A high-throughput cell-based method to predict the unbound drug fraction in the brain

Antidepressants enter cells, organelles, and membranes

We begin by summarizing several examples of antidepressants whose therapeutic actions begin when they encounter their targets in the cytoplasm or in the lumen of an organelle. These actions contrast with the prevailing view that most neuropharmacological actions begin when drugs engage their therapeutic targets at extracellular binding sites of plasma membrane targets-ion channels, receptors, and transporters. We review the chemical, pharmacokinetic, and pharmacodynamic principles underlying the movements of drugs into subcellular compartments. We note the relationship between protonation-deprotonation events and membrane permeation of antidepressant drugs. The key properties relate to charge and hydrophobicity/lipid solubility, summarized by the parameters LogP, pKa, and LogDpH7.4. The classical metric, volume of distribution (Vd), is unusually large for some antidepressants and has both supracellular and subcellular components. A table gathers structures, LogP, PKa, LogDpH7.4, and Vd data and/or calculations for most antidepressants and antidepressant candidates. The subcellular components, which can now be measured in some cases, are dominated by membrane binding and by trapping in the lumen of acidic organelles. For common antidepressants, such as selective serotonin reuptake inhibitors (SSRIs) and serotonin/norepinephrine reuptake inhibitors (SNRIs), the target is assumed to be the eponymous reuptake transporter(s), although in fact the compartment of target engagement is unknown. We review special aspects of the pharmacokinetics of ketamine, ketamine metabolites, and other rapidly acting antidepressants (RAADs) including methoxetamine and scopolamine, psychedelics, and neurosteroids. Therefore, the reader can assess properties that markedly affect a drug's ability to enter or cross membranes-and therefore, to interact with target sites that face the cytoplasm, the lumen of organelles, or a membrane. In the current literature, mechanisms involving intracellular targets are termed "location-biased actions" or "inside-out pharmacology". Hopefully, these general terms will eventually acquire additional mechanistic details.

An LC-ESI-MS/MS method for determination of ondansetron in low-volume plasma and cerebrospinal fluid: Method development, validation, and clinical application

Ondansetron is used in clinical settings as an antiemetic drug. Although the animal studies showed its potential effectiveness also in treating neuropathic pain, the results from humans are inconclusive. The lack of efficacy of ondansetron in a subset of patients might be due to the overexpression of P-glycoprotein, which could result in low concentrations of ondansetron in the central nervous system (CNS). A surrogate of the CNS exposure might be drug concentration in the cerebrospinal fluid (CSF), especially in humans, as assessing the drug disposition directly in the patient's brain would be challenging. The study aimed to develop a sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to determine concentrations of ondansetron in human K3EDTA plasma and CSF. Ondansetron was extracted from biological matrices by liquid-liquid extraction. The quantification was performed on a Sciex QTRAP 6500+ mass spectrometer with labeled ondansetron as an internal standard. The calibration range was 0.25-350 ng/mL in plasma and 0.025-100 ng/mL in CSF; for both matrices, 25 µL of samples was required for the assays. The method was validated according to the FDA and EMA guidelines and showed acceptable results. A pilot study confirmed its suitability for clinical samples: after 4-16 mg of intravenous ondansetron, the determined concentrations in plasma were 1.22-235.90 ng/mL, while in CSF - 0.018-11.93 ng/mL. In conclusion, the developed method fulfilled all validation requirements and can be applied to pharmacokinetic studies assessing the CNS ondansetron exposure in humans. The method's advantages, such as a low volume of matrix and a wide calibration range, support its use in a study in which rich sampling and various drug doses are expected.

In Silico Analysis, Anticonvulsant Activity, and Toxicity Evaluation of Schisandrin B in Zebrafish Larvae and Mice

The aim of this study is to evaluate the anticonvulsant potential of schisandrin B, a main ingredient of Schisandra chinensis extracts. Schisandrin B showed anticonvulsant activity in the zebrafish larva pentylenetetrazole acute seizure assay but did not alter seizure thresholds in the intravenous pentylenetetrazole test in mice. Schisandrin B crosses the blood-brain barrier, which we confirmed in our in silico and in vivo analyses; however, the low level of its unbound fraction in the mouse brain tissue may explain the observed lack of anticonvulsant activity. Molecular docking revealed that the anticonvulsant activity of the compound in larval zebrafish might have been due to its binding to a benzodiazepine site within the GABAA receptor and/or the inhibition of the glutamate NMDA receptor. Although schisandrin B showed a beneficial anticonvulsant effect, toxicological studies revealed that it caused serious developmental impairment in zebrafish larvae, underscoring its teratogenic properties. Further detailed studies are needed to precisely identify the properties, pharmacological effects, and safety of schisandrin B.

Physiologically Based Pharmacokinetic Model To Predict Metoprolol Disposition in Healthy and Disease Populations

The evolution in the development of drugs has increased the popularity of physiologically based pharmacokinetic (PBPK) models. This study seeks to assess the PK of metoprolol in populations with healthy, chronic kidney disease (CKD), and acute myocardial infarction (AMI) conditions by developing and evaluating PBPK models. An extensive literature review for identifying and selecting plasma concentration vs time profile data and other drug-related parameters was undergone for their integration into the PK-Sim program followed by the development of intravenous, oral, and diseased models. The developed PBPK model of metoprolol was then evaluated using the visual predictive checks, mean observed/predicted ratios (Robs/pre), and average fold error for all PK parameters, i.e., the area under the curve (AUC), maximal plasma concentration, and clearance. The model evaluation depicted that none of the PK parameters were out of the allowed range (2-fold error) in the case of the mean Robs/pre ratios. The model anticipations were executed to determine the influence of diseases on unbound and total AUC after the application of metoprolol in healthy, moderate, and severe CKD. The dosage reductions were also suggested based on differences in unbound and total AUC in different stages of CKD. The developed PBPK models have successfully elaborated the PK changes of metoprolol occurring in healthy individuals and those with renal and heart diseases (CKD & AMI), which may be fruitful for dose optimization among diseased patients.

Selective Serotonin Reuptake Inhibitors within Cells: Temporal Resolution in Cytoplasm, Endoplasmic Reticulum, and Membrane

Selective serotonin reuptake inhibitors (SSRIs) are the most prescribed treatment for individuals experiencing major depressive disorder. The therapeutic mechanisms that take place before, during, or after SSRIs bind the serotonin transporter (SERT) are poorly understood, partially because no studies exist on the cellular and subcellular pharmacokinetic properties of SSRIs in living cells. We studied escitalopram and fluoxetine using new intensity-based, drug-sensing fluorescent reporters targeted to the plasma membrane, cytoplasm, or endoplasmic reticulum (ER) of cultured neurons and mammalian cell lines. We also used chemical detection of drug within cells and phospholipid membranes. The drugs attain equilibrium in neuronal cytoplasm and ER at approximately the same concentration as the externally applied solution, with time constants of a few s (escitalopram) or 200-300 s (fluoxetine). Simultaneously, the drugs accumulate within lipid membranes by ≥18-fold (escitalopram) or 180-fold (fluoxetine), and possibly by much larger factors. Both drugs leave cytoplasm, lumen, and membranes just as quickly during washout. We synthesized membrane-impermeant quaternary amine derivatives of the two SSRIs. The quaternary derivatives are substantially excluded from membrane, cytoplasm, and ER for >2.4 h. They inhibit SERT transport-associated currents sixfold or 11-fold less potently than the SSRIs (escitalopram or fluoxetine derivative, respectively), providing useful probes for distinguishing compartmentalized SSRI effects. Although our measurements are orders of magnitude faster than the therapeutic lag of SSRIs, these data suggest that SSRI-SERT interactions within organelles or membranes may play roles during either the therapeutic effects or the antidepressant discontinuation syndrome.SIGNIFICANCE STATEMENT Selective serotonin reuptake inhibitors stabilize mood in several disorders. In general, these drugs bind to SERT, which clears serotonin from CNS and peripheral tissues. SERT ligands are effective and relatively safe; primary care practitioners often prescribe them. However, they have several side effects and require 2-6 weeks of continuous administration until they act effectively. How they work remains perplexing, contrasting with earlier assumptions that the therapeutic mechanism involves SERT inhibition followed by increased extracellular serotonin levels. This study establishes that two SERT ligands, fluoxetine and escitalopram, enter neurons within minutes, while simultaneously accumulating in many membranes. Such knowledge will motivate future research, hopefully revealing where and how SERT ligands engage their therapeutic target(s).

Clinical Pharmacokinetics of Metoprolol: A Systematic Review

BACKGROUND

Metoprolol is recommended for therapeutic use in multiple cardiovascular conditions, thyroid crisis, and circumscribed choroidal hemangioma. A detailed systematic review on the metoprolol literature would be beneficial to assess all pharmacokinetic parameters in humans and their respective effects on patients with hepatic, renal, and cardiovascular diseases. This review combines all the pharmacokinetic data on metoprolol from various accessible studies, which may assist in clinical decision making.

METHODOLOGY

The Google Scholar and PubMed databases were searched to screen articles associated with the clinical pharmacokinetics of metoprolol. The comprehensive literature search retrieved 41 articles including data on plasma concentration-time profiles after intravenous and oral (immediate-release, controlled-release, slow-release, or extended-release) routes of administration, and at least one pharmacokinetic parameter was reported in all studies included.

RESULTS

Out of 41 retrieved articles, six were after intravenous and 12 were after oral administration in healthy individuals. The oral studies depict a dose-dependent increase in maximum plasma concentration (C_max), time to reach maximum plasma concentration (T_max), and area under the concentration-time curve (AUC). Two studies were conducted in R- and S-enantiomers, in which one study reported the gender differences, depicting greater C_max and AUC among women, whereas in another study S-metoprolol was found to have higher values of C_max, T_max, and AUC in comparison with R-metoprolol. Results in different diseases depicted that after IV administration of 20 mg, patients with renal impairment showed an increase in clearance (CL) (60 L/h vs 48 L/h) compared with healthy subjects, whereas a decrease in CL (36.6 ± 7.8 L/h vs 48 ± 6.6 L/h) was seen in patients with hepatic cirrhosis at a similar dose. In comparison with a single oral dose following administration of 15 mg IV in three divided doses, patients having an acute myocardial infarction (AMI) showed an increase in C_max (823 nmol/L vs 248 nmol/L) at a steady state. Twenty different studies have reported significant changes in CL, C_max, and AUC of metoprolol when it is co-administered with other drugs. One study has reported a drug-food interaction for metoprolol but no significant changes were seen in the C_max and AUC.

CONCLUSION

This review summarizes all the pharmacokinetic parameters of metoprolol after pooling up-to-date data from all the studies available. The summarized pharmacokinetic data presented in this review can assist in developing and evaluating pharmacokinetic models of metoprolol. Moreover, this data can provide practitioners with an insight into dosage adjustments among the diseased populations and can assist in preventing potential adverse drug reactions. This review can also help avoid side effects and drug-drug interactions.

Non-metabolic functions of phosphofructokinase-1 orchestrate tumor cellular invasion and genome maintenance under bevacizumab therapy

BACKGROUND

Glioblastoma (GBM) is a highly lethal malignancy for which neoangiogenesis serves as a defining hallmark. The anti-VEGF antibody, bevacizumab, has been approved for the treatment of recurrent GBM, but resistance is universal.

METHODS

We analyzed expression data of GBM patients treated with bevacizumab to discover potential resistance mechanisms. Patient-derived xenografts (PDXs) and cultures were interrogated for effects of phosphofructokinase-1, muscle isoform (PFKM) loss on tumor cell motility, migration, and invasion through genetic and pharmacologic targeting.

RESULTS

We identified PFKM as a driver of bevacizumab resistance. PFKM functions dichotomize based on subcellular location: cytosolic PFKM interacted with KIF11, a tubular motor protein, to promote tumor invasion, whereas nuclear PFKM safeguarded genomic stability of tumor cells through interaction with NBS1. Leveraging differential transcriptional profiling, bupivacaine phenocopied genetic targeting of PFKM, and enhanced efficacy of bevacizumab in preclinical GBM models in vivo.

CONCLUSION

PFKM drives novel molecular pathways in GBM, offering a translational path to a novel therapeutic paradigm.

Inhibition of prolyl oligopeptidase: A promising pathway to prevent the progression of age-related macular degeneration

Dry age-related macular degeneration (AMD) is a currently untreatable vision threatening disease. Impaired proteasomal clearance and autophagy in the retinal pigment epithelium (RPE) and subsequent photoreceptor damage are connected with dry AMD, but detailed pathophysiology is still unclear. In this paper, we discover inhibition of cytosolic protease, prolyl oligopeptidase (PREP), as a potential pathway to treat dry AMD. We showed that PREP inhibitor exposure induced autophagy in the RPE cells, shown by increased LC3-II levels and decreased p62 levels. PREP inhibitor treatment increased total levels of autophagic vacuoles in the RPE cells. Global proteomics was used to examine the phenotype of a commonly used cell model displaying AMD characteristics, oxidative stress and altered protein metabolism, in vitro. These RPE cells displayed induced protein aggregation and clear alterations in macromolecule metabolism, confirming the relevance of the cell model. Differences in intracellular target engagement of PREP inhibitors were observed with cellular thermal shift assay (CETSA). These differences were explained by intracellular drug exposure (the unbound cellular partition coefficient, Kp_uu). Importantly, our data is in line with previous observations regarding the discrepancy between PREP's cleaving activity and outcomes in autophagy. This highlights the need to further explore PREP's role in autophagy so that more effective compounds can be designed to battle diseases in which autophagy induction is needed. The present work is the first report investigating the PREP pathway in the RPE and we predict that the PREP inhibitors can be further optimized for treatment of dry AMD.

Model-based Target Pharmacology Assessment (mTPA): An Approach Using PBPK/PD Modeling and Machine Learning to Design Medicinal Chemistry and DMPK Strategies in Early Drug Discovery

The optimal pharmacokinetic (PK) required for a drug candidate to elicit efficacy is highly dependent on the targeted pharmacology, a relationship that is often not well characterized during early phases of drug discovery. Generic assumptions around PK and potency risk misguiding screening and compound design toward nonoptimal absorption, distribution, metabolism, and excretion (ADME) or molecular properties and ultimately may increase attrition as well as hit-to-lead and lead optimization timelines. The present work introduces model-based target pharmacology assessment (mTPA), a computational approach combining physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling, sensitivity analysis, and machine learning (ML) to elucidate the optimal combination of PK, potency, and ADME specific for the targeted pharmacology. Examples using frequently encountered PK/PD relationships are presented to illustrate its application, and the utility and benefits of deploying such an approach to guide early discovery efforts are discussed.

Physiologically Based Pharmacokinetic Modeling of Metoprolol Enantiomers and α-Hydroxymetoprolol to Describe CYP2D6 Drug-Gene Interactions

The beta-blocker metoprolol (the sixth most commonly prescribed drug in the USA in 2017) is subject to considerable drug–gene interaction (DGI) effects caused by genetic variations of the CYP2D6 gene. CYP2D6 poor metabolizers (5.7% of US population) show approximately five-fold higher metoprolol exposure compared to CYP2D6 normal metabolizers. This study aimed to develop a whole-body physiologically based pharmacokinetic (PBPK) model to predict CYP2D6 DGIs with metoprolol. The metoprolol (R)- and (S)-enantiomers as well as the active metabolite α-hydroxymetoprolol were implemented as model compounds, employing data of 48 different clinical studies (dosing range 5–200 mg). To mechanistically describe the effect of CYP2D6 polymorphisms, two separate metabolic CYP2D6 pathways (α-hydroxylation and O-demethylation) were incorporated for both metoprolol enantiomers. The good model performance is demonstrated in predicted plasma concentration–time profiles compared to observed data, goodness-of-fit plots, and low geometric mean fold errors of the predicted AUC_last (1.27) and C_max values (1.23) over all studies. For DGI predictions, 18 out of 18 DGI AUC_last ratios and 18 out of 18 DGI C_max ratios were within two-fold of the observed ratios. The newly developed and carefully validated model was applied to calculate dose recommendations for CYP2D6 polymorphic patients and will be freely available in the Open Systems Pharmacology repository.

In vitro binding affinity vs. in vivo site occupancy: A PET study of four diastereomers of dihydrotetrabenazine (DTBZ) in monkey brain

INTRODUCTION

In vivo imaging methods such as Positron Emission Tomography (PET) can be used to examine the relationship between in vitro binding affinity and in vivo occupancy of binding sites in the brain for new drug candidates. In this study, PET imaging in monkey brain was used to evaluate that correlation for a set of four diastereomers of the compound dihydrotetrabenazine (DTBZ), the pharmacologically active metabolite of the drug tetrabenazine.

METHODS

PET studies of DTBZ diastereomers were completed in a single monkey brain. In vivo occupancies (ED₅₀) were estimated using multiple drug doses and the vesicular monoamine transporter 2 specific radioligand (+)-α-[¹¹C] DTBZ, employing a test-retest sequence of control PET scan, drug administration and a second PET scan completed on a single day.

RESULTS

DTBZ has three chiral carbon centers and eight possible stereoisomers, and in vivo occupancy of the target site VMAT2 was observed only for the four diastereomers of DTBZ having the 11bR absolute configuration. The estimated in vivo occupancies (ED₅₀ values from 0.023 to >3.15 mg/kg) correlated well (R² = 0.95) with the in vitro binding affinities (K_i values of 4 to 600 nM for the VMAT2), and an even better correlation (R² = 0.99) was found for the three isomers with in vitro binding affinities <100 nM.

CONCLUSIONS

If the physiochemical (MW, log P, pKa) or physiological (metabolism, transport, protein binding) properties of a set of drug stereoisomers are considered similar, the binding affinities determined from in vitro assays may predict the in vivo occupancies of the target binding site in the monkey brain.

A Cell-Free Approach Based on Phospholipid Characterization for Determination of the Cell Specific Unbound Drug Fraction (fu,cell)

Purpose

The intracellular fraction of unbound compound (f_u,cell) is an important parameter for accurate prediction of drug binding to intracellular targets. f_u,cell is the result of a passive distribution process of drug molecules partitioning into cellular structures. Initial observations in our laboratory showed an up to 10-fold difference in the f_u,cell of a given drug for different cell types. We hypothesized that these differences could be explained by the phospholipid (PL) composition of the cells, since the PL cell membrane is the major sink of unspecific drug binding. Therefore, we determined the f_u,cell of 19 drugs in cell types of different origin.

Method

The cells were characterized for their total PL content and we used mass spectrometric PL profiling to delineate the impact of each of the four major cellular PL subspecies: phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS) and phosphatidylinositol (PI). The cell-based experiments were compared to cell-free experiments that used beads covered by PL bilayers consisting of the most abundant PL subspecies.

Results

PC was found to give the largest contribution to the drug binding. Improved correlations between the cell-based and cell-free assays were obtained when affinities to all four major PL subspecies were considered. Together, our data indicate that f_u,cell is influenced by PL composition of cells.

Conclusion

We conclude that cellular PL composition varies between cell types and that cell-specific mixtures of PLs can replace cellular assays for determination of f_u,cell as a rapid, small-scale assay covering a broad dynamic range.

Graphical Abstract

Impact of Intracellular Concentrations on Metabolic Drug-Drug Interaction Studies

Accurate prediction of drug-drug interactions (DDI) is a challenging task in drug discovery and development. It requires determination of enzyme inhibition in vitro which is highly system-dependent for many compounds. The aim of this study was to investigate whether the determination of intracellular unbound concentrations in primary human hepatocytes can be used to bridge discrepancies between results obtained using human liver microsomes and hepatocytes. Specifically, we investigated if Kp_uu could reconcile differences in CYP enzyme inhibition values (K_i or IC₅₀). Firstly, our methodology for determination of Kp_uu was optimized for human hepatocytes, using four well-studied reference compounds. Secondly, the methodology was applied to a series of structurally related CYP2C9 inhibitors from a Roche discovery project. Lastly, the Kp_uu values of three commonly used CYP3A4 inhibitors—ketoconazole, itraconazole, and posaconazole—were determined and compared to compound-specific hepatic enrichment factors obtained from physiologically based modeling of clinical DDI studies with these three compounds. Kp_uu obtained in suspended human hepatocytes gave good predictions of system-dependent differences in vitro. The Kp_uu was also in fair agreement with the compound-specific hepatic enrichment factors in DDI models and can therefore be used to improve estimations of enrichment factors in physiologically based pharmacokinetic modeling.

Improved predictions of time-dependent drug-drug interactions by determination of cytosolic drug concentrations

The clinical impact of drug-drug interactions based on time-dependent inhibition of cytochrome P450 (CYP) 3A4 has often been overpredicted, likely due to use of improper inhibitor concentration estimates at the enzyme. Here, we investigated if use of cytosolic unbound inhibitor concentrations could improve predictions of time-dependent drug-drug interactions. First, we assessed the inhibitory effects of ten time-dependent CYP3A inhibitors on midazolam 1′-hydroxylation in human liver microsomes. Then, using a novel method, we determined the cytosolic bioavailability of the inhibitors in human hepatocytes, and used the obtained values to calculate their concentrations at the active site of the enzyme, i.e. the cytosolic unbound concentrations. Finally, we combined the data in mechanistic static predictions, by considering different combinations of inhibitor concentrations in intestine and liver, including hepatic concentrations corrected for cytosolic bioavailability. The results were then compared to clinical data. Compared to no correction, correction for cytosolic bioavailability resulted in higher accuracy and precision, generally in line with those obtained by more demanding modelling. The best predictions were obtained when the inhibition of hepatic CYP3A was based on unbound maximal inhibitor concentrations corrected for cytosolic bioavailability. Our findings suggest that cytosolic unbound inhibitor concentrations improves predictions of time-dependent drug-drug interactions for CYP3A.

Advancing Predictions of Tissue and Intracellular Drug Concentrations Using In Vitro, Imaging and Physiologically Based Pharmacokinetic Modeling Approaches

This white paper examines recent progress, applications, and challenges in predicting unbound and total tissue and intra/subcellular drug concentrations using in vitro and preclinical models, imaging techniques, and physiologically based pharmacokinetic (PBPK) modeling. Published examples, regulatory submissions, and case studies illustrate the application of different types of data in drug development to support modeling and decision making for compounds with transporter-mediated disposition, and likely disconnects between tissue and systemic drug exposure. The goals of this article are to illustrate current best practices and outline practical strategies for selecting appropriate in vitro and in vivo experimental methods to estimate or predict tissue and plasma concentrations, and to use these data in the application of PBPK modeling for human pharmacokinetic (PK), efficacy, and safety assessment in drug development.

Prediction of intracellular exposure bridges the gap between target- and cell-based drug discovery

Inadequate target exposure is a major cause of high attrition in drug discovery. Here, we show that a label-free method for quantifying the intracellular bioavailability (F_ic) of drug molecules predicts drug access to intracellular targets and hence, pharmacological effect. We determined F_ic in multiple cellular assays and cell types representing different targets from a number of therapeutic areas, including cancer, inflammation, and dementia. Both cytosolic targets and targets localized in subcellular compartments were investigated. F_ic gives insights on membrane-permeable compounds in terms of cellular potency and intracellular target engagement, compared with biochemical potency measurements alone. Knowledge of the amount of drug that is locally available to bind intracellular targets provides a powerful tool for compound selection in early drug discovery.

Intracellular drug bioavailability: a new predictor of system dependent drug disposition

Intracellular drug exposure is influenced by cell- and tissue-dependent expression of drug-transporting proteins and metabolizing enzymes. Here, we introduce the concept of intracellular bioavailability (F_ic) as the fraction of extracellular drug available to bind intracellular targets, and we assess how F_ic is affected by cellular drug disposition processes. We first investigated the impact of two essential drug transporters separately, one influx transporter (OATP1B1; SLCO1B1) and one efflux transporter (P-gp; ABCB1), in cells overexpressing these proteins. We showed that OATP1B1 increased F_ic of its substrates, while P-gp decreased F_ic. We then investigated the impact of the concerted action of multiple transporters and metabolizing enzymes in freshly-isolated human hepatocytes in culture configurations with different levels of expression and activity of these proteins. We observed that F_ic was up to 35-fold lower in the configuration with high expression of drug-eliminating transporters and enzymes. We conclude that F_ic provides a measurement of the net impact of all cellular drug disposition processes on intracellular bioavailable drug levels. Importantly, no prior knowledge of the involved drug distribution pathways is required, allowing for high-throughput determination of drug access to intracellular targets in highly defined cell systems (e.g., single-transporter transfectants) or in complex ones (including primary human cells).

Identification of Triazolothiadiazoles as Potent Inhibitors of the dCTP Pyrophosphatase 1

The dCTP pyrophosphatase 1 (dCTPase) is involved in the regulation of the cellular dNTP pool and has been linked to cancer progression. Here we report on the discovery of a series of 3,6-disubstituted triazolothiadiazoles as potent dCTPase inhibitors. Compounds 16 and 18 display good correlation between enzymatic inhibition and target engagement, together with efficacy in a cellular synergy model, deeming them as a promising starting point for hit-to-lead development.

Reliability of In Vitro and In Vivo Methods for Predicting the Effect of P-Glycoprotein on the Delivery of Antidepressants to the Brain

As the effect of P-glycoprotein (P-gp) transport on antidepressant delivery has been extensively evaluated using in vitro cellular and in vivo rodent models, an increasing number of publications have addressed the effect of P-gp in limiting brain penetration of antidepressants and causing treatment-resistant depression in current clinical therapies. However, contradictory results have been observed in different systems. It is of vital importance to understand the potential for drug interactions related to P-gp at the blood-brain barrier (BBB), and whether coadministration of a P-gp inhibitor together with an antidepressant is a good clinical strategy for dosing of patients with treatment-resistant depression. In this review, the complicated construction of the BBB, the transport mechanisms for compounds that cross the BBB, and the basic characteristics of antidepressants are illustrated. Further, the reliability of different systems related to antidepressant brain delivery, including in vitro bidirectional transport cell lines, in vivo Mdr1 knockout mice, and chemical inhibition studies in rodents are analyzed, supporting a low possibility that P-gp affects currently marketed antidepressants when these results are extrapolated to the human BBB. These findings can also be applied to other central nervous system drugs.

Early Perspective

The cellular thermal shift assay (CETSA) was introduced in 2013 as a means to assess drug binding in complex environments such as cell lysates, live cells, and even tissues. The assay principle relies on the well-proven biophysical concept of ligand-induced thermal stabilization of proteins, which in CETSA applications is measured as a persistent presence of soluble protein at elevated temperatures. Given its recent development, we have just started to learn about the benefits and pitfalls of the method as it is applied to a growing number of protein target classes, the majority of which are intracellular soluble proteins. One of the early technology developments concerned the transfer of the original assay procedure from PCR tubes and Western blot detection of soluble protein to a homogeneous assay in high-density microplates. A move to high-throughput formats is essential for a more systematic application in drug discovery settings, as well as in academic efforts for validating chemical probes through studies of structure-activity relationships. This perspective aims at providing an overview of knowledge gained in microplate formatting of CETSA and makes an attempt at forecasting future applications.

CETSA screening identifies known and novel thymidylate synthase inhibitors and slow intracellular activation of 5-fluorouracil

Target engagement is a critical factor for therapeutic efficacy. Assessment of compound binding to native target proteins in live cells is therefore highly desirable in all stages of drug discovery. We report here the first compound library screen based on biophysical measurements of intracellular target binding, exemplified by human thymidylate synthase (TS). The screen selected accurately for all the tested known drugs acting on TS. We also identified TS inhibitors with novel chemistry and marketed drugs that were not previously known to target TS, including the DNA methyltransferase inhibitor decitabine. By following the cellular uptake and enzymatic conversion of known drugs we correlated the appearance of active metabolites over time with intracellular target engagement. These data distinguished a much slower activation of 5-fluorouracil when compared with nucleoside-based drugs. The approach establishes efficient means to associate drug uptake and activation with target binding during drug discovery.

The In Vitro Pharmacological Profile of Drugs as a Proxy Indicator of Potential In Vivo Organ Toxicities

The potential of a drug to cause certain organ toxicities is somehow implicitly contained in its full pharmacological profile, provided the drug reaches and accumulates at the various organs where the different interacting proteins in its profile, both targets and off-targets, are expressed. Under this assumption, a computational approach was implemented to obtain a projected anatomical profile of a drug from its in vitro pharmacological profile linked to protein expression data across 47 organs. It was observed that the anatomical profiles obtained when using only the known primary targets of the drugs reflected roughly the intended organ targets. However, when both known and predicted secondary pharmacology was considered, the projected anatomical profiles of the drugs were able to clearly highlight potential organ off-targets. Accordingly, when applied to sets of drugs known to cause cardiotoxicity and hepatotoxicity, the approach is able to identify heart and liver, respectively, as the organs where the proteins in the pharmacological profile of the corresponding drugs are specifically expressed. When applied to a set of drugs linked to a risk of Torsades de Pointes, heart is again the organ clearly standing out from the rest and a potential protein profile hazard is proposed. The approach can be used as a proxy indicator of potential in vivo organ toxicities.

Direct Measurement of Intracellular Compound Concentration by RapidFire Mass Spectrometry Offers Insights into Cell Permeability

One of the key challenges facing early stage drug discovery is understanding the commonly observed difference between the activity of compounds in biochemical assays and cellular assays. Traditionally, indirect or estimated cell permeability measurements such as estimations from logP or artificial membrane permeability are used to explain the differences. The missing link is a direct measurement of intracellular compound concentration in whole cells. This can, in some circumstances, be estimated from the cellular activity, but this may also be problematic if cellular activity is weak or absent. Advances in sensitivity and throughput of analytical techniques have enabled us to develop a high-throughput assay for the measurement of intracellular compound concentration for routine use to support lead optimization. The assay uses a RapidFire-MS based readout of compound concentration in HeLa cells following incubation of cells with test compound. The initial assay validation was performed by ultra-high performance liquid chromatography tandem mass spectrometry, and the assay was subsequently transferred to RapidFire tandem mass spectrometry. Further miniaturization and optimization were performed to streamline the process, increase sample throughput, and reduce cycle time. This optimization has delivered a semi-automated platform with the potential of production scale compound profiling up to 100 compounds per day.

Molecular determinants of blood-brain barrier permeation

The blood-brain barrier (BBB) is a microvascular unit which selectively regulates the permeability of drugs to the brain. With the rise in CNS drug targets and diseases, there is a need to be able to accurately predict a priori which compounds in a company database should be pursued for favorable properties. In this review, we will explore the different computational tools available today, as well as underpin these to the experimental methods used to determine BBB permeability. These include in vitro models and the in vivo models that yield the dataset we use to generate predictive models. Understanding of how these models were experimentally derived determines our accurate and predicted use for determining a balance between activity and BBB distribution.