Novel 5-HT7 receptor antagonists modulate intestinal immune responses and reduce severity of colitis.

Inflammatory bowel disease (IBD) encompasses several debilitating chronic gastrointestinal (GI) inflammatory disorders, including Crohn's disease and ulcerative colitis. In both conditions, mucosal inflammation is a key clinical presentation associated with altered serotonin (5-hydroxytryptamine or 5-HT) signaling. This altered 5-HT signaling is also found across various animal models of colitis. Of the 14 known receptor subtypes, 5-HT receptor type 7 (5-HT7) is one of the most recently discovered. We previously reported that blocking 5-HT signaling with either a selective 5-HT7 receptor antagonist (SB-269970) or genetic ablation alleviated intestinal inflammation in murine experimental models of colitis. Here, we developed novel antagonists, namely, MC-170073 and MC-230078, which target 5-HT7 receptors with high selectivity. We also investigated the in vivo efficacy of these antagonists in experimental colitis by using dextran sulfate sodium (DSS) and the transfer of CD4+CD45RBhigh T cells to induce intestinal inflammation. Inhibition of 5-HT7 receptor signaling with the antagonists, MC-170073 and MC-230078, ameliorated intestinal inflammation in both acute and chronic colitis models, which was accompanied by lower histopathological damage and diminished levels of proinflammatory cytokines compared with vehicle-treated controls. Together, the data reveal that the pharmacological inhibition of 5-HT7 receptors by these selective antagonists ameliorates the severity of colitis across various experimental models and may, in the future, serve as a potential treatment option for patients with IBD. In addition, these findings support that 5-HT7 is a viable therapeutic target for IBD.NEW & NOTEWORTHY This study demonstrates that the novel highly selective 5-HT7 receptor antagonists, MC-170073 and MC-230078, significantly alleviated the severity of colitis across models of experimental colitis. These findings suggest that inhibition of 5-HT7 receptor signaling by these new antagonists may serve as an alternative mode of treatment to diminish symptomology in those with inflammatory bowel disease.

First-in-Human Phase 1b Trial of Quinacrine Plus Capecitabine in Patients With Refractory Metastatic Colorectal Cancer.

BACKGROUND: Quinacrine plus a fluoropyrimidine has in vivo efficacy against metastatic colorectal cancer (mCRC). This phase 1b trial evaluated the combination of quinacrine plus capecitabine in patients with treatment-refractory mCRC. PATIENTS AND METHODS: Using a modified Simon accelerated titration design, adults with treatment-refractory mCRC were treated with capecitabine 1000 mg/m2 twice daily for 14/21-day cycle, and escalating doses of quinacrine 100 mg daily, 100 mg twice daily, and 200 mg twice daily for 21 days. The primary endpoint was identifying the maximum tolerated dose, determining tolerability and safety. In an expansion cohort, it was overall response rate and time to tumor progression (TTP). RESULTS: Ten patients (median age of 60 years) were treated in phase 1b. The first 2 quinacrine dosing levels were well tolerated. Dose-limiting toxicities were seen in 3 patients treated with quinacrine 200 mg twice daily. Five additional patients tolerated quinacrine 100 mg twice daily without further dose-limiting toxicities, thus establishing the maximum tolerated dose. Seven additional expansion-cohort patients enrolled onto the study before quinacrine manufacturing ceased within the United States. Five patients experienced stable disease, 1 partial response, and 10 disease progression. Median TTP overall was 2.12 months and median overall survival 5.22 months for the 17 patients. CONCLUSION: Capecitabine and quinacrine can be safely administered at the maximum tolerated dose of capecitabine 1000 mg/m2 by mouth twice daily on days 1-14 and quinacrine 100 mg by mouth twice daily on days 1-21 of a 21-day cycle in mCRC patients. Although the expansion study was halted early, TTP was in line with other studies of refractory mCRC, suggesting activity of this regimen in heavily pretreated patients.

Design, synthesis, and evaluation of N-(4-(4-phenyl piperazin-1-yl)butyl)-4-(thiophen-3-yl)benzamides as selective dopamine D3 receptor ligands.

As part of our on-going effort to explore the role of dopamine receptors in drug addiction and identify potential novel therapies for this condition, we have a identified a series of N-(4-(4-phenyl piperazin-1-yl)butyl)-4-(thiophen-3-yl)benzamide D3 ligands. Members of this class are highly selective for D3 versus D2, and we have identified two compounds (13g and 13r) whose rat in vivo IV pharmacokinetic properties that indicate that they are suitable for assessment in in vivo efficacy models of substance use disorders.

Intracellular Unbound Atorvastatin Concentrations in the Presence of Metabolism and Transport.

Accurate prediction of drug target activity and rational dosing regimen design require knowledge of drug concentrations at the target. It is important to understand the impact of processes such as membrane permeability, partitioning, and active transport on intracellular drug concentrations. The present study aimed to predict intracellular unbound atorvastatin concentrations and characterize the effect of enzyme-transporter interplay on these concentrations. Single-pass liver perfusion studies were conducted in rats using atorvastatin (ATV, 1 µM) alone at 4°C and at 37°C in presence of rifampin (RIF, 20 µM) and 1-aminobenzotriazole (ABT, 1 mM), separately and in combination. The unbound intracellular ATV concentration was predicted with a five-compartment explicit membrane model using the parameterized diffusional influx clearance, active basolateral uptake clearance, and metabolic clearance. Chemical inhibition of uptake and metabolism at 37°C proved to be better controls relative to studies at 4°C. The predicted unbound intracellular concentration at the end of the 50-minute perfusion in the +ABT , +ABT+RIF, and the ATV-only groups was 6.5 µM, 0.58 µM, and 5.14 µM, respectively. The predicted total liver concentrations and amount recovered in bile were within 0.94-1.3 fold of the observed value in all groups. The fold difference in total liver concentration did not always extrapolate to the fold difference in predicted unbound concentration across groups. Together, these results support the use of compartmental modeling to predict intracellular concentrations in dynamic organ-based systems. These predictions can provide insight into the role of uptake transporters and metabolizing enzymes in determining drug tissue concentrations.

Heterocyclic chalcone activators of nuclear factor (erythroid-derived 2)-like 2 (Nrf2) with improved in vivo efficacy.

Nrf2 activators represent a good drug target for designing agents to treat diseases associated with oxidative stress. Building upon previous work, we designed and prepared a series of heterocyclic chalcone-based Nrf2 activators with reduced lipophilicity and, in some cases, greater in vitro potency compared to the respective carbocyclic scaffold. These changes resulted in enhanced oral bioavailability and a superior pharmacodynamic effect in vivo.

Predicting intrinsic clearance for drugs and drug candidates metabolized by aldehyde oxidase.

Metabolism by aldehyde oxidase (AO) has been responsible for a number of drug failures in clinical trials. The main reason is the clearance values for drugs metabolized by AO are underestimated by allometric scaling from preclinical species. Furthermore, in vitro human data also underestimates clearance. We have developed the first in silico models to predict both in vitro and in vivo human intrinsic clearance for 8 drugs with just two chemical descriptors. These models explain a large amount of the variance in the data using two computational estimates of the electronic and steric features of the reaction. The in vivo computational models for human metabolism are better than in vitro preclinical animal testing at predicting human intrinsic clearance. Thus, it appears that AO is amenable to computational prediction of rates, which may be used to guide drug discovery, and predict pharmacokinetics for clinical trials.

Impact of pH on plasma protein binding in equilibrium dialysis.

Many pharmacokinetic analyses require unbound plasma concentrations, including prediction of clearance, volume of distribution, drug-drug interactions, brain uptake analysis, etc. It is most often more convenient to measure the total drug concentration in plasma rather than the unbound drug concentration. To arrive at unbound plasma concentrations, separate in vitro determinations of the plasma protein binding of a drug are usually carried out in serum or in plasma, and the plasma pharmacokinetic results are then mathematically adjusted by this fraction unbound ( f u,p). Plasma protein binding or the drug fraction unbound in plasma ( f u,p) is known to be affected by protein, drug, free fatty acid concentrations, lipoprotein partitioning, temperature, pH, and the presence or absence of other drugs/displacing agents within plasma samples. Errors in f u,p determination caused by lack of adequate pH control in newer assay formats for plasma protein binding (e.g., 96-well equilibrium thin walled polypropylene dialysis plates) will have significant drug-specific impact on these pharmacokinetic calculations. Using a diverse set of 55 drugs and a 96-well equilibrium dialysis plate format, the effect of variable pH during equilibrium dialysis experiments on measured values of f u,p was examined. Equilibrium dialysis of human plasma against Dulbecco's phosphate buffered saline at 37 degrees C under an air or 10% CO 2 atmosphere for 22 h resulted in a final pH of approximately 8.7 and 7.4, respectively. The ratio of f u,p at pH 7.4 (10% CO 2) vs pH 8.7 (air) was >or=2.0 for 40% of the 55 compounds tested. Only one of the 55 compounds tested had a ratio <0.9. Select compounds were further examined in rat and dog plasma. In addition, physicochemical properties were calculated for all compounds using ACD/Labs software or Merck in-house software and compared to plasma protein binding results. Changes in plasma protein binding due to pH increases which occurred during the equilibrium dialysis experiment were not species specific but were drug-specific, though nonpolar, cationic compounds had a higher likely hood of displaying pH-dependent binding. These studies underscore the importance of effectively controlling pH in plasma protein binding studies.

Use of density functional calculations to predict the regioselectivity of drugs and molecules metabolized by aldehyde oxidase.

Aldehyde oxidase is a molybdenum hydroxylase that catalyzes the oxidation of aldehydes and nitrogen-containing heterocycles. The enzyme plays a dual role in the metabolism of physiologically important endogenous compounds and the biotransformation of xenobiotics. Using density functional theory methods, geometry optimization of tetrahedral intermediates of drugs and druglike compounds was examined to predict the likely metabolites of aldehyde oxidase. The calculations suggest that the lowest energy tetrahedral intermediate resulting from the initial substrate corresponds to the observed metabolite >or=90% of the time. Additional calculations were performed on a series of heterocyclic compounds where the products resulting from metabolism by xanthine oxidase and aldehyde oxidase differ in many instances. Again, the lowest energy tetrahedral intermediate corresponded to the observed product of aldehyde oxidase metabolism >or=90% for the compounds examined, while the observed products of xanthine oxidase were not well predicted.

Empirical regioselectivity models for human cytochromes P450 3A4, 2D6, and 2C9.

Cytochromes P450 3A4, 2D6, and 2C9 metabolize a large fraction of drugs. Knowing where these enzymes will preferentially oxidize a molecule, the regioselectivity, allows medicinal chemists to plan how best to block its metabolism. We present QSAR-based regioselectivity models for these enzymes calibrated against compiled literature data of drugs and drug-like compounds. These models are purely empirical and use only the structures of the substrates, in contrast to those models that simulate a specific mechanism like hydrogen radical abstraction, and/or use explicit models of active sites. Our most predictive models use three substructure descriptors and two physical property descriptors. Descriptor importances from the random forest QSAR method show that other factors than the immediate chemical environment and the accessibility of the hydrogen affect regioselectivity in all three isoforms. The cross-validated predictions of the models are compared to predictions from our earlier mechanistic model (Singh et al. J. Med. Chem. 2003, 46, 1330-1336) and predictions from MetaSite (Cruciani et al. J. Med. Chem. 2005, 48, 6970-6979).

Inhibition of recombinant cytochrome P450 isoforms 2D6 and 2C9 by diverse drug-like molecules.

The affinities of a diverse set of 500 drug-like molecules to cytochrome P450 isoforms 2C9 and 2D6 were measured using recombinant expressed enzyme. The dose-response curve of each compound was fitted with a series of equations representing typical or various types of atypical kinetics. Atypical kinetics was identified where the Akaike Information Criterion, plus other criteria, suggested the kinetics was more complex than expected for a Michaelis-Menten model. Approximately 20% of the compounds were excluded due to poor solubility, and approximately 15% were excluded due to fluorescence interference. Of the remaining compounds, roughly half were observed to bind with an affinity of 200 microM or lower for each of the two isoforms. Atypical kinetics was observed in 18% of the compounds that bind to cytochrome 2C9, but less than 2% for 2D6. The resulting collection of competitive inhibitors and inactive compounds were analyzed for trends in binding affinity. For CYP2D6, a clear relationship between polar surface area and charge was observed, with the most potent inhibitors having a formal positive charge and a low percent polar surface area. For CYP2C9, no clear trend between activity and physicochemical properties could be seen for the group as a whole; however, certain classes of compounds have altered frequencies of activity and atypical kinetics.

Computational models for cytochrome P450: a predictive electronic model for aromatic oxidation and hydrogen atom abstraction.

Experimental observations suggest that electronic characteristics play a role in the rates of substrate oxidation for cytochrome P450 enzymes. For example, the tendency for oxidation of a certain functional group generally follows the relative stability of the radicals that are formed (e.g., N-dealkylation > O-dealkylation > 2 degrees carbon oxidation > 1 degree carbon oxidation). In addition, results show that useful correlations between the rates of product formation can be developed using electronic models. In this article, we attempt to determine whether a combined computational model for aromatic and aliphatic hydroxylation can be developed. Toward this goal, we used a combination of experimental data and semiempirical molecular orbital calculations to predicted activation energies for aromatic and aliphatic hydroxylation. The resulting model extends the predictive capacity of our previous aliphatic hydroxylation model to include the second most important group of oxidations, aromatic hydroxylation. The combined model can account for about 83% of the variance in the data for the 20 compounds in the training set and has an error of about 0.7 kcal/mol.