advantages and limitations. Recent advances, including the development of folding biosensors and promising methods for the stabilization of proteins in vivo, provide new routes for chaperone discovery.     

Aromatase inhibitors--gene discovery

Microarray analysis of tumour RNA is an extremely powerful tool which allows global gene expression to be measured. When used in combination with neoadjuvant treatment protocols in which therapy is given with the primary tumour within the breast, sequential biopsies may be analysed and results correlated with clinical and pathological response. In the present study, a neoadjuvant protocol has been used, administering the third generation inhibitor, letrozole, for 3 months and subjecting RNA extracted from biopsies taken before and after 10–14 days of treatment to microarray analysis. The objectives were to discover: (i) genes that change with estrogen deprivation (the only known biological effect of letrozole is to inhibit aromatase activity and reduce endogenous estrogens in postmenopausal women) and (ii) genes whose basal, on treatment or change in expression differ between tumours which are either responsive or resistant to treatment (so that predictive indices of response/resistance may be developed).

Early changes in gene expression were identified by comparing paired tumour core biopsies taken before and after 14 days treatment in 58 patients using three different approaches based on frequency of changes, magnitude of changes and SAM analysis. All three approaches showed a greater number of genes were down-regulated than up-regulated. Merging of the data produced a total of 143 genes which were subject to gene ontology and cluster analysis. The ontology of the 91 down-regulated genes showed that they were functionally associated with cell cycle progression, particularly mitosis. In contrast, up-regulated genes were associated with organ development and extra-cellular matrix turnover and regulation.

Clinical response was assessable in 52 patients; 37 (71%) tumours were classified as clinical responders (>50% reduction in volume at 3 months). Microarray analysis of pre- and 14-day biopsies identified 291 covariates (84 baselines, 72 14-day and 135 changes) highly predictive of response status. A similarity matrix using the covariates showed responding tumours have a similar genetic profile which was dissimilar to non-responding cancers whereas non-responsive cases were distinctive from each other. Changed genes predicting for response showed no concordance with those changed significantly by treatment in the overall group.     

Dual-purpose drug discovery

A hot area in drug discovery focuses on developing small-molecule inhibitors of the epidermal growth factor receptor (EGFR) signaling pathway.     

Tools of discovery

Molecular Systems Biology has transitioned to the new EMBO Press publishing platform to offer a richer and more transparent access to high‐quality research.     

High-throughput discovery metabolomics

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Digital drug discovery

A report of the Cambridge Healthtech Institute conference 'Beyond Genome', San Franciso, USA, 13-16 June 2005.     

Bifurcation discovery tool

MOTIVATION: Biochemical networks often yield interesting behavior such as switching, oscillation and chaotic dynamics. This article describes a tool that is capable of searching for bifurcation points in arbitrary ODE-based reaction networks by directing the user to regions in the parameter space, where such interesting dynamical behavior can be observed. RESULTS: We have implemented a genetic algorithm that searches for Hopf bifurcations, turning points and bistable switches. The software is implemented as a Systems Biology Workbench (SBW) enabled module and accepts the standard SBML model format. The interface permits a user to choose the parameters to be searched, admissible parameter ranges, and the nature of the bifurcation to be sought. The tool will return the parameter values for the model for which the particular behavior is observed. AVAILABILITY: The software, tutorial manual and test models are available for download at the following website: http:/www.sys-bio.org/ under the bifurcation link. The software is an open source and licensed under BSD.     

Viral pathogen discovery

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Single-round deoxyribozyme discovery

Artificial evolution experiments typically use libraries of ∼10¹⁵ sequences and require multiple rounds of selection to identify rare variants with a desired activity. Based on the simple structures of some aptamers and nucleic acid enzymes, we hypothesized that functional motifs could be isolated from significantly smaller libraries in a single round of selection followed by high-throughput sequencing. To test this idea, we investigated the catalytic potential of DNA architectures in which twelve or fifteen randomized positions were embedded in a scaffold present in all library members. After incubating in either the presence or absence of lead (which promotes the nonenzymatic cleavage of RNA), library members that cleaved themselves at an RNA linkage were purified by PAGE and characterized by high-throughput sequencing. These selections yielded deoxyribozymes with activities 8- to 30-fold lower than those previously isolated under similar conditions from libraries containing 10¹⁴ different sequences, indicating that the disadvantage of using a less diverse pool can be surprisingly small. It was also possible to elucidate the sequence requirements and secondary structures of deoxyribozymes without performing additional experiments. Due to its relative simplicity, we anticipate that this approach will accelerate the discovery of new catalytic DNA and RNA motifs.