Development of Pyrazolopyrimidine Anti-Wolbachia Agents for the Treatment of Filariasis.

Anti-Wolbachia therapy has been identified as a viable treatment for combating filarial diseases. Phenotypic screening revealed a series of pyrazolopyrimidine hits with potent anti-Wolbachia activity. This paper focuses on the exploration of the SAR for this chemotype, with improvement of metabolic stability and solubility profiles using medicinal chemistry approaches. Organic synthesis has enabled functionalization of the pyrazolopyrimidine core at multiple positions, generating a library of compounds of which many analogues possess nanomolar activity against Wolbachia in vitro with improved DMPK parameters. A lead compound, 15f, was selected for in vivo pharmacokinetics (PK) profiling in mice. The combination of potent anti-Wolbachia activity in two in vitro assessments plus the exceptional oral PK profiles in mice puts this lead compound in a strong position for in vivo proof-of-concept pharmacodynamics studies and demonstrates the strong potential for further optimization and development of this series for treatment of filariasis in the future.

Prediction of Chameleonic Efficiency.

Chameleonic properties, i. e., the capacity of a molecule to hide polarity in non-polar environments and expose it in water, help achieving sufficient permeability and solubility for drug molecules with high MW. We present models of experimental measures of polarity for a set of 24 FDA approved drugs (MW 405-1113) and one PROTAC (MW 1034). Conformational ensembles in aqueous and non-polar environments were generated using molecular dynamics. A linear regression model that predicts chromatographic apparent polarity (EPSA) with a mean unsigned error of 10 Å2 was derived based on separate terms for donor, acceptor, and total molecular SASA. A good correlation (R2 =0.92) with an experimental measure of hydrogen bond donor potential, Δlog Poct-tol , was found for the mean hydrogen bond donor SASA of the conformational ensemble scaled with Abraham's A hydrogen bond acidity. Two quantitative measures of chameleonic behaviour, the chameleonic efficiency indices, are introduced. We envision that the methods presented herein will be useful to triage designed molecules and prioritize those with the best chance of achieving acceptable permeability and solubility.

Interpreting physicochemical experimental data sets.

With the wealth of experimental physicochemical data available to chemoinformaticians from the literature, commercial, and company databases an increasing challenge is the interpretation of such datasets. Subtle differences in experimental methodology used to generate these datasets can give rise to variations in physicochemical property values. Such methodology nuances will be apparent to an expert experimentalist but not necessarily to the data analyst and modeller. This paper describes the differences between common methodologies for measuring the four most important physicochemical properties namely aqueous solubility, octan-1-ol/water distribution coefficient, pK(a) and plasma protein binding highlighting key factors that can lead to systematic differences. Insight is given into how to identify datasets suitable for combining.

How experimental errors influence drug metabolism and pharmacokinetic QSAR/QSPR models.

We consider the impact of gross, systematic, and random experimental errors in relation to their impact on the predictive ability of QSAR/QSPR DMPK models used within early drug discovery. Models whose training sets contain fewer but repeatedly measured data points, with a defined threshold for the random error, resulted in prediction improvements ranging from 3.3% to 23.0% for an external test set, compared to models built from training sets in which the molecules were defined by single measurements. Similarly, models built on data with low experimental uncertainty, compared to those built on data with higher experimental uncertainty, gave prediction improvements ranging from 3.3% to 27.5%.

In silico physicochemical parameter predictions.

Drug discovery is a complex process with the aim of discovering efficacious molecules where their potency and selectivity are balanced against ADMET properties to set the appropriate dose and dosing interval. The link between physicochemical properties and molecular structure are well established. The subsequent connections between physicochemical properties and a drug's biological behavior provide an indirect link back to structure, facilitating the prediction of a biological property as a consequence of a particular molecular manipulation. Due to this understanding, during early drug discovery in vitro physicochemical property assays are commonly performed to eliminate compounds with properties commensurate with high attrition risks. However, the goal is to accurately predict physicochemical properties to prevent the synthesis of high risk compounds and hence minimize wasted drug discovery efforts. This paper will review the relevance to ADMET behaviors of key physicochemical properties, such as ionization, aqueous solubility, hydrogen bonding strength and hydrophobicity, and the in silico methodology for predicting them.

Selection of a screening panel of rhinoviral serotypes.

A novel methodology for the selection of a representative primary and secondary screening panel of rhinoviral serotypes for the purposes of identifying potential antiviral agents is presented. This methodology focuses on the active-sites of the rhinoviral proteins but does not invoke historical SAR data, thereby avoiding compound bias.

Lead optimisation of pyrazoles as novel FPR1 antagonists.

Optimisation of a series of pyrazole inhibitors of the human FPR1 receptor has been achieved. The use of an in vitro media loss assay was utilised to identify sub-series with more robust DMPK profiles. These were subsequently improved to generate analogues with attractive overall profiles.

In silico prediction of acyl glucuronide reactivity.

Drugs and drug candidates containing a carboxylic acid moiety, including many widely used non-steroidal anti-inflammatory drugs (NSAIDs) are often metabolized to form acyl glucuronides (AGs). NSAIDs such as Ibuprofen are amongst the most widely used drugs on the market, whereas similar carboxylic acid drugs such as Suprofen have been withdrawn due to adverse events. Although the link between these AG metabolites and toxicity is not proven, there is circumstantial literature evidence to suggest that more reactive acyl glucuronides may, in some cases, present a greater risk of exhibiting toxic effects. We wished therefore to rank the reactivity of potential new carboxylate-containing drug candidates, and performed kinetic studies on synthetic acyl glucuronides to benchmark our key compounds. Driven by the desire to quickly rank the reactivity of compounds without the need for lengthy synthesis of the acyl glucuronide, a correlation was established between the degradation half-life of the acyl glucuronide and the half life for the hydrolysis of the more readily available methyl ester derivative. This finding enabled a considerable broadening of chemical property space to be investigated. The need for kinetic measurements was subsequently eliminated altogether by correlating the methyl ester hydrolysis half-life with the predicted (13)C NMR chemical shift of the carbonyl carbon together with readily available steric descriptors in a PLS model. This completely in silico prediction of acyl glucuronide reactivity is applicable within the earliest stages of drug design with low cost and acceptable accuracy to guide intelligent molecular design. This reactivity data will be useful alongside the more complex additional pharmacokinetic exposure and distribution data that is generated later in the drug discovery process for assessing the overall toxicological risk of acidic drugs.

Discovery of pyrazoles as novel FPR1 antagonists.

A series of pyrazole inhibitors of the human FPR1 receptor have been identified from high throughput screening. The compounds demonstrate potent inhibition in human neutrophils and attractive physicochemical and in vitro DMPK profiles to be of further interest.

Strategies to improve in vivo toxicology outcomes for basic candidate drug molecules.

A valid PLS-DA model to predict attrition in pre-clinical toxicology for basic oral candidate drugs was built. A combination of aromatic/aliphatic balance, flatness, charge distribution and size descriptors helped predict the successful progression of compounds through a wide range of toxicity testing. Eighty percent of an independent test set of marketed post-2000 basic drugs could be successfully classified using the model, indicating useful forward predictivity. The themes within this work provide additional guidance for medicinal design chemists and complement other literature property guidelines.

A highly automated assay for determining the aqueous equilibrium solubility of drug discovery compounds.

Aqueous solubility is an important physicochemical parameter for any potential drug candidate, and high-throughput kinetic assays are frequently used in drug discovery to give an estimate of a compound's aqueous solubility. However, the aqueous solubility data from an equilibrium (thermodynamic) shake-flask technique is considered more relevant, but is slower and more labor intensive to generate. A highly automated aqueous equilibrium solubility shake-flask technique is described and validated on a set of 15 marketed drugs, whose aqueous solubilities cover four orders of magnitude. The assay uses a Tecan Freedom Evo 200 liquid handling robot (Tecan Group Ltd., Männerdorf, Switzerland) with integrated appliances for the transportation, decapping and recapping, and centrifugation of sample tubes. These bespoke automation solutions help overcome the labor intensive steps associated with performing conventional, gold standard, aqueous equilibrium solubility shake-flask measurements, enabling the assay to be used as a primary-wave drug discovery screen.

Lipophilicity of acidic compounds: impact of ion pair partitioning on drug design.

In drug discovery projects the ability to show a relationship between a compound's molecular structure and its pharmacokinetic, in vivo efficacy, or toxicity profile is paramount for the design of better analogues. To aid this understanding the measurement of distribution coefficients at some physiologically relevant pH, for example, log D(7.4), is common practice as they are used as a key descriptor in mathematical models for predicting various biological parameters. Evidence is presented that under typical experimental conditions ion pair partitioning can contribute greatly to log D(7.4) results for acidic compounds; if this is ignored it may compromise data analysis within drug discovery projects where the modulation of lipophilicity is a primary design strategy. The work herein focuses on acidic compounds and reflects the experience of AstraZeneca R&D Charnwood (AZ) where ion pair partitioning contributions can be minimized by the routine measurement of log D(5.5) data. The magnitude of ion pair partitioning contributions to the log D(7.4) measurements of 24 acidic drugs are investigated, and the risks to drug discovery projects that ignore such contributions are discussed. The superiority of measured lipophilicity data over calculated data for a set of AZ proprietary acidic compounds is also presented.

A kinetic method for the determination of plasma protein binding of compounds unstable in plasma: Specific application to enalapril.

Traditional methods for the determination of plasma protein binding (PPB), such as equilibrium dialysis and ultrafiltration, normally operate on a timescale ranging from tens of minutes to several hours and are not suitable for measuring compounds that have significant chemical degradation on this timescale. One such compound is enalapril. Although stable in human plasma enalapril is subject to rapid esterase-catalyzed hydrolysis in rat plasma. A method has been developed which allows the extent of rat PPB of enalapril to be determined from initial rates kinetics of the adsorption of the unstable compound to dextran coated charcoal (DCC). The method has been applied to stable compounds, and the results are consistent with those from traditional equilibrium dialysis experiments. The experimental method is simple to run, requires no specialized equipment, and can potentially be applied to other compounds that show instability in plasma where traditional experimental techniques are unsuitable.

A method for measuring the lipophilicity of compounds in mixtures of 10.

Lipophilicity is an important parameter for any potential drug candidate. Accurate and efficient lipophilicity measurements facilitate the development of high-quality predictive in silico models that support the design of future drugs. Lipophilicity estimates derived from the traditional 1-octanol/water shake flask techniques have been the most widely employed and are therefore the best understood. This technique can be considered to give a good measure of a compound's lipophilicity, albeit slower and more labor intensive to run compared with some other methodologies. Herein is described and validated an efficient 1-octanol/water shake flask technique that has sufficient capacity to be run as a primary screen within the drug discovery process. This is achieved by the simultaneous measurement of the distribution coefficients of mixtures of up to 10 compounds using high-performance liquid chromatography and tandem mass spectrometry. Concerns regarding ion pair partitioning that could result in erroneous results due to interactions between compounds within a mixture are discussed.

The thermodynamics of the partitioning of ionizing molecules between aqueous buffers and phospholipid membranes.

PURPOSE: To study the thermodynamics of partitioning of eight ionising dual D2-recepto beta2-adrenoceptor agonists between vesicles of L-alpha-dimyristoylphosphatidylcholine (DMPC) and aqueous buffers. METHODS: The thermodynamics of partitioning have been studied by isothermal titration calorimetry (ITC). RESULTS: Compounds which are predominantly cationic at pH 7.4 (designated as class 1 compounds) have a more exothermic partitioning than those which are predominantly in the electronically neutral form (designated as class 2 compounds) at pH 7.4, and less positive standard entropies of partitioning. Under acidic conditions (pH 4.0), class compounds 2 (predominantly electronically neutral at pH 7.4) are almost completely cationic and accordingly have a more exothermic partitioning than at pH 7.4. The standard entropies of partitioning also depend on the pH. When the compounds are predominantly cationic, the standard entropy change is less positive (less favourable) than under conditions where the compounds are predominantly electronically neutral. CONCLUSIONS: The observations are consistent with the notion of there being a favourable electrostatic interaction (enthalpically) between the positively charged amino-group of predominantly cationic compounds and the negatively charged phosphate group of the vesicle.

A comparison of physiochemical property profiles of development and marketed oral drugs.

The process of drug discovery applies rigorous selection pressures. Marketed oral drugs will generally possess favorable physiochemical properties with respect to absorption, metabolism, distribution, and clearance. This paper describes a study in which the distributions of physiochemical properties of oral drugs in different phases of clinical development are compared to those already marketed. The aim is to identify the trends in physiochemical properties that favor a drug's successful passage through clinical development and on to the market. Two libraries were created, one of current development oral drugs and one of marketed oral drugs. Statistical analysis of the two showed that the mean molecular weight of orally administered drugs in development decreases on passing through each of the different clinical phases and gradually converges toward the mean molecular weight of marketed oral drugs. It is also clear that the most lipophilic compounds are being discontinued from development.

The influence of nonspecific microsomal binding on apparent intrinsic clearance, and its prediction from physicochemical properties.

The apparent intrinsic clearance of 13 drugs has been determined using rat liver microsomes at three different concentrations of microsomal protein. The kinetics was studied using the in vitro half-life method. The nonspecific binding of these drugs to the microsomes was also studied under the same conditions, except for cofactor removal, using equilibrium dialysis. The intrinsic clearances are shown to be dependent on the microsomal concentration, but are approximately constant when corrected for the extent of nonspecific binding to the microsomes. The large difference between observed intrinsic clearance and unbound intrinsic clearance that exists for some compounds, particularly lipophilic bases, is highlighted. A simple model has been developed for understanding the binding of compounds to microsomes and is demonstrated to accurately predict the extent of microsomal binding at one concentration of microsomes from measurement at another. The binding of a further 25 drugs to rat liver microsomes at a microsomal concentration of 1 mg/ml was also studied, along with measurements of lipophilicity using octanol-water partition coefficients. It is shown that the extent of microsomal binding is correlated with lipophilicity, but that basic compounds show a different behavior to acidic and neutral compounds. Microsomal binding is shown to be best predicted using a model where log P is used for basic compounds, and log D(7.4) is used for acidic and neutral compounds. This model has been developed further so that the extent of binding to microsomes of any given concentration can be estimated purely from a knowledge of lipophilicity and ionization.