Publications by authors named "Whitebread S"

Excipients, considered "inactive ingredients," are a major component of formulated drugs and play key roles in their pharmacokinetics. Despite their pervasiveness, whether they are active on any targets has not been systematically explored. We computed the likelihood that approved excipients would bind to molecular targets.

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Metallo-β-lactamases (MBLs), such as New Delhi metallo-β-lactamase (NDM-1) have spread world-wide and present a serious threat. Expression of MBLs confers resistance in Gram-negative bacteria to all classes of β-lactam antibiotics, with the exception of monobactams, which are intrinsically stable to MBLs. However, existing first generation monobactam drugs like aztreonam have limited clinical utility against MBL-expressing strains because they are impacted by serine β-lactamases (SBLs), which are often co-expressed in clinical isolates.

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The Food and Drug Administration Adverse Event Reporting System (FAERS) remains the primary source for post-marketing pharmacovigilance. The system is largely un-curated, unstandardized, and lacks a method for linking drugs to the chemical structures of their active ingredients, increasing noise and artefactual trends. To address these problems, we mapped drugs to their ingredients and used natural language processing to classify and correlate drug events.

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Secondary pharmacology is an essential component of drug discovery and is used extensively in the pharmaceutical industry for achieving optimal specificity of new drugs via early hazard identification and off-target mitigation. The importance of this discipline has been achieved by increasing its translational value, based on the recognition of biological target-drug molecule-adverse drug reaction (ADR) associations and integration of secondary pharmacology data with pharmacokinetic parameters. Information obtained from clinical ADRs, from recognition of specific phenotypes of animal models and from hereditary diseases provides increasing regulatory confidence in the target-based approach to ADR prediction and mitigation.

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Blockade of the hERG potassium channel prolongs the ventricular action potential (AP) and QT interval, and triggers early after depolarizations (EADs) and torsade de pointes (TdP) arrhythmia. Opinions differ as to the causal relationship between hERG blockade and TdP, the relative weighting of other contributing factors, definitive metrics of preclinical proarrhythmicity, and the true safety margin in humans. Here, we have used in silico techniques to characterize the effects of channel gating and binding kinetics on hERG occupancy, and of blockade on the human ventricular AP.

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Article Synopsis
  • The study investigates a new computational method called HTS fingerprints (HTSFPs) for predicting small molecule-target interactions in drug discovery, emphasizing the need to consider more than just chemical structures.
  • By screening over 1,400 drugs and 1,300 natural products across 200 assays, the researchers generated activity patterns that led to the identification of more than 5,000 novel targets, with notable differences in target types between drugs and natural products.
  • The findings revealed that HTSFPs could predict some targets beyond the capabilities of traditional methods, with a high validation rate for drug-target interactions, including a link between the HIV drug Tipranavir and unexpected effects related to blood clotting.
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Matched molecular pair analysis (MMPA) has become a major tool for analyzing large chemistry data sets for promising chemical transformations. However, the dependence of MMPA predictions on data constraints such as the number of pairs involved, experimental uncertainty, source of the experiments, and variability of the true physical effect has not yet been described. In this contribution the statistical basics for judging MMPA are analyzed.

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In vitro pharmacological profiling is increasingly being used earlier in the drug discovery process to identify undesirable off-target activity profiles that could hinder or halt the development of candidate drugs or even lead to market withdrawal if discovered after a drug is approved. Here, for the first time, the rationale, strategies and methodologies for in vitro pharmacological profiling at four major pharmaceutical companies (AstraZeneca, GlaxoSmithKline, Novartis and Pfizer) are presented and illustrated with examples of their impact on the drug discovery process. We hope that this will enable other companies and academic institutions to benefit from this knowledge and consider joining us in our collaborative knowledge sharing.

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Discovering the unintended 'off-targets' that predict adverse drug reactions is daunting by empirical methods alone. Drugs can act on several protein targets, some of which can be unrelated by conventional molecular metrics, and hundreds of proteins have been implicated in side effects. Here we use a computational strategy to predict the activity of 656 marketed drugs on 73 unintended 'side-effect' targets.

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Histone deacetylase (HDAC) inhibitors have shown promise in treating various forms of cancer. However, many HDAC inhibitors from diverse structural classes have been associated with QT prolongation in humans. Inhibition of the human ether a-go-go related gene (hERG) channel has been associated with QT prolongation and fatal arrhythmias.

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One of the main reasons for drug failures in clinical development, or postmarket launch, is lacking or compromised safety margins at therapeutic doses. Organ toxicity with poorly defined mechanisms and adverse drug reactions associated with on- and off-target effects are the major contributors to safety-related shortfalls of many clinical drug candidates. Therefore, to avoid high attrition rates in clinical trials, it is imperative to test compounds for potential adverse reactions during early drug discovery.

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We present a workflow that leverages data from chemogenomics based target predictions with Systems Biology databases to better understand off-target related toxicities. By analyzing a set of compounds that share a common toxic phenotype and by comparing the pathways they affect with pathways modulated by nontoxic compounds we are able to establish links between pathways and particular adverse effects. We further link these predictive results with literature data in order to explain why a certain pathway is predicted.

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We present a novel method to better investigate adverse drug reactions in chemical space. By integrating data sources about adverse drug reactions of drugs with an established cheminformatics modeling method, we generate a data set that is then visualized with a systems biology tool. Thereby new insights into undesired drug effects are gained.

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High throughput screening identified a phenoxyacetic acid scaffold as a novel CRTh2 receptor antagonist chemotype, which could be optimised to furnish a compound with functional potency for inhibition of human eosinophil shape change and oral bioavailability in the rat.

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This study describes a method for mining and modeling binding data obtained from a large panel of targets (in vitro safety pharmacology) to distinguish differences between promiscuous and selective compounds. Two naïve Bayes models for promiscuity and selectivity were generated and validated on a test set as well as publicly available drug databases. The model shows a higher score (lower promiscuity) for marketed drugs than for compounds in early development or compounds that failed during clinical development.

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Preclinical Safety Pharmacology (PSP) attempts to anticipate adverse drug reactions (ADRs) during early phases of drug discovery by testing compounds in simple, in vitro binding assays (that is, preclinical profiling). The selection of PSP targets is based largely on circumstantial evidence of their contribution to known clinical ADRs, inferred from findings in clinical trials, animal experiments, and molecular studies going back more than forty years. In this work we explore PSP chemical space and its relevance for the prediction of adverse drug reactions.

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This article reviews the use of a selection of in vitro assays implemented at Novartis and intends to address exposure and safety in early drug discovery. The authors' own experience, based on a large number of 'real' drug discovery compounds, is described to reflect on what has worked, where improvement is needed and how to best use the data for decision making. Possible strategies are discussed, and guidelines are provided on how to organise assays, extract value and contribute knowledge from the data.

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[(11)C]ABP688 (2) has recently been demonstrated to be a useful PET tracer for in vivo imaging of the metabotropic glutamate receptors type 5 (mGluR5) in rodents. We describe here the identification and preclinical profiling of ABP688 and its tritiated version [(3)H]ABP688, and show that its high affinity (K(d)=2nM), selectivity, and pharmacokinetic properties fulfill all requirements for development as a PET tracer for clinical imaging of the mGlu5 receptor.

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Broad-scale in vitro pharmacology profiling of new chemical entities during early phases of drug discovery has recently become an essential tool to predict clinical adverse effects. Modern, relatively inexpensive assay technologies and rapidly expanding knowledge about G-protein coupled receptors, nuclear receptors, ion channels and enzymes have made it possible to implement a large number of assays addressing possible clinical liabilities. Together with other in vitro assays focusing on toxicology and bioavailability, they provide a powerful tool to aid drug development.

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Combination of structural elements from a potent Y5 antagonist (2) with thiazole fragments that exhibit weak Y5 affinities followed by lead optimisation led to the discovery of (5,6-dihydro-4H-3-thia-1-aza-benzo[e]azulen-2-yl)-piperidin-4-ylmethyl-amino and (4,5-dihydro-6-oxa-3-thia-1-aza-benzo[e]azulen-2-yl)-piperidin-4-ylmethyl-amino derivatives. Both classes of compounds are capable of delivering potent and selective orally and centrally bioavailable NPY Y5 receptor antagonists.

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Leptin decreases food intake and increases energy expenditure in rodents by inhibiting neurones in the hypothalamic arcuate nucleus. The growth hormone secretagogue (GHS) ghrelin is known to stimulate food intake and to be the endogenous ligand for the GHS-receptor, which is strongly expressed in the arcuate nucleus, like the leptin receptor (Ob-R). In this study, we analysed the effect of systemic ghrelin administration on Fos expression in the arcuate nucleus on neurones expressing Ob-R.

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The design of a novel series of NPY-Y5 receptor antagonists is described. Key elements for the design were the identification of weak Y5 hits from a Y1 program, results from a combinatorial approach and database mining. This led to the discovery of the quinazoline 4 and the aryl-sulphonamide moiety as major components of the pharmacophore for Y5 affinity.

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Objective: The purpose of the present study was to investigate the continuing validity of the hypothesis that leptin is a physiologically important regulator of food intake, using the human leptin mutant R128Q leptin.

Design: In a cellular proliferation assay, based on BAF-3 cells transfected with the murine ObRb receptor, R128Q leptin was shown to be devoid of agonistic activity and to competitively inhibit the proliferative effects of leptin. To determine whether R128Q leptin was also an antagonist of leptin in vivo, the leptin mutant was injected intracerebroventricularly (i.

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Background: AT1 angiotensin II (AT1 Ang II) receptor activation has been shown to cause increased vascular resistance in the systemic (SVR), pulmonary (PVR), and coronary vasculature which may be of particular importance in the setting of congestive heart failure (CHF). The overall goal of this study was to examine the effects of acute AT1 Ang II receptor inhibition on left ventricular (LV) pump function, systemic hemodynamics, and regional blood flow patterns in the normal state and with CHF, both at rest and with treadmill-induced exercise.

Methods And Results: Pigs (25 kg) were instrumented to measure cardiac output (CO), SVR, and PVR, and LV myocardial blood flow distribution in the conscious state and were assigned to one of two groups: (1) pacing-induced CHF (240 bpm for 3 weeks, n = 6) or (2) sham controls (n = 5).

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The new neuropeptide Y (NPY) Y5 receptor antagonist CGP 71683A displayed high affinity for the cloned rat NPY Y5 subtype, but > 1, 000-fold lower affinity for the cloned rat NPY Y1, Y2, and Y4 subtypes. In LMTK cells transfected with the human NPY Y5 receptor, CGP 71683A was without intrinsic activity and antagonized NPY-induced Ca2+ transients. CGP 71683A was given intraperitoneally (dose range 1-100 mg/kg) to a series of animal models of high hypothalamic NPY levels.

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