Steven Whitebread

Preliminary biochemical characterization of two angiotensin II receptor subtypes

Two angiotensin II receptor subtypes (A and B) are described from rat and human tissues. They have been characterised using specific peptidic and non-peptidic ligands with affinities differing by 1000 fold or more. These subtypes are present in adrenal glomerulosa of both species. Human uterus contains only subtype A, whereas both subtypes are found in rat uterus. Vascular smooth muscle cells in culture express only subtype B. Dithio-threitol totally inhibits binding to subtype B, but enhances the affinity to subtype A. There is a good correlation between the affinities of the selected agonists and antagonists for the two subtypes in the various tissues tested which is a usual requirement for receptor classification.

Large Scale Prediction and Testing of Drug Activity on Side-Effect Targets

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. Approximately half of the predictions were confirmed, either from proprietary databases unknown to the method or by new experimental assays. Affinities for these new off-targets ranged from 1 nM to 30 μM. To explore relevance, we developed an association metric to prioritize those new off-targets that explained side effects better than any known target of a given drug, creating a drug–target–adverse drug reaction network. Among these new associations was the prediction that the abdominal pain side effect of the synthetic oestrogen chlorotrianisene was mediated through its newly discovered inhibition of the enzyme cyclooxygenase-1. The clinical relevance of this inhibition was borne out in whole human blood platelet aggregation assays. This approach may have wide application to de-risking toxicological liabilities in drug discovery.

Reducing safety-related drug attrition: the use of in vitro pharmacological profiling

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.

Analysis of Pharmacology Data and the Prediction of Adverse Drug Reactions and Off-Target Effects from Chemical Structure

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. Firstly, in silico (computational) Bayesian models for 70 PSP‐related targets were built, which are able to detect 93 % of the ligands binding at IC50≤10 μM at an overall correct classification rate of about 94 %. Secondly, employing the World Drug Index (WDI), a model for adverse drug reactions was built directly based on normalized side‐effect annotations in the WDI, which does not require any underlying functional knowledge. This is, to our knowledge, the first attempt to predict adverse drug reactions across hundreds of categories from chemical structure alone. On average 90 % of the adverse drug reactions observed with known, clinically used compounds were detected, an overall correct classification rate of 92 %. Drugs withdrawn from the market (Rapacuronium, Suprofen) were tested in the model and their predicted ADRs align well with known ADRs. The analysis was repeated for acetylsalicylic acid and Benperidol which are still on the market. Importantly, features of the models are interpretable and back‐projectable to chemical structure, raising the possibility of rationally engineering out adverse effects. By combining PSP and ADR models new hypotheses linking targets and adverse effects can be proposed and examples for the opioid μ and the muscarinic M2 receptors, as well as for cyclooxygenase‐1 are presented. It is hoped that the generation of predictive models for adverse drug reactions is able to help support early SAR to accelerate drug discovery and decrease late stage attrition in drug discovery projects. In addition, models such as the ones presented here can be used for compound profiling in all development stages.

Pharmacological profile of valsartan: a potent, orally active, nonpeptide antagonist of the angiotensin II AT1-receptor subtype

1 The pharmacological profile of valsartan, (S)‐N‐valeryl‐N‐{[2′‐(1H‐tetrazol‐5‐yl)biphenyl‐4‐yl]‐methyl}‐valine, a potent, highly selective, and orally active antagonist at the angiotensin II (AII) AT1‐receptor, was studied in vitro and in vivo. 2 Valsartan competed with [125I]‐AII at its specific binding sites in rat aortic smooth muscle cell membranes (AT1‐receptor subtype) with a Ki of 2.38 nm, but was about 30,000 times less active in human myometrial membranes (AT2‐receptor subtype). 3 In rabbit aortic rings incubated for 5 min with valsartan, at concentrations of 2, 20 and 200 nm, the concentration‐response curve of AII was displaced to the right and the maximum response was reduced by 33%, 36% and 40%, respectively. Prolongation of the incubation time with valsartan to 1 h or 3 h, further reduced the maximum response by 48% or 59% (after 20 nm) and by 59% or 60% (after 200 nm) respectively. After 3 h incubation an apparent pKB value of 9.26 was calculated. Contractions induced by noradrenaline, 5‐hydroxytryptamine, or potassium chloride were not affected by valsartan. No agonistic effects were observed in the rabbit aorta at concentrations of valsartan up to 2 μm. 4 In bovine adrenal glomerulosa, valsartan inhibited All‐stimulated aldosterone release without affecting the maximum response (pA2 8.4). 5 In the pithed rat, oral administration of valsartan (10 mg kg−1) shifted the All‐induced pressor response curves to the right, without affecting responses induced by the electrical stimulation of the sympathetic outflow or by noradrenaline. Animals treated with valsartan 24 h before pithing also showed significant inhibition of the response to AII. 6 In conscious, two‐kidney, one‐clip renal hypertensive rats (2K1C), valsartan decreased blood pressure in a dose‐dependent manner after single i.v. or oral administration. The respective ED30 values were 0.06 mg kg−1 (i.v.) and 1.4 mg kg−1 (p.o.). The antihypertensive effect lasted for at least 24 h after either route of administration. After repeated oral administration for 4 days (3 and 10 mg kg−1 daily), in 2K1C renal hypertensive rats, systolic blood pressure was consistently decreased, but heart rate was not significantly affected. 7 In conscious, normotensive, sodium‐depleted marmosets, valsartan decreased mean arterial pressure, measured by telemetry, after oral doses of 1–30 mg kg−1. The hypotensive effect persisted up to 12 h after 3 and 10 mg kg−1 and up to 24 h after 30 mg kg−1. 8 In sodium‐depleted marmosets, the hypotensive effect of valsartan lasted longer than that of losartan (DuP 753). In renal hypertensive rats, both agents had a similar duration (24 h), but a different onset of action (valsartan at 1 h, losartan between 2 h and 24 h). 9 These results demonstrate that valsartan is a potent, specific, highly selective antagonist of AII at the AT1‐receptor subtype and does not possess agonistic activity. Furthermore, it is an efficacious, orally active, blood pressure‐lowering agent in conscious renal hypertensive rats and in conscious normotensive, sodium‐depleted primates.

Keynote review: In vitro safety pharmacology profiling: an essential tool for successful drug development

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. In this article, we review the development of this tool for drug discovery, its appropriate use and predictive value.

FOOD INTAKE IN FREE-FEEDING AND ENERGY-DEPRIVED LEAN RATS IS MEDIATED BY THE NEUROPEPTIDE Y5 RECEPTOR

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. In lean satiated rats CGP 71683A significantly antagonized the increase in food intake induced by intracerebroventricular injection of NPY. In 24-h fasted and streptozotocin diabetic rats CGP 71683A dose-dependently inhibited food intake. During the dark phase, CGP 71683A dose-dependently inhibited food intake in free-feeding lean rats without affecting the normal pattern of food intake or inducing taste aversion. In free-feeding lean rats, intraperitoneal administration of CGP 71683A for 28 d inhibited food intake dose-dependently with a maximum reduction observed on days 3 and 4. Despite the return of food intake to control levels, body weight and the peripheral fat mass remained significantly reduced. The data demonstrate that the NPY Y5 receptor subtype plays a role in NPY-induced food intake, but also suggest that, with chronic blockade, counterregulatory mechanisms are induced to restore appetite.

Modeling Promiscuity Based on in vitro Safety Pharmacology Profiling Data

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. Such models can be used in triaging high‐throughput screening data or for lead optimization.

Gaining Insight into Off-Target Mediated Effects of Drug Candidates with a Comprehensive Systems Chemical Biology Analysis

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. Specifically, relevant pathways are elucidated for the side effects rhabdomyolysis and hypotension. Prospectively, our approach is valuable not only to better understand toxicities of novel compounds early on but also for drug repurposing exercises to find novel uses for known drugs.

Angiotensin II AT2 receptors do not interact with guanine nucleotide binding proteins.

We have studied the effect of GTP gamma S on the affinity and binding kinetics of angiotensin II in plasma membrane particulate prepared from tissues expressing either only AT1 (human renal artery smooth muscle cells), only AT2 (human myometrium and bovine cerebellar cortex) or both angiotensin II receptor subtypes (rat adrenal glomerulosa). We also examined the ability of angiotensin II to stimulate GTP gamma[35S] incorporation in these membrane preparations. In contrast to its effects on angiotensin II binding to the AT1 receptor, GTP gamma S does not affect binding parameters to the AT2 receptor. Moreover, in tissues expressing solely AT2 receptors, angiotensin II was unable to induce GTP gamma[35S] incorporation. These findings indicate that AT2 receptors do not interact with G-proteins and that angiotensin II must therefore mediate some of its effects through G-protein-independent mechanisms.