Structural Requirements for Dihydrobenzoxazepinone Anthelmintics: Actions against Medically Important and Model Parasites: Trichuris muris, Brugia malayi, Heligmosomoides polygyrus, and Schistosoma mansoni.

Nine hundred million people are infected with the soil-transmitted helminths Ascaris lumbricoides (roundworm), hookworm, and Trichuris trichiura (whipworm). However, low single-dose cure rates of the benzimidazole drugs, the mainstay of preventative chemotherapy for whipworm, together with parasite drug resistance, mean that current approaches may not be able to eliminate morbidity from trichuriasis. We are seeking to develop new anthelmintic drugs specifically with activity against whipworm as a priority and previously identified a hit series of dihydrobenzoxazepinone (DHB) compounds that block motility of ex vivo Trichuris muris. Here, we report a systematic investigation of the structure-activity relationship of the anthelmintic activity of DHB compounds. We synthesized 47 analogues, which allowed us to define features of the molecules essential for anthelmintic action as well as broadening the chemotype by identification of dihydrobenzoquinolinones (DBQs) with anthelmintic activity. We investigated the activity of these compounds against other parasitic nematodes, identifying DHB compounds with activity against Brugia malayi and Heligmosomoides polygyrus. We also demonstrated activity of DHB compounds against the trematode Schistosoma mansoni, a parasite that causes schistosomiasis. These results demonstrate the potential of DHB and DBQ compounds for further development as broad-spectrum anthelmintics

Changing patterns of cancer incidence in the early- and late-HAART periods: the Swiss HIV Cohort Study

BACKGROUND: The advent of highly active antiretroviral therapy (HAART) in 1996 led to a decrease in the incidence of Kaposi's sarcoma (KS) and non-Hodgkin's lymphoma (NHL), but not of other cancers, among people with HIV or AIDS (PWHA). It also led to marked increases in their life expectancy. METHODS: We conducted a record-linkage study between the Swiss HIV Cohort Study and nine Swiss cantonal cancer registries. In total, 9429 PWHA provided 20,615, 17,690, and 15,410 person-years in the pre-, early-, and late-HAART periods, respectively. Standardised incidence ratios in PWHA vs the general population, as well as age-standardised, and age-specific incidence rates were computed for different periods. RESULTS: Incidence of KS and NHL decreased by several fold between the pre- and early-HAART periods, and additionally declined from the early- to the late-HAART period. Incidence of cancers of the anus, liver, non-melanomatous skin, and Hodgkin's lymphoma increased in the early- compared with the pre-HAART period, but not during the late-HAART period. The incidence of all non-AIDS-defining cancers (NADCs) combined was similar in all periods, and approximately double that in the general population. CONCLUSIONS: Increases in the incidence of selected NADCs after the introduction of HAART were largely accounted for by the ageing of PWHA

Four-Year Treatment Outcomes of Adult Patients Enrolled in Mozambique's Rapidly Expanding Antiretroviral Therapy Program

BACKGROUND: In Mozambique during 2004-2007 numbers of adult patients (≥15 years old) enrolled on antiretroviral therapy (ART) increased about 16-fold, from <5,000 to 79,500. All ART patients were eligible for co-trimoxazole. ART program outcomes, and determinants of outcomes, have not yet been reported. METHODOLOGY/PRINCIPAL FINDINGS: In a retrospective cohort study, we investigated rates of mortality, attrition (death, loss to follow-up, or treatment cessation), immunologic treatment failure, and regimen-switch, as well as determinants of selected outcomes, among a nationally representative sample of 2,596 adults initiating ART during 2004-2007. At ART initiation, median age of patients was 34 and 62% were female. Malnutrition and advanced disease were common; 18% of patients weighed <45 kilograms, and 15% were WHO stage IV. Median baseline CD4(+) T-cell count was 153/µL and was lower for males than females (139/µL vs. 159/µL, p<0.01). Stavudine, lamivudine, and nevirapine or efavirenz were prescribed to 88% of patients; only 31% were prescribed co-trimoxazole. Mortality and attrition rates were 3.4 deaths and 19.8 attritions per 100 patient-years overall, and 12.9 deaths and 57.2 attritions per 100 patient-years in the first 90 days. Predictors of attrition included male sex [adjusted hazard ratio (AHR) 1.5; 95% confidence interval (CI), 1.3-1.8], weight <45 kg (AHR 2.1; 95% CI, 1.6-2.9, reference group >60 kg), WHO stage IV (AHR 1.7; 95% CI, 1.3-2.4, reference group WHO stage I/II), lack of co-trimoxazole prescription (AHR 1.4; 95% CI, 1.0-1.8), and later calendar year of ART initiation (AHR 1.5; 95% CI, 1.2-1.8). Rates of immunologic treatment failure and regimen-switch were 14.0 and 0.6 events per 100-patient years, respectively. CONCLUSIONS: ART initiation at earlier disease stages and scale-up of co-trimoxazole among ART patients could improve outcomes. Research to determine reasons for low regimen-switch rates and increasing rates of attrition during program expansion is needed

Using Functional Signatures to Identify Repositioned Drugs for Breast, Myelogenous Leukemia and Prostate Cancer

The cost and time to develop a drug continues to be a major barrier to widespread distribution of medication. Although the genomic revolution appears to have had little impact on this problem, and might even have exacerbated it because of the flood of additional and usually ineffective leads, the emergence of high throughput resources promises the possibility of rapid, reliable and systematic identification of approved drugs for originally unintended uses. In this paper we develop and apply a method for identifying such repositioned drug candidates against breast cancer, myelogenous leukemia and prostate cancer by looking for inverse correlations between the most perturbed gene expression levels in human cancer tissue and the most perturbed expression levels induced by bioactive compounds. The method uses variable gene signatures to identify bioactive compounds that modulate a given disease. This is in contrast to previous methods that use small and fixed signatures. This strategy is based on the observation that diseases stem from failed/modified cellular functions, irrespective of the particular genes that contribute to the function, i.e., this strategy targets the functional signatures for a given cancer. This function-based strategy broadens the search space for the effective drugs with an impressive hit rate. Among the 79, 94 and 88 candidate drugs for breast cancer, myelogenous leukemia and prostate cancer, 32%, 13% and 17% respectively are either FDA-approved/in-clinical-trial drugs, or drugs with suggestive literature evidences, with an FDR of 0.01. These findings indicate that the method presented here could lead to a substantial increase in efficiency in drug discovery and development, and has potential application for the personalized medicine

A pharmacological organization of G protein–coupled receptors

Protein classification typically uses structural, sequence, or functional similarity. Here we introduce an orthogonal method that organizes proteins by ligand similarity, focusing here on the class A G protein-coupled receptor (GPCR) protein family. Comparing a ligand-based dendogram to a sequence-based one, we sought examples of GPCRs that were distantly linked by sequence but neighbors by ligand similarity. Experimental testing of compounds predicted to link three of these new pairs confirmed the predicted association, with potencies ranging from the low-nanomolar to low-micromolar. We then identified hundreds of non-GPCRs closely related to GPCRs by ligand similarity, including the CXCR2 chemokine receptor to Casein kinase I, the cannabinoid receptors to epoxide hydrolase 2, and the α2 adrenergic receptor to phospholipase D. These, too, were confirmed experimentally. Ligand similarities among these targets may reflect a chemical integration in the time domain of molecular signaling

Chemical and protein structural basis for biological crosstalk between PPARα and COX enzymes

We have previously validated a probabilistic framework that combined computational approaches for predicting the biological activities of small molecule drugs. Molecule comparison methods included molecular structural similarity metrics and similarity computed from lexical analysis of text in drug package inserts. Here we present an analysis of novel drug/target predictions, focusing on those that were not obvious based on known pharmacological crosstalk. Considering those cases where the predicted target was an enzyme with known 3D structure allowed incorporation of information from molecular docking and protein binding pocket similarity in addition to ligand-based comparisons. Taken together, the combination of orthogonal information sources led to investigation of a surprising predicted relationship between a transcription factor and an enzyme, specifically, PPARα and the cyclooxygenase enzymes. These predictions were confirmed by direct biochemical experiments which validate the approach and show for the first time that PPARα agonists are cyclooxygenase inhibitors

Modeling of Human Prokineticin Receptors: Interactions with Novel Small-Molecule Binders and Potential Off-Target Drugs

The Prokineticin receptor (PKR) 1 and 2 subtypes are novel members of family A GPCRs, which exhibit an unusually high degree of sequence similarity. Prokineticins (PKs), their cognate ligands, are small secreted proteins of ∼80 amino acids; however, non-peptidic low-molecular weight antagonists have also been identified. PKs and their receptors play important roles under various physiological conditions such as maintaining circadian rhythm and pain perception, as well as regulating angiogenesis and modulating immunity. Identifying binding sites for known antagonists and for additional potential binders will facilitate studying and regulating these novel receptors. Blocking PKRs may serve as a therapeutic tool for various diseases, including acute pain, inflammation and cancer.Ligand-based pharmacophore models were derived from known antagonists, and virtual screening performed on the DrugBank dataset identified potential human PKR (hPKR) ligands with novel scaffolds. Interestingly, these included several HIV protease inhibitors for which endothelial cell dysfunction is a documented side effect. Our results suggest that the side effects might be due to inhibition of the PKR signaling pathway. Docking of known binders to a 3D homology model of hPKR1 is in agreement with the well-established canonical TM-bundle binding site of family A GPCRs. Furthermore, the docking results highlight residues that may form specific contacts with the ligands. These contacts provide structural explanation for the importance of several chemical features that were obtained from the structure-activity analysis of known binders. With the exception of a single loop residue that might be perused in the future for obtaining subtype-specific regulation, the results suggest an identical TM-bundle binding site for hPKR1 and hPKR2. In addition, analysis of the intracellular regions highlights variable regions that may provide subtype specificity

Consumer–brand identification revisited: An integrative framework of brand identification, customer satisfaction, and price image and their role for brand loyalty and word of mouth

Consumer–brand identification has received considerable attraction among scholars and practitioners in recent years. We contribute to previous research by proposing an integrative model that includes consumer–brand identification, customer satisfaction, and price image to investigate the interrelationships among these constructs as well as their effects on brand loyalty and positive word of mouth. To provide general results, we empirically test the model using a sample of 1443 respondents from a representative consumer panel and 10 service/product brands. The results demonstrate that identification, satisfaction, and price image significantly influence both loyalty and word of mouth. Moreover, we find significant interrelationships among the constructs: Identification positively influences both satisfaction and price image, which also increases satisfaction. By disclosing the relative importance of three separate ways of gaining and retaining customers, this study helps managers more appropriately choose the right mix of branding, pricing, and relationship marketing. From an academic point of view, our research is the first to explicitly examine the effects of the concept of identification for price management and to integrate variables from the fields of branding, relationship marketing, and behavioral pricing, which have separately been identified as particularly important determinants of marketing outcomes

Drug Discovery Using Chemical Systems Biology: Identification of the Protein-Ligand Binding Network To Explain the Side Effects of CETP Inhibitors

Systematic identification of protein-drug interaction networks is crucial to correlate complex modes of drug action to clinical indications. We introduce a novel computational strategy to identify protein-ligand binding profiles on a genome-wide scale and apply it to elucidating the molecular mechanisms associated with the adverse drug effects of Cholesteryl Ester Transfer Protein (CETP) inhibitors. CETP inhibitors are a new class of preventive therapies for the treatment of cardiovascular disease. However, clinical studies indicated that one CETP inhibitor, Torcetrapib, has deadly off-target effects as a result of hypertension, and hence it has been withdrawn from phase III clinical trials. We have identified a panel of off-targets for Torcetrapib and other CETP inhibitors from the human structural genome and map those targets to biological pathways via the literature. The predicted protein-ligand network is consistent with experimental results from multiple sources and reveals that the side-effect of CETP inhibitors is modulated through the combinatorial control of multiple interconnected pathways. Given that combinatorial control is a common phenomenon observed in many biological processes, our findings suggest that adverse drug effects might be minimized by fine-tuning multiple off-target interactions using single or multiple therapies. This work extends the scope of chemogenomics approaches and exemplifies the role that systems biology has in the future of drug discovery