Fulfilling the promise: drug discovery in the post-genomic era

Cell-Based Double-Screening Method to Identify a Reliable Candidate for Osteogenesis-Targeting Compounds

Small-molecule compounds strongly affecting osteogenesis can form the basis of effective therapeutic strategies in bone regenerative medicine. A cell-based high-throughput screening system might be a powerful tool for identifying osteoblast-targeting candidates; however, this approach is generally limited with using only one molecule as a cell-based sensor that does not always reflect the activation of the osteogenic phenotype. In the present study, we used the MC3T3-E1 cell line stably transfected with the green fluorescent protein (GFP) reporter gene driven by a fragment of type I collagen promoter (Col-1a1GFP-MC3T3-E1) to evaluate a double-screening system to identify osteogenic inducible compounds using a combination of a cell-based reporter assay and detection of alkaline phosphatase (ALP) activity. Col-1a1GFP-MC3T3-E1 cells were cultured in an osteogenic induction medium after library screening of 1280 pharmacologically active compounds (Lopack¹²⁸⁰). After 7 days, GFP fluorescence was measured using a microplate reader. After 14 days of osteogenic induction, the cells were stained with ALP. Library screening using the Col-1a1/GFP reporter and ALP staining assay detected three candidates with significant osteogenic induction ability. Furthermore, leflunomide, one of the three detected candidates, significantly promoted new bone formation in vivo. Therefore, this double-screening method could identify candidates for osteogenesis-targeting compounds more reliably than conventional methods.

Chemical Probes for Understudied Kinases: Challenges and Opportunities

Over 20 years after the approval of the first-in-class protein kinase inhibitor imatinib, the biological function of a significant fraction of the human kinome remains poorly understood while most research continues to be focused on few well-validated targets. Given the strong genetic evidence for involvement of many kinases in health and disease, the understudied fraction of the kinome holds a large and unexplored potential for future therapies. Specific chemical probes are indispensable tools to interrogate biology enabling proper preclinical validation of novel kinase targets. In this Perspective, we highlight recent case studies illustrating the development of high-quality chemical probes for less-studied kinases and their application in target validation. We spotlight emerging techniques and approaches employed in the generation of chemical probes for protein kinases and beyond and discuss the associated challenges and opportunities.

iCAVE: an open source tool for visualizing biomolecular networks in 3D, stereoscopic 3D and immersive 3D

Visualizations of biomolecular networks assist in systems-level data exploration in many cellular processes. Data generated from high-throughput experiments increasingly inform these networks, yet current tools do not adequately scale with concomitant increase in their size and complexity. We present an open source software platform, interactome-CAVE (iCAVE), for visualizing large and complex biomolecular interaction networks in 3D. Users can explore networks (i) in 3D using a desktop, (ii) in stereoscopic 3D using 3D-vision glasses and a desktop, or (iii) in immersive 3D within a CAVE environment. iCAVE introduces 3D extensions of known 2D network layout, clustering, and edge-bundling algorithms, as well as new 3D network layout algorithms. Furthermore, users can simultaneously query several built-in databases within iCAVE for network generation or visualize their own networks (e.g., disease, drug, protein, metabolite). iCAVE has modular structure that allows rapid development by addition of algorithms, datasets, or features without affecting other parts of the code. Overall, iCAVE is the first freely available open source tool that enables 3D (optionally stereoscopic or immersive) visualizations of complex, dense, or multi-layered biomolecular networks. While primarily designed for researchers utilizing biomolecular networks, iCAVE can assist researchers in any field.

The Use of Omic Technologies Applied to Traditional Chinese Medicine Research

Natural products represent one of the most important reservoirs of structural and chemical diversity for the generation of leads in the drug development process. A growing number of researchers have shown interest in the development of drugs based on Chinese herbs. In this review, the use and potential of omic technologies as powerful tools in the modernization of traditional Chinese medicine are discussed. The analytical combination from each omic approach is crucial for understanding the working mechanisms of cells, tissues, organs, and organisms as well as the mechanisms of disease. Gradually, omic approaches have been introduced in every stage of the drug development process to generate high-quality Chinese medicine-based drugs. Finally, the future picture of the use of omic technologies is a promising tool and arena for further improvement in the modernization of traditional Chinese medicine.

Activity of novel inhibitors of Staphylococcus aureus biofilms

Staphylococcus aureus is one of the most important pathogens causing chronic biofilm infections. These are becoming more difficult to treat owing to drug resistance, particularly because S. aureus biofilms limit the efficacy of antimicrobial agents, leading to high morbidity and mortality. In the present study, we screened for inhibitors of S. aureus biofilm formation using a natural product library from the Korea Chemical Bank (KCB). Screening by crystal violet-based biomass staining assay identified hit compounds. Further examination of antibiofilm properties of these compounds was conducted and led to the identification of celastrol and telithromycin. In vitro, both celastrol and telithromycin were toxic to planktonic S. aureus and also active against a clinical methicillin-resistant S. aureus (MRSA) isolate. The effect of the compounds on preformed biofilms of clinical MRSA isolates was evaluated by confocal laser scanning microscopy (CLSM), which revealed the absence of typical biofilm architecture. In addition, celastrol and telithromycin inhibited the production of extracellular protein at selected sub-MIC concentrations, which revealed the reduced extracellular polymeric substance (EPS) secretion. Celastrol exhibited greater cytotoxicity than telithromycin. These data suggest that the hit compounds, especially telithromycin, could be considered novel inhibitors of S. aureus biofilm. Although the mechanisms of the effects on S. aureus biofilms are not fully understood, our data suggest that telithromycin could be a useful adjuvant therapeutic agent for S. aureus biofilm-related infections.

DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing

Background

The targeting of disease-related proteins is important for drug discovery, and yet target-based discovery has not been fruitful. Contextualizing overall biological processes is critical to formulating successful drug-disease hypotheses. Network pharmacology helps to overcome target-based bottlenecks through systems biology analytics, such as protein-protein interaction (PPI) networks and pathway regulation.

Results

We present a systems polypharmacology platform entitled DrugGenEx-Net (DGE-NET). DGE-NET predicts empirical drug-target (DT) interactions, integrates interaction pairs into a multi-tiered network analysis, and ultimately predicts disease-specific drug polypharmacology through systems-based gene expression analysis. Incorporation of established biological network annotations for protein target-disease, −signaling pathway, −molecular function, and protein-protein interactions enhances predicted DT effects on disease pathophysiology. Over 50 drug-disease and 100 drug-pathway predictions are validated. For example, the predicted systems pharmacology of the cholesterol-lowering agent ezetimibe corroborates its potential carcinogenicity.

When disease-specific gene expression analysis is integrated, DGE-NET prioritizes known therapeutics/experimental drugs as well as their contra-indications. Proof-of-concept is established for immune-related rheumatoid arthritis and inflammatory bowel disease, as well as neuro-degenerative Alzheimer’s and Parkinson’s diseases.

Conclusions

DGE-NET is a novel computational method that predicting drug therapeutic and counter-therapeutic indications by uniquely integrating systems pharmacology with gene expression analysis. DGE-NET correctly predicts various drug-disease indications by linking the biological activity of drugs and diseases at multiple tiers of biological action, and is therefore a useful approach to identifying drug candidates for re-purposing.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1065-y) contains supplementary material, which is available to authorized users.

Systems Pharmacology Links GPCRs with Retinal Degenerative Disorders

In most biological systems, second messengers and their key regulatory and effector proteins form links between multiple cellular signaling pathways. Such signaling nodes can integrate the deleterious effects of genetic aberrations, environmental stressors, or both in complex diseases, leading to cell death by various mechanisms. Here we present a systems (network) pharmacology approach that, together with transcriptomics analyses, was used to identify different G protein-coupled receptors that experimentally protected against cellular stress and death caused by linked signaling mechanisms. We describe the application of this concept to degenerative and diabetic retinopathies in appropriate mouse models as an example. Systems pharmacology also provides an attractive framework for devising strategies to combat complex diseases by using (repurposing) US Food and Drug Administration-approved pharmacological agents.

High-content phenotypic screenings to identify inhibitors of Candida albicans biofilm formation and filamentation

Candida species represent the main cause of opportunistic fungal infections worldwide, and Candida albicans remains the most common etiological agent of candidiasis, now the third to fourth most common nosocomial infection. These infections are typically associated with high morbidity and mortality, mainly due to the limited efficacy of current antifungal drugs. In C. albicans, morphogenetic conversions between yeast and filamentous forms and biofilm formation represent two important biological processes that are intimately associated with the biology of this fungus and also play important roles during the pathogenesis of candidiasis. We have performed cell-based phenotypic screens using three different chemical libraries from the National Cancer Institute's Open Chemical Repository collection and identified several compounds with inhibitory activity against C. albicans biofilm formation and/or filamentation. These phenotype-based approaches represent a prosperous alternative to conventional genetics and genomics techniques to address experimentally challenging and complex biological phenomena, such as biofilm formation and filamentation, while at the same time opening new possibilities for the development of new antifungal agents.

Biochemical properties of human dehydrogenase/reductase (SDR family) member 7

Dehydrogenase/reductase (SDR family) member 7 (DHRS7, retSDR4, SDR34C1) is a previously uncharacterized member of the short-chain dehydrogenase/reductase (SDR) superfamily. While human SDR members are known to play an important role in various (patho)biochemical pathways including intermediary metabolism and biotransformation of xenobiotics, only 20% of them are considered to be well characterized. Based on phylogenetic tree and SDR sequence clusters analysis DHRS7 is a close relative to well-known SDR member 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1) that participates in metabolism of endogenous and xenobiotic substances with carbonyl group. The aim of present study is to determine the basic biochemical properties of DHRS7 and its possible involvement in metabolism of substrates with carbonyl group. For the first time the computational predictions of this membrane protein and membrane topology were experimentally confirmed. DHRS7 has been demonstrated to be an integral protein facing the lumen of the endoplasmic reticulum with lack of posttranscriptional glycosylation modification. Subsequently, NADP(H) cofactor preference and enzymatic reducing activity of DHRS7 was determined towards endogenous substrates with a steroid structure (cortisone, 4-androstene-3,17-dion) and also toward relevant exogenous substances bearing a carbonyl group harmful to human health (1,2-naphtoquinone, 9,10-phenantrenequinone). In addition to 11β-HSD1, DHRS7 is another enzyme from SDR superfamily that have been proved, at least in vitro, to contribute to the metabolism of xenobiotics with carbonyl group.

Systems biology-embedded target validation: improving efficacy in drug discovery

The pharmaceutical industry is faced with a range of challenges with the ever-escalating costs of drug development and a drying out of drug pipelines. By harnessing advances in -omics technologies and moving away from the standard, reductionist model of drug discovery, there is significant potential to reduce costs and improve efficacy. Embedding systems biology approaches in drug discovery, which seek to investigate underlying molecular mechanisms of potential drug targets in a network context, will reduce attrition rates by earlier target validation and the introduction of novel targets into the currently stagnant market. Systems biology approaches also have the potential to assist in the design of multidrug treatments and repositioning of existing drugs, while stratifying patients to give a greater personalization of medical treatment.

Template-induced macrocycle diversity through large ring-forming alkylations of tryptophan

Macrocyclic peptidomimetics are valuable in research and serve as lead compounds in drug discovery efforts. New methods to prepare such structures are of considerable interest. In this pilot study, we show that an organic template harboring a latent cinnamyl cation participates in novel Friedel-Crafts macrocyclization reactions with tryptophan. Upon joining the template to Trp-Trp-Tyr, a single operation efficiently generates eight unique macrocycles. Each has been isolated and thoroughly characterized. Product distribution as a function of Brønsted and/or Lewis acidic conditions was explored, and outcomes were compared to rearrangements induced within a corresponding tyrosine-linked cyclic ether. The solution structure of a new macrocyclic pyrroloindoline was solved using a combination of two-dimensional NMR methods and molecular mechanics simulations. Template-induced structural diversification of peptide sequences harboring aromatic residues has potential to create myriad macrocycles that target surfaces involved in protein-protein interactions.

Applications and limitations of in silico models in drug discovery

Drug discovery in the late twentieth and early twenty-first century has witnessed a myriad of changes that were adopted to predict whether a compound is likely to be successful, or conversely enable identification of molecules with liabilities as early as possible. These changes include integration of in silico strategies for lead design and optimization that perform complementary roles to that of the traditional in vitro and in vivo approaches. The in silico models are facilitated by the availability of large datasets associated with high-throughput screening, bioinformatics algorithms to mine and annotate the data from a target perspective, and chemoinformatics methods to integrate chemistry methods into lead design process. This chapter highlights the applications of some of these methods and their limitations. We hope this serves as an introduction to in silico drug discovery.

Design and synthesis of biologically active peptides: a 'tail' of amino acids can modulate activity of synthetic cyclic peptides

In earlier work, we synthesized a cyclic 9-amino acid peptide (AFPep, cyclo[EKTOVNOGN]) and showed it to be useful for prevention and therapy of breast cancer. In an effort to explore the structure-function relationships of AFPep, we have designed analogs that bear a short 'tail' (one or two amino acids) attached to the cyclic peptide distal to its pharmacophore. Analogs that bore a tail of either one or two amino acids, either of which had a hydrophilic moiety in the side chain (e.g., cyclo[EKTOVNOGN]FS) exhibited greatly diminished biological activity (inhibition of estrogen-stimulated uterine growth) relative to AFPep. Analogs that bore a tail of either one or two amino acids which had hydrophobic (aliphatic or aromatic) side chains (e.g., cyclo[EKTOVNOGN]FI) retained (or had enhanced) growth inhibition activity. Combining in the same biological assay a hydrophilic-tailed analog with either AFPep or a hydrophobic-tailed analog resulted in decreased activity relative to that for AFPep or for the hydrophobic-tailed analog alone, suggesting that hydrophilic-tailed analogs are binding to a biologically active receptor. An analog with a disrupted pharmacophore (cyclo[EKTOVGOGN]) exhibited little or no growth inhibition activity. An analog with a hydrophilic tail and a disrupted pharmacophore (cyclo[EKTOVGOGN]FS) exhibited no growth inhibition activity of its own and did not affect the activity of a hydrophobic-tailed analog, but enhanced the growth inhibition activity of AFPep. These results are discussed in the context of a two-receptor model for binding of AFPep and ring-and-tail analogs. We suggest that tails on cyclic peptides may comprise a useful method to enhance diversity of peptide design and specificity of ligand-receptor interactions.

DrugPred: a structure-based approach to predict protein druggability developed using an extensive nonredundant data set

Judging if a protein is able to bind orally available molecules with high affinity, i.e. if a protein is druggable, is an important step in target assessment. In order to derive a structure-based method to predict protein druggability, a comprehensive, nonredundant data set containing crystal structures of 71 druggable and 44 less druggable proteins was compiled by literature search and data mining. This data set was subsequently used to train a structure-based druggability predictor (DrugPred) using partial least-squares projection to latent structures discriminant analysis (PLS-DA). DrugPred performed well in discriminating druggable from less druggable binding sites for both internal and external predictions. The method is robust against conformational changes in the binding site and outperforms previously published methods. The superior performance of DrugPred is likely due to the size and composition of the training set which, in contrast to most previously developed methods, only contains cavities that have evolved to bind a natural ligand.

INTEGRATING COMPUTATIONAL PROTEIN FUNCTION PREDICTION INTO DRUG DISCOVERY INITIATIVES

Pharmaceutical researchers must evaluate vast numbers of protein sequences and formulate innovative strategies for identifying valid targets and discovering leads against them as a way of accelerating drug discovery. The ever increasing number and diversity of novel protein sequences identified by genomic sequencing projects and the success of worldwide structural genomics initiatives have spurred great interest and impetus in the development of methods for accurate, computationally empowered protein function prediction and active site identification. Previously, in the absence of direct experimental evidence, homology-based protein function annotation remained the gold-standard for in silico analysis and prediction of protein function. However, with the continued exponential expansion of sequence databases, this approach is not always applicable, as fewer query protein sequences demonstrate significant homology to protein gene products of known function. As a result, several non-homology based methods for protein function prediction that are based on sequence features, structure, evolution, biochemical and genetic knowledge have emerged. Herein, we review current bioinformatic programs and approaches for protein function prediction/annotation and discuss their integration into drug discovery initiatives. The development of such methods to annotate protein functional sites and their application to large protein functional families is crucial to successfully utilizing the vast amounts of genomic sequence information available to drug discovery and development processes.

RNAi screening of the kinome identifies modulators of cisplatin response in ovarian cancer cells

OBJECTIVE

Ovarian cancer retains a poor prognosis among the female gynaecological malignancies. It constitutes about 3% of all malignancies in women and accounts for 5% of all female cancer related deaths. A standard treatment is cytoreductive surgery followed by adjuvant chemotherapy, and re-treatment with platinum based chemotherapy at the time of relapse. In order to improve cisplatin response in ovarian cancer cells, we utilized a high-throughput RNAi screening to identify kinase modulators.

METHODS

A high-throughput RNAi screen was performed using a siRNA library targeting 572 kinases to identify potentiators of cisplatin response in the ovarian cancer cell line SKOV3.

RESULTS

RNAi screening identified at least 55 siRNAs that potentiated the growth inhibitory effects of cisplatin in SKOV3 cells. Inhibition of ATR and CHK1 resulted in the greatest modulation of cisplatin response. Drug dose response of cisplatin in the presence of siRNA validated the effects of these target genes. To show that the siRNA data could be successfully translated into potential therapeutic strategies, CHK1 was further targeted with small molecule inhibitor PD 407824 in combination with cisplatin. Results showed that treatment of SKOV3 and OVCAR3 cells with CHK1 inhibitor PD 407824 led to sensitization of ovarian cancer cells to cisplatin.

CONCLUSIONS

Our data provides kinase targets that could be exploited to design better therapeutics for ovarian cancer patients. We also demonstrate the effectiveness of high-throughput RNAi screening as a tool for identifying sensitizing targets to known and established chemotherapeutic agents.

Up-regulation of p21 and TNF-alpha is mediated in lycorine-induced death of HL-60 cells

Background

Leukemia is one of the most life-threatening cancers today, and acute promyelogenous leukemia (APL) is a common type of leukemia. Many natural compounds have already been found to exhibit significant anti-tumor effects. Lycorine, a natural alkaloid extracted from Amaryllidaceae, exhibited anti-leukemia effects in vitro and in vivo. The survival rate of HL-60 cells exposed to lycorine was decreased, cell growth was slowed down, and cell regeneration potential was inhibited. HL-60 cells exhibited typical apoptotic characteristic. Lycorine can suppress leukemia growth and reduce cell survival and inducing apoptosis of tumor cells. The purpose of this work is to elucidate the mechanism by which lycorine induces APL cells.

Results

When HL-60 cells were treated with different concentration of lycorine, the expression of p21 and TNF-α was up-regulated in a concentration-dependent manner as shown by real-time quantitative reverse transcriptase-polymerase chain reaction and Western blotting. Lycorine also down-regulated p21-related gene expression, including Cdc2, Cyclin B, Cdk2 and Cyclin E, promoted Bid truncation, decreased IκB phosphorylation and blocked NF-κB nuclear import. Cytochrome c was released from mitochondria as observed with confocal laser microscopy.

Conclusions

The TNF-α signal transduction pathway and p21-mediated cell-cycle inhibition were involved in the apoptosis of HL-60 cells induced by lycorine. These results contribute to the development of new lycorine-based anti-leukemia drugs.

In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen

The growing resistance to current first-line antimalarial drugs represents a major health challenge. To facilitate the discovery of new antimalarials, we have implemented an efficient and robust high-throughput cell-based screen (1,536-well format) based on proliferation of Plasmodium falciparum (Pf) in erythrocytes. From a screen of approximately 1.7 million compounds, we identified a diverse collection of approximately 6,000 small molecules comprised of >530 distinct scaffolds, all of which show potent antimalarial activity (<1.25 microM). Most known antimalarials were identified in this screen, thus validating our approach. In addition, we identified many novel chemical scaffolds, which likely act through both known and novel pathways. We further show that in some cases the mechanism of action of these antimalarials can be determined by in silico compound activity profiling. This method uses large datasets from unrelated cellular and biochemical screens and the guilt-by-association principle to predict which cellular pathway and/or protein target is being inhibited by select compounds. In addition, the screening method has the potential to provide the malaria community with many new starting points for the development of biological probes and drugs with novel antiparasitic activities.

New insights into chemical biology from ORFeome libraries

As the genomes of many organisms have been sequenced, a variety of global analyses, called 'omics,' have been initiated. Cloning of the set of all open reading frames encoded by the genome (ORFeome) of an organism is a major challenge, which serves as an indispensable provision before one launches into the ocean of the postgenomic world. A suitable strategy for high-throughput cloning and expression of thousands of genes is crucial to success. Recently developed systems employing site-specific or homologous recombination have made it feasible to manipulate thousands of ORFs en masse. Using these technologies, several recent studies have successfully fished biologically active small molecules and target proteins out of this bountiful ocean.

Drug-target network

The global set of relationships between protein targets of all drugs and all disease-gene products in the human protein-protein interaction or 'interactome' network remains uncharacterized. We built a bipartite graph composed of US Food and Drug Administration-approved drugs and proteins linked by drug-target binary associations. The resulting network connects most drugs into a highly interlinked giant component, with strong local clustering of drugs of similar types according to Anatomical Therapeutic Chemical classification. Topological analyses of this network quantitatively showed an overabundance of 'follow-on' drugs, that is, drugs that target already targeted proteins. By including drugs currently under investigation, we identified a trend toward more functionally diverse targets improving polypharmacology. To analyze the relationships between drug targets and disease-gene products, we measured the shortest distance between both sets of proteins in current models of the human interactome network. Significant differences in distance were found between etiological and palliative drugs. A recent trend toward more rational drug design was observed.

Retroviral microarray-based platform on nanostructured TiO2 for functional genomics and drug discovery

Living-cell microarrays are powerful tools for functional genomics and drug discovery. However, despite several attempts to improve this technology, it is still a challenge to obtain microarrays of cells efficiently overexpressing or downregulating specific genes to address complex phenotypes. Here, we present a cell-based microarray for phenotype screening on primary and cancer cells based on the localized reverse infection by retroviruses. Viral vectors are immobilized on a nanostructured titanium dioxide (ns-TiO2) film obtained by depositing a supersonic beam of titania clusters on a glass substrate. We validated the retroviral cell array by overexpression of GFP reporter genes in primary and cancer cells, and by RNA interference of p53 in primary cells by analyzing effects in cell growth. We demonstrate that ns-TiO2 retroviral arrays are an enabling tool for the study of gene function of families of genes for complex phenotypes and for the identification of novel drug targets.

Treatment of lycorine on SCID mice model with human APL cells

In our previous study, lycorine, a natural alkaloid extracted from Amaryllidaceae, exhibited anti-leukemia effects in vitro. To determine whether lycorine has an anti-tumor effect in vivo, a series of experiments were carried out in this study. HL-60 cells (5 × 10⁶) were inoculated i.v. into severe combined immuno-deficiency (SCID) mice after these mice had been irradiated (total body receiving 200 cGy χ irradiation). Treatment was given once a day from day 2 to 6, and from day 14 to 18. Lycorine (5 or 10 mg/kg/day i.p.) was found to decrease the percentages of immature granular leukocytes and of monocytes among the peripheral blood cells, and the mean survival time of both lycorine-treated groups was longer than that of the control group. Compared with the asynchronous and cytosine arabinoside- (Ara-C) treated (20 mg/kg/day i.p.) group, treatment with lycorine was more effective. Lycorine was also found to alleviate the infiltration of tumor cells into the liver, bone, and marrow. When SCID mice inoculated with HL-60 cells were then treated with lycorine, no severe adverse effects were observed. This study revealed that lycorine, when tested in the human leukemia xenograft models, appears to exhibit anti-tumor activity in vivo and is a useful therapy against acute promyelocytic leukemia.

High-content screening of functional genomic libraries

Recent advances in functional genomics have enabled genome-wide genetic studies in mammalian cells. These include the establishment of high-throughput transfection and viral propagation methodologies, the production of large-scale cDNA and siRNA libraries, and the development of sensitive assay detection processes and instrumentation. The latter has been significantly facilitated by the implementation of automated microscopy and quantitative image analysis, collectively referred to as high-content screening (HCS), toward cell-based functional genomics application. This technology can be applied to whole genome analysis of discrete molecular and phenotypic events at the level of individual cells and promises to significantly expand the scope of functional genomic analyses in mammalian cells. This chapter provides a comprehensive guide for curating and preparing function genomics libraries and performing HCS at the level of the genome.

The limits of reductionism in medicine: could systems biology offer an alternative?

In the first of a two part series, Ahn and colleagues discuss the reductionist approach pervading medicine and explain how a systems approach (as advocated by systems biology) may complement reductionism.

Chemical modulation of receptor signaling inhibits regenerative angiogenesis in adult zebrafish

We examined the role of angiogenesis and the need for receptor signaling using chemical inhibition of the vascular endothelial growth factor receptor in the adult zebrafish tail fin. Using a small-molecule inhibitor, we were able to exert precise control over blood vessel regeneration. An angiogenic limit to tissue regeneration was determined, as avascular tissue containing skin, pigment, neuronal axons and bone precursors could regenerate up to about 1 mm. This indicates that tissues can regenerate without direct interaction with endothelial cells and at a distance from blood supply. We also investigated whether the effects of chemical inhibition could be enhanced in zebrafish vascular mutants. We found that adult zebrafish, heterozygous for a mutation in the critical receptor effector phospholipase Cgamma1, show a greater sensitivity to chemical inhibition. This study illustrates the utility of the adult zebrafish as a new model system for receptor signaling and chemical biology.

Direct Selection of Antibodies from Complex Libraries with the Protein Fragment Complementation Assay

The aim of the present study was to develop the protein fragment complementation assay (PCA) for the intracellular selection of specific binding molecules from the fully synthetic HuCAL antibody library. Here, we describe the first successful selections of specific antibodies by PCA, and we discuss the opportunities and limitations of this approach. First, we enriched an antibody specific for the capsid protein D of bacteriophage lambda (gpD) by ten successive rounds of competitive liquid culture selection. In an independent approach, we selected a specific antibody for the c-Jun N-terminal kinase 2 (JNK2) in a single-step selection setup. In order to obtain specific antibodies in only a single PCA selection round, the selection system was thoroughly investigated and several strategies to reduce the amount of false positives were evaluated. When expressed in the cytoplasm of Escherichia coli, the PCA-selected scFv antibody fragments could be purified as soluble and monomeric proteins. Denaturant-induced unfolding experiments showed that both antibody fragments are stable molecules, even when the disulfide bonds are reduced. Furthermore, antigen-specificity of the PCA-selected antibody fragments is demonstrated by in vivo and in vitro experiments. As antigen binding is retained regardless of the antibody redox state, both PCA-selected antibody fragments can tolerate the loss of disulfide bridge formation. Our results illustrate that it is possible to select well-expressed, stable, antigen-specific, and intracellular functional antibodies by PCA directly.

Functional Screening of Serine Protease Inhibitors in the Medical Leech Hirudo medicinalis Monitored by Intensity Fading MALDI-TOF MS

The blood-feeding invertebrates are a rich biological source of drugs and lead compounds to treat cardiovascular diseases because they have evolved highly efficient mechanisms to feed on their hosts by blocking blood coagulation. In this work, we focused our attention on the leech Hirudo medicinalis. We performed, by "intensity fading" MALDI-TOF mass spectrometry, a comprehensive detection and functional analysis of pre-existent peptides and small proteins with the capability of binding to trypsin-like proteases related to blood coagulation. Combining "intensity fading MS" and off-line LC prefractionation allowed us to detect more than 75 molecules present in the leech extract that interact specifically with a trypsin-like protease over a sample profile of nearly 2,000 different peptides/proteins in the 2-20-kDa range. Moreover we resolved 232 individual components from the complex mixture, 13 of which have high sequence homology with previously described serine protease inhibitors. Our findings indicate that such extracts are much more complex than expected. Additionally, intensity fading MS, when complemented with LC separation strategies, seems to be a useful tool to investigate complex biological samples, establishing a new bridge between profiling, functional peptidomics, and subsequent drug discovery.

Shaking the tree: mapping complex disease genes with linkage disequilibrium

Much effort and expense are being spent internationally to detect genetic polymorphisms contributing to susceptibility to complex human disease. Concomitantly, the technology for detecting and genotyping single nucleotide polymorphisms (SNPs) has undergone rapid development, yielding extensive catalogues of these polymorphisms across the genome. Population-based maps of the correlations amongst SNPs (linkage disequilibrium) are now being developed to accelerate the discovery of genes for complex human diseases. These genomic advances coincide with an increasing recognition of the importance of very large sample sizes for studying genetic effects. Together, these new genetic and epidemiological data hold renewed promise for the identification of susceptibility genes for complex traits. We review the state of knowledge about the structure of the human genome as related to SNPs and linkage disequilibrium, discuss the potential applications of this knowledge to mapping complex disease genes, and consider the issues facing whole genome association scanning using SNPs.

Genetically based therapeutics for cancer: similarities and contrasts with traditional drug discovery and development

The field of molecular therapeutics is in its infancy and represents a promising and novel avenue for targeted cancer treatments. Like the small-molecule and antibody therapeutics before them, however, the genetic-based therapies will face significant research and development challenges in their maturation toward an approved cancer therapy. To facilitate this process, we outline and examine in this review the drug development process, briefly summarizing the research and development paradigms that have accompanied the recent successes of the small-molecule and antibody-based cancer therapeutics. Using this background, we compare and contrast the research and development experiences of small-molecule and antibody therapeutics with genetic-based cancer therapeutics, using oncolytic viruses as a defined example of an experimental molecular therapeutic for cancer.

The promise of genomics to identify novel therapeutic targets

The cataloguing of the human genome has provided an unprecedented prospectus for target identification and drug discovery. A current analysis indicates that slightly more than 3000 unique protein encoding loci are potentially amenable to pharmacological intervention (the 'druggable genome', which can be queried at http://function.gnf.org/druggable). However, the assessment of genome sequence data has not resulted in the anticipated acceleration of novel therapeutic developments. The basis for this shortfall lies in the significant attrition rates endemic to preclinical/clinical development, as well as the often underestimated complexity of gene function in higher order biological systems. To address the latter issue, a number of strategies have emerged to facilitate genomics-driven target identification and validation, including cellular profiling of gene function, in silico modelling of gene networks, and systematic analyses of protein complexes. The expectation is that the integration of these and other systems-based technologies may enable the conversion of potential genomic targets into functionally validated molecules, and result in practicable gene-based drug discovery pipelines.

Disease-specific target selection: a critical first step down the right road

Relevance of a drug target for a disease is often inferred with strong belief but fragile evidence. Here, a program for early identification of human disease-specific drug targets using high-throughput genetic associations is described. Large numbers of well-characterized patients (>1000) and matched controls are screened for genetic associations using several thousand (>7000) single nucleotide polymorphisms from more than 1500 genes. The genes were selected because they are members of target classes for which there are precedents for high-throughput chemical screening technology. This review summarizes the methods and intensive data analyses leading to target gene identification for type 2 diabetes mellitus, including the statistical permutation methodology used to correct for many variables.

Systems modeling: a pathway to drug discovery

Systems modeling is emerging as a valuable tool in therapeutics. This is seen by the increasing use of clinically relevant computational models and a rise in systems biology companies working with the pharmaceutical industry. Systems models have helped understand the effects of pharmacological intervention at receptor, intracellular and intercellular communication stages of cell signaling. For instance, angiogenesis models at the ligand-receptor interaction level have suggested explanations for the failure of therapies for cardiovascular disease. Intracellular models of myeloma signaling have been used to explore alternative drug targets and treatment schedules. Finally, modeling has suggested novel approaches to treating disorders of intercellular communication, such as diabetes. Systems modeling can thus fill an important niche in therapeutics by making drug discovery a faster and more systematic process.

Optimizing the discovery organization for innovation

Strategic management is the process of adapting organizational structure and management principles to fit the strategic goal of the business unit. The pharmaceutical industry has generally been expert at optimizing its organizations for drug development, but has rarely implemented different structures for the early discovery process, where the objective is innovation and the transformation of innovation into drug projects. Here, a set of strategic management methods is proposed, covering team composition, organizational structure, management principles and portfolio management, which are designed to increase the level of innovation in the early drug discovery process.

Development of an ischemic tolerance model in a PC12 cell line

Although ischemic tolerance has been described in a variety of primary cell culture systems, no similar in vitro models have been reported with any cell line. A model of ischemic preconditioning in the rat pheochromocytoma PC12 cell line is described here. When compared to nonpreconditioned cells, preexposure of PC12 cells to 6 hours of oxygen and glucose deprivation (OGD) significantly increased cell viability after 15 hours of OGD 24 hours later. Flow cytometry analysis of cells labeled with specific markers for apoptosis, Annexin V, and Hoechst 33342, and of DNA content, revealed that apoptosis is involved in OGD-induced PC12 cell death and that preconditioning of the cells mainly counteracts the effect of apoptosis. Immunocytochemistry of caspase-3, a central executioner in the apoptotic process, further confirmed the activation of apoptotic pathways in OGD-induced PC12 cell death. This model may be useful to investigate the cellular mechanisms involved in neuronal transient tolerance following ischemia.

Setting sights on the treatment of ocular angiogenesis using antisense oligonucleotides

The application of antisense technology to study physiological and disease processes continues to mature. Antisense approaches are among the most direct means to use genomic sequence information. When developing therapeutics, applications range from early target validation in discovery to the therapeutic product. In this review, we describe the application of antisense oligonucleotides (ASOs) to identify genes that are important in controlling angiogenesis. High-throughput assays in vitro have been used to evaluate many gene targets. Genes that appear to be important in angiogenesis are then evaluated further in animal models of ocular angiogenesis. The ability of ASOs to reduce target-gene expression in the appropriate cells in the eye raises the possibility that this class of compounds could be used for target validation in vivo, and also be developed as a novel class of therapeutics in their own right.

Effects of lycorine on HL-60 cells via arresting cell cycle and inducing apoptosis

As a natural anti-cancer alkaloid extracted from Amaryllidaceae, lycorine shows various biological effects on tumor cells. The survival rate of HL-60 cells exposed to lycorine was decreased in a dose-dependent manner with 1 microM as the 50% inhibitory concentration (IC50), cell growth was slowed down by arresting cell cycle at G2/M phase, and cell regeneration potential was inhibited. HL-60 cells exhibited typical apoptotic morphological changes, apoptotic DNA "ladder" pattern, and sub-G1 peak in cell phase distribution, showing apoptosis of HL-60 cells. To further understand the apoptotic molecular mechanism of lycorine on HL-60 cells, caspase activity was tested by colorimetric assay, and the expression of Bcl-2 and Bax proteins was examined by Western blotting. The increase of caspase-8, -9, -3 activities demonstrated that caspase was a key mediator of apoptotic pathways induced by lycorine. Under-expression of Bcl-2 and increase of Bax:Bcl-2 ratio showed that Bcl-2 family proteins were involved in apoptosis. Our finding suggests that lycorine can suppress leukemia growth and reduce cell survival via arresting cell cycle and inducing apoptosis of tumor cells.

The role of the medicinal chemist in drug discovery--then and now

The role of the medicinal chemist in drug discovery has undergone major changes in the past 25 years, mainly because of the introduction of technologies such as combinatorial chemistry and structure-based drug design. As medicinal chemists with more than 50 years of combined experience spanning the past four decades, we discuss this changing role using examples from our own and others' experience. This historical perspective could provide insights in to how to improve the current model for drug discovery by helping the medicinal chemist regain the creative role that contributed to past successes.

Pharmacogenetics and drug development: the path to safer and more effective drugs

Pharmacogenetics provides opportunities for informed decision-making along the pharmaceutical pipeline. There is a growing literature of retrospective studies of marketed medicines that describe efficacy or safety on the basis of patient genotypes. These studies emphasize the potential prospective use of genome information to enhance success in finding new medicines. An example of a prospective efficacy pharmacogenetic Phase-IIA proof-of-concept study is described. Inserting a rapidly performed efficacy pharmacogenetic step after initial clinical data are obtained can provide confidence for a commitment to full drug development. The rapid identification of adverse events during and after drug development using genomic mapping tools is also reviewed.

Pharmacogenetics

This article provides an introduction to the discipline of pharmacogenetics and discusses the implications of pharmacogenetics research for primary care practice. Examples are given of how genetic information can predict and inform; drug interactions influencing drug efficacy, metabolism, dosing, and toxicity. Caveats on the need for vigilance in the interpretation of pharmacogenetics studies are discussed briefly, together with the need for a convergence of biomolecular research, translational research, education,and policy to promote evidence-based genetic medicine.

Quantitative X-ray photoelectron spectroscopy and time-of-flight secondary ion mass spectrometry characterization of the components in DNA

The great diversity of techniques to synthesize and use DNA microarrays has made them extremely flexible for a variety of applications. This flexibility also has made standardization difficult, leading to problems comparing data from these different systems. In this work, we use the surface science techniques of X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (TOF-SIMS) to analyze the components of DNA. The atomic ratios of the components of nucleobases, nucleosides, and nucleotides were characterized by XPS. The chemical shifts in the high-resolution XPS spectra allow for their relatively easy resolution. The unique positive and negative ions from the nucleobases, nucleosides, and nucleotides in their TOF-SIMS spectra were identified. This information was used to build a comprehensive table of all of the molecular ions. These standard spectra of DNA components can be used to predict the relative amounts of the bases within more complex molecules either by univariate analysis (i.e., by relating the base molecular ions to the sugar fragment ions within the nucleotides) or by multivariate analysis (e.g., principal component analysis). Our preliminary examination of four oligonucleotides shows promising results in that we can distinguish between two oligomers of similar composition using univariate and multivariate analysis, although additional studies are needed to expand this method to more complex oligomers.

Developments toward a Microfluidic System for Long-Term Monitoring of Dynamic Cellular Events in Immobilized Human Cells

A microfluidic system for long-term real-time monitoring of dynamic cellular events of immobilized human cells was investigated. The luciferase reporter gene activity in the reporter cell line HFF11, based on HeLa cells, was used as the model system. The cells were immobilized on silicon flow-through microchips and continuously supplied with a cell medium at 2 microL/min while maintaining the chip at 37 degrees C. The HFF11 cell line was designed for high-throughput screening of ligands for seven-transmembrane receptors. When a ligand binds, the receptor is activated and a cascade of intracellular reactions starts, ending with the synthesis of the reporter protein Photinus luciferase. The major goal was to develop a microfluidic system for continuous long-term assaying of the intracellular reporter gene activity in real time and determine the conditions, which could minimize cells stress and hence unspecific expression of the reporter gene. In the resulting microfluidic system and assay protocol, the cell microchip could be kept and assayed for a period up to 30 h. The developed system and data outcome was compared with a corresponding microtiter plate performed with the same cell line to highlight the advantages obtained in the microfluidic format.

The evolution of microarrayed compound screening

This review describes recent developments in the evolutionary process of microarrayed compound screening (microARCS to become a robust and efficient ultra-high-throughput screening technology. Improvements in compound spotting (including new quality-control methods), gel casting and imaging, together with software capable of automatic analysis and deconvolution of images, have helped to streamline the screening process. A variety of screening projects using cell-based and non-cell-based approaches have been successfully concluded using microARCS. Comparison of hits derived from standard microtitre-plate-based screening and from microARCS reveals excellent overlap. Furthermore, there seems to be no bias towards finding compounds within a particular range of logP values, even though compounds are solubilized from a dry state during the course of the assay.

Surfection: a new platform for transfected cell arrays

Efficient high-throughput expression of genes in mammalian cells can facilitate large-scale functional genomic studies. Towards this aim, we developed a simple yet powerful method to deliver genes into cells by cationic polymers on the surface of substrates. Transfection can be achieved by directly contacting nucleic acid-cell mixtures with the cationic substrates, e.g. polyethylenimine/collagen-coated wells. This single-step matrix-surface- mediated transfection method, termed 'surfection', can efficiently deliver multiple plasmids into cells and can successfully assay siRNA-mediated gene silencing. This technology represents the easiest method to transfer combinations of genes in large-scale arrays, and is a versatile tool for live-cell imaging and cell-based drug screening.

MexAB-OprM specific efflux pump inhibitors in Pseudomonas aeruginosa. Part 2: achieving activity in vivo through the use of alternative scaffolds

Problems of low solubility, high serum protein binding, and lack of efficacy in vivo in first generation MexAB-OprM specific efflux pump inhibitors were addressed. Through the use of pharmacophore modelling, the key structural elements for pump inhibition were defined. Use of alternative scaffolds upon which the key elements were arrayed gave second generation leads with greatly improved physical properties and activity in the potentiation of antibacterial quinolones (levofloxacin and sitafloxacin) versus Pseudomonas aeruginosa in vivo.

Rediscovering the sweet spot in drug discovery

Advances over the past decade in drug discovery technologies have not yet led to an increase in productivity. We analyzed the reasons that have led to this juncture and identify the selection of the right target and the right lead as crucial. New approaches are required to take full advantage of the genomics revolution. For targets, methods are becoming available for high-throughput proteome analysis and pathway characterization that synergize with studies of disease association and differential expression. For leads, methods are being developed that 'reverse' the high-throughput screening paradigm by mapping drugs and drug-like compounds back onto the proteome. The synergy between pathway mapping and compound mapping could allow the pharmaceutical and biotechnology industries to rediscover the sweet spot of research productivity.

Integrative analysis of intraerythrocytic differentially expressed transcripts yields novel insights into the biology of Plasmodium falciparum

Background

The intraerythrocytic development of Plasmodium falciparum, the most virulent human malaria parasite involves asexual and gametocyte stages. There has been a significant increase in disparate datasets derived from genomic and post-genomic analysis of the parasite that necessitates delivery of integrated analysis from which biological processes important to the survival of the parasite can be determined.

Methods

In order to resolve genes associated with stage differentially expressed transcripts, we have developed and implemented an integrative approach that combines evidence from P. falciparum expressed sequence tags (ESTs), genomic, microarray, proteomic and gene ontology data.

Results

A total of 143 gametocyte-overexpressed and 51 asexual-overexpressed transcripts were identified. A subset of 74 genes associated with these transcripts showed evidence of stage-correlated protein expression, of which 53 have not been experimentally characterised. Our study has revealed (1) possible regulatory mechanisms in malaria parasites' gametocyte maturation, (2) correlation between EST and microarray data for a P. falciparum gene family to present unique EST-derived information, (3) candidate drug and antigenic targets on which computational and experimental studies can be performed, and (4) the need for more empirical studies on gene and protein expression in malaria parasites.

Conclusion

Applying different domains of data to the same underlying gene set has yielded novel insights into the biology of the parasite and presents an approach to appraise critically the data quality of post-genomic datasets from malaria parasites.