Structural alert/reactive metabolite concept as applied in medicinal chemistry to mitigate the risk of idiosyncratic drug toxicity: a perspective based on the critical examination of trends in the top 200 drugs marketed in the United States

Computationally Assessing the Bioactivation of Drugs by N-Dealkylation

Cytochromes P450 (CYPs) oxidize alkylated amines commonly found in drugs and other biologically active molecules, cleaving them into an amine and an aldehyde. Metabolic studies usually neglect to report or investigate aldehydes, even though they can be toxic. It is assumed that they are efficiently detoxified into carboxylic acids and alcohols. Nevertheless, some aldehydes are reactive and escape detoxification pathways to cause adverse events by forming DNA and protein adducts. Herein, we modeled N-dealkylations that produce both amine and aldehyde metabolites and then predicted the reactivity of the aldehyde. This model used a deep learning approach previously developed by our group to predict other types of drug metabolism. In this study, we trained the model to predict N-dealkylation by human liver microsomes (HLM), finding that including isozyme-specific metabolism data alongside HLM data significantly improved results. The final HLM model accurately predicted the site of N-dealkylation within metabolized substrates (97% top-two and 94% area under the ROC curve). Next, we combined the metabolism, metabolite structure prediction, and previously published reactivity models into a bioactivation model. This combined model predicted the structure of the most likely reactive metabolite of a small validation set of drug-like molecules known to be bioactivated by N-dealkylation. Applying this model to approved and withdrawn medicines, we found that aldehyde metabolites produced from N-dealkylation may explain the hepatotoxicity of several drugs: indinavir, piperacillin, verapamil, and ziprasidone. Our results suggest that N-dealkylation may be an under-appreciated bioactivation pathway, especially in clinical contexts where aldehyde detoxification pathways are inhibited. Moreover, this is the first report of a bioactivation model constructed by combining a metabolism and reactivity model. These results raise hope that more comprehensive models of bioactivation are possible. The model developed in this study is available at http://swami.wustl.edu/xenosite/ .

Design and Mechanism of (S)-3-Amino-4-(difluoromethylenyl)cyclopent-1-ene-1-carboxylic Acid, a Highly Potent γ-Aminobutyric Acid Aminotransferase Inactivator for the Treatment of Addiction

γ-Aminobutyric acid (GABA) is the major inhibitory neurotransmitter in the central nervous system. Inhibition of GABA aminotransferase (GABA-AT), a pyridoxal 5'-phosphate (PLP)-dependent enzyme that degrades GABA, has been established as a possible strategy for the treatment of substance abuse. The raised GABA levels that occur as a consequence of this inhibition have been found to antagonize the rapid release of dopamine in the ventral striatum (nucleus accumbens) that follows an acute challenge by an addictive substance. In addition, increased GABA levels are also known to elicit an anticonvulsant effect in patients with epilepsy. We previously designed the mechanism-based inactivator (1S,3S)-3-amino-4-difluoromethylenyl-1-cyclopentanoic acid (2), now called CPP-115, that is 186 times more efficient in inactivating GABA-AT than vigabatrin, the only FDA-approved drug that is an inactivator of GABA-AT. CPP-115 was found to have high therapeutic potential for the treatment of cocaine addiction and for a variety of epilepsies, has successfully completed a Phase I safety clinical trial, and was found to be effective in the treatment of infantile spasms (West syndrome). Herein we report the design, using molecular dynamics simulations, synthesis, and biological evaluation of a new mechanism-based inactivator, (S)-3-amino-4-(difluoromethylenyl)cyclopent-1-ene-1-carboxylic acid (5), which was found to be almost 10 times more efficient as an inactivator of GABA-AT than CPP-115. We also present the unexpected crystal structure of 5 bound to GABA-AT, as well as computational analyses used to assist the structure elucidation process. Furthermore, 5 was found to have favorable pharmacokinetic properties and low off-target activities. In vivo studies in freely moving rats showed that 5 was dramatically superior to CPP-115 in suppressing the release of dopamine in the corpus striatum, which occurs subsequent to either an acute cocaine or nicotine challenge. Compound 5 also attenuated increased metabolic demands (neuronal glucose metabolism) in the hippocampus, a brain region that encodes spatial information concerning the environment in which an animal receives a reinforcing or aversive drug. This multidisciplinary computational design to preclinical efficacy approach should be applicable to the design and improvement of mechanism-based inhibitors of other enzymes whose crystal structures and inactivation mechanisms are known.

Photooxygenation of an amino-thienopyridone yields a more potent PTP4A3 inhibitor

The phosphatase PTP4A3 is an attractive anticancer target, but knowledge of its exact role in cells remains incomplete. A potent, structurally novel inhibitor of the PTP4A family was obtained by photooxygenation of a less active, electron-rich thienopyridone (1). Iminothienopyridinedione 13 displays increased solution stability and is readily obtained by two new synthetic routes that converge in the preparation of 1. The late-stage photooxygenation of 1 to give 13 in high yield highlights the potential of this reaction to modify the structure and properties of a biological lead compound and generate value for expanding the scope of an SAR investigation. Analog 13 should become a valuable tool for further exploration of the role of PTP4A3 in tumor progression.

Fluorine and Fluorinated Motifs in the Design and Application of Bioisosteres for Drug Design

The electronic properties and relatively small size of fluorine endow it with considerable versatility as a bioisostere and it has found application as a substitute for lone pairs of electrons, the hydrogen atom, and the methyl group while also acting as a functional mimetic of the carbonyl, carbinol, and nitrile moieties. In this context, fluorine substitution can influence the potency, conformation, metabolism, membrane permeability, and P-gp recognition of a molecule and temper inhibition of the hERG channel by basic amines. However, as a consequence of the unique properties of fluorine, it features prominently in the design of higher order structural metaphors that are more esoteric in their conception and which reflect a more sophisticated molecular construction that broadens biological mimesis. In this Perspective, applications of fluorine in the construction of bioisosteric elements designed to enhance the in vitro and in vivo properties of a molecule are summarized.

Identification of Ketene-Reactive Intermediate of Erlotinib Possibly Responsible for Inactivation of P450 Enzymes

Erlotinib (ELT), a tyrosine kinase inhibitor, is widely used for the treatment of nonsmall cell lung cancer in clinic. Unfortunately, severe drug-induced liver injury and other adverse effects occurred during the treatment. Meanwhile, ELT has been reported to be a mechanism-based inactivator of cytochrome P450(CYPs) 3A4 and 3A5. The objectives of this study were to identify ketene intermediate of ELT and investigate the association of the acetylenic bioactivation with the enzyme inactivation caused by ELT. A ketene intermediate was detected in human microsomal incubations of ELT, using 4-bromobenzylamine as a trapping agent. CYPs 3A4 and 3A5 mainly contributed to the bioactivation of ELT. Microsomal incubation study showed that the ketene intermediate covalently modified the enzyme protein at lysine residues and destroyed the structure of heme. The vinyl and ethyl analogs of ELT showed minor enzyme inhibitory effect (less than 20%), whereas ELT inactivated more than 60% of the enzyme. The present study provided a novel bioactivation pathway of ELT and facilitated the understanding of the mechanisms of ELT-induced mechanism-based enzyme inactivation and liver injury.

Identification of a Potent, Highly Selective, and Brain Penetrant Phosphodiesterase 2A Inhibitor Clinical Candidate

Computational modeling was used to direct the synthesis of analogs of previously reported phosphodiesterase 2A (PDE2A) inhibitor 1 with an imidazotriazine core to yield compounds of significantly enhanced potency. The analog PF-05180999 (30) was subsequently identified as a preclinical candidate targeting cognitive impairment associated with schizophrenia. Compound 30 demonstrated potent binding to PDE2A in brain tissue, dose responsive mouse brain cGMP increases, and reversal of N-methyl-d-aspartate (NMDA) antagonist-induced (MK-801, ketamine) effects in electrophysiology and working memory models in rats. Preclinical pharmacokinetics revealed unbound brain/unbound plasma levels approaching unity and good oral bioavailability resulting in an average concentration at steady state (C_av,ss) predicted human dose of 30 mg once daily (q.d.). Modeling of a modified release formulation suggested that 25 mg twice daily (b.i.d.) could maintain plasma levels of 30 at or above targeted efficacious plasma levels for 24 h, which became part of the human clinical plan.

Lipoprotein Signal Peptidase Inhibitors with Antibiotic Properties Identified through Design of a Robust In Vitro HT Platform

As resistance to antibiotics increases, the exploration of new targets and strategies to combat pathogenic bacteria becomes more urgent. Ideal protein targets are required for viability across many species, are unique to prokaryotes to limit effects on the host, and have robust assays to quantitate activity and identify inhibitors. Lipoprotein signal peptidase (Lsp) is a transmembrane aspartyl protease required for lipoprotein maturation and comprehensively fits these criteria. Here, we have developed the first in vitro high-throughput assay to monitor proteolysis by Lsp. We employed our high-throughput screen assay against 646,275 compounds to discover inhibitors of Lsp and synthesized a range of analogs to generate molecules with nanomolar half maximal inhibitory concentration values. Importantly, our inhibitors are effective in preventing the growth of E. coli cultures in the presence of outer-membrane permeabilizer PMBN and should facilitate development of antibacterial agents with a novel mechanism of action to treat antibiotic-resistant bacteria.

Deuterium- and Tritium-Labelled Compounds: Applications in the Life Sciences

Hydrogen isotopes are unique tools for identifying and understanding biological and chemical processes. Hydrogen isotope labelling allows for the traceless and direct incorporation of an additional mass or radioactive tag into an organic molecule with almost no changes in its chemical structure, physical properties, or biological activity. Using deuterium-labelled isotopologues to study the unique mass-spectrometric patterns generated from mixtures of biologically relevant molecules drastically simplifies analysis. Such methods are now providing unprecedented levels of insight in a wide and continuously growing range of applications in the life sciences and beyond. Tritium (³ H), in particular, has seen an increase in utilization, especially in pharmaceutical drug discovery. The efforts and costs associated with the synthesis of labelled compounds are more than compensated for by the enhanced molecular sensitivity during analysis and the high reliability of the data obtained. In this Review, advances in the application of hydrogen isotopes in the life sciences are described.

Computational Toxicology and Drug Discovery

The use of computational toxicology methods within drug discovery began in the early 2000s with applications such as predicting bacterial mutagenicity and hERG inhibition. The field has been continuously expanding ever since and the tasks at hand have become more complex. These approaches are now strategically integrated into the risk assessment process, as a complement to in vitro and in vivo methods. Today, computational toxicology can be used in every phase of drug discovery and development, from profiling large libraries early on, to predicting off-target effects in the mid-discovery phase, to assessing potential mutagenic impurities in development and degradants as part of life-cycle management. This chapter provides an overview of the field and describes the application of computational toxicology throughout the entire discovery and development process.

LC-ESI-MS/MS reveals the formation of reactive intermediates in brigatinib metabolism: elucidation of bioactivation pathways

Four phase I BGB metabolites and three cyano adducts for BGB were detected using LC-MS/MS. The piperidine ring was found to be responsible for BGB bioactivation and the bioactivation pathways are proposed.

Successful Identification of Cardiac Troponin Calcium Sensitizers Using a Combination of Virtual Screening and ROC Analysis of Known Troponin C Binders

Calcium-dependent cardiac muscle contraction is regulated by the protein complex troponin. Calcium binds to the N-terminal domain of troponin C (cNTnC) which initiates the process of contraction. Heart failure is a consequence of a disruption of this process. With the prevalence of this condition, a strong need exists to find novel compounds to increase the calcium sensitivity of cNTnC. Desirable are small chemical molecules that bind to the interface between cTnC and the cTnI switch peptide and exhibit calcium sensitizing properties by possibly stabilizing cTnC in an open conformation. To identify novel drug candidates, we employed a structure-based drug discovery protocol that incorporated the use of a relaxed complex scheme (RCS). In preparation for the virtual screening, cNTnC conformations were identified based on their ability to correctly predict known cNTnC binders using a receiver operating characteristics analysis. Following a virtual screen of the National Cancer Institute's Developmental Therapeutic Program database, a small number of molecules were experimentally tested using stopped-flow kinetics and steady-state fluorescence titrations. We identified two novel compounds, 3-(4-methoxyphenyl)-6,7-chromanediol (NSC600285) and 3-(4-methylphenyl)-7,8-chromanediol (NSC611817), that show increased calcium sensitivity of cTnC in the presence of the regulatory domain of cTnI. The effects of NSC600285 and NSC611817 on the calcium dissociation rate was stronger than that of the known calcium sensitizer bepridil. Thus, we identified a 3-phenylchromane group as a possible key pharmacophore in the sensitization of cardiac muscle contraction. Building on this finding is of interest to researchers working on development of drugs for calcium sensitization.

Design, Synthesis, and Structure-Activity Relationship of Tetrahydropyrido[4,3-d]pyrimidine Derivatives as Potent Smoothened Antagonists with in Vivo Activity

Medulloblastoma is one of the most prevalent brain tumors in children. Aberrant hedgehog (Hh) pathway signaling is thought to be involved in the initiation and development of medulloblastoma. Vismodegib, the first FDA-approved cancer therapy based on inhibition of aberrant hedgehog signaling, targets smoothened (Smo), a G-protein coupled receptor (GPCR) central to the Hh pathway. Although vismodegib exhibits promising therapeutic efficacy in tumor treatment, concerns have been raised from its nonlinear pharmacokinetic (PK) profiles at high doses partly due to low aqueous solubility. Many patients experience adverse events such as muscle spasms and weight loss. In addition, drug resistance often arises among tumor cells during treatment with vismodegib. There is clearly an urgent need to explore novel Smo antagonists with improved potency and efficacy. Through a scaffold hopping strategy, we have identified a series of novel tetrahydropyrido[4,3-d]pyrimidine derivatives, which exhibited effective inhibition of Hh signaling. Among them, compound 24 is three times more potent than vismodegib in the NIH3T3-GRE-Luc reporter gene assay. Compound 24 has a lower melting point and much greater solubility compared with vismodegib, resulting in linear PK profiles when dosed orally at 10, 30, and 100 mg/kg in rats. Furthermore, compound 24 showed excellent PK profiles with a 72% oral bioavailability in beagle dogs. Compound 24 demonstrated overall favorable in vitro safety profiles with respect to CYP isoform and hERG inhibition. Finally, compound 24 led to significant regression of subcutaneous tumor generated by primary Ptch1-deficient medulloblastoma cells in SCID mouse. In conclusion, tetrahydropyrido[4,3-d]pyrimidine derivatives represent a novel set of Smo inhibitors that could potentially be utilized to treat medulloblastoma and other Hh pathway related malignancies.

Discovery and Characterization of (R)-6-Neopentyl-2-(pyridin-2-ylmethoxy)-6,7-dihydropyrimido[2,1-c][1,4]oxazin-4(9H)-one (PF-06462894), an Alkyne-Lacking Metabotropic Glutamate Receptor 5 Negative Allosteric Modulator Profiled in both Rat and Nonhuman Primates

We previously observed a cutaneous type IV immune response in nonhuman primates (NHP) with the mGlu₅ negative allosteric modulator (NAM) 7. To determine if this adverse event was chemotype- or mechanism-based, we evaluated a distinct series of mGlu₅ NAMs. Increasing the sp³ character of high-throughput screening hit 40 afforded a novel morpholinopyrimidone mGlu₅ NAM series. Its prototype, (R)-6-neopentyl-2-(pyridin-2-ylmethoxy)-6,7-dihydropyrimido[2,1-c][1,4]oxazin-4(9H)-one (PF-06462894, 8), possessed favorable properties and a predicted low clinical dose (2 mg twice daily). Compound 8 did not show any evidence of immune activation in a mouse drug allergy model. Additionally, plasma samples from toxicology studies confirmed that 8 did not form any reactive metabolites. However, 8 caused the identical microscopic skin lesions in NHPs found with 7, albeit with lower severity. Holistically, this work supports the hypothesis that this unique toxicity may be mechanism-based although additional work is required to confirm this and determine clinical relevance.

Discovery of novel frizzled-7 inhibitors by targeting the receptor's transmembrane domain

Frizzled (Fzd) proteins are seven transmembrane receptors that belong to a novel and separated family of G-protein-coupled receptors (GPCRs). The Fzd receptors can respond to Wnt proteins to activate the canonical β-catenin pathway which is important for both initiation and progression of cancers. Disruption of the Wnt/β-catenin signal thus represents an opportunity for rational cancer prevention and therapy. Of the 10 members of the Fzd family, Fzd7 is the most important member involved in cancer development and progression. In the present studies, we applied structure-based virtual screening targeting the transmembrane domain (TMD) of Fzd7 to select compounds that could potentially bind to the Fzd7-TMD and block the Wnt/Fzd7 signaling and further evaluated them in biological assays. Six small molecule compounds were confirmed as Fzd7 inhibitors. The best hit, SRI37892, significantly blocked the Wnt/Fzd7 signaling with IC₅₀ values in the sub-micromolar range and inhibited cancer cell proliferation with IC₅₀ values around 2 μM. Our results provide the first proof of concept of targeting Fzd-TMD for the development of Wnt/Fzd modulators. The identified small molecular Fzd7 inhibitors can serve as a useful tool for studying the regulation mechanism(s) of Wnt/Fzd7 signaling as well as a starting point for the development of cancer therapeutic agents.

Quantitative Chemical Proteomic Profiling of the in Vivo Targets of Reactive Drug Metabolites

Idiosyncratic liver toxicity represents an important problem in drug research and pharmacotherapy. Reactive drug metabolites that modify proteins are thought to be a principal factor in drug-induced liver injury. Here, we describe a quantitative chemical proteomic method to identify the targets of reactive drug metabolites in vivo. Treating mice with clickable analogues of four representative hepatotoxic drugs, we demonstrate extensive covalent binding that is confined primarily to the liver. Each drug exhibited a distinct target profile that, in certain cases, showed strong enrichment for specific metabolic pathways (e.g., lipid/sterol pathways for troglitazone). Site-specific proteomics revealed that acetaminophen reacts with high stoichiometry with several conserved, functional (seleno)cysteine residues throughout the liver proteome. Our findings thus provide an advanced experimental framework to characterize the proteomic reactivity of drug metabolites in vivo, revealing target profiles that may help to explain mechanisms and identify risk factors for drug-induced liver injury.

Mechanisms of Skin Toxicity Associated with Metabotropic Glutamate Receptor 5 Negative Allosteric Modulators

Cutaneous reactions represent one of the most common adverse drug effects observed in clinical trials leading to substantial compound attrition. Three negative allosteric modulators (NAMs) of metabotropic glutamate receptors (mGluRs), which represent an important target for neurological diseases, developed by Pfizer, were recently failed in preclinical development due to delayed type IV skin hypersensitivity observed in non-human primates (NHPs). Here we employed large-scale phenotypic profiling in standardized panels of human primary cell/co-culture systems to characterize the skin toxicity mechanism(s) of mGluR5 NAMs from two different series. Investigation of a database of chemicals tested in these systems and transcriptional profiling suggested that the mechanism of toxicity may involve modulation of nuclear receptor targets RAR/RXR, and/or VDR with AhR antagonism. The studies reported here demonstrate how phenotypic profiling of preclinical drug candidates using human primary cells can provide insights into the mechanisms of toxicity and inform early drug discovery and development campaigns.

Nontargeted Identification of Reactive Metabolite Protein Adducts

Metabolic bioactivation of many different chemicals results in the formation of highly reactive compounds (chemically reactive metabolites, CRMs) that can lead to toxicity via binding to macromolecular targets (e.g., proteins or DNA). There is a need to develop robust, rapid, and nontargeted analytical techniques to determine the identity of the protein targets of CRMs and their sites of modification. Here, we introduce a nontargeted methodology capable of determining both the identity of a CRM formed from an administered compound as well as the protein targets modified by the reactive metabolite in a single experiment without prior information. Acetaminophen (N-acetyl-p-aminophenol, APAP) and ¹³C₆-APAP were incubated with rat liver microsomes, which are known to bioactivate APAP to the reactive metabolite N-acetyl-p-benzoquinone imine (NAPQI). Global tryptic digestion followed by liquid chromatographic/mass spectrometric (LC/MS) analysis was used to locate "twin" ion peaks of peptides adducted by NAPQI and for shotgun proteomics via tandem mass spectrometry (MS/MS). By the development of blended data analytics software called Xenophile, the identity of the amino acid residue that was adducted can be established, which eliminates the need for specific parametrization of protein database search algorithms. This combination of experimental design and data analysis software allows the identity of a CRM, the protein target, and the amino acid residues that are modified to be rapidly established directly from experimental data. Xenophile is freely available from https://github.com/mgleeming/Xenophile .

Discovery of 2-[[2-Ethyl-6-[4-[2-(3-hydroxyazetidin-1-yl)-2-oxoethyl]piperazin-1-yl]-8-methylimidazo[1,2-a]pyridin-3-yl]methylamino]-4-(4-fluorophenyl)thiazole-5-carbonitrile (GLPG1690), a First-in-Class Autotaxin Inhibitor Undergoing Clinical Evaluation for the Treatment of Idiopathic Pulmonary Fibrosis

Autotaxin is a circulating enzyme with a major role in the production of lysophosphatic acid (LPA) species in blood. A role for the autotaxin/LPA axis has been suggested in many disease areas including pulmonary fibrosis. Structural modifications of the known autotaxin inhibitor lead compound 1, to attenuate hERG inhibition, remove CYP3A4 time-dependent inhibition, and improve pharmacokinetic properties, led to the identification of clinical candidate GLPG1690 (11). Compound 11 was able to cause a sustained reduction of LPA levels in plasma in vivo and was shown to be efficacious in a bleomycin-induced pulmonary fibrosis model in mice and in reducing extracellular matrix deposition in the lung while also reducing LPA 18:2 content in bronchoalveolar lavage fluid. Compound 11 is currently being evaluated in an exploratory phase 2a study in idiopathic pulmonary fibrosis patients.

Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors

The modulation of PPIs by low molecular weight chemical compounds, particularly by orally bioavailable molecules, would be very valuable in numerous disease indications. However, it is known that PPI inhibitors (iPPIs) tend to have properties that are linked to poor Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) and in some cases to poor clinical outcomes. Previously reported in silico analyses of iPPIs have essentially focused on physicochemical properties but several other ADMET parameters would be important to assess. In order to gain new insights into the ADMET properties of iPPIs, computations were carried out on eight datasets collected from several databases. These datasets involve compounds targeting enzymes, GPCRs, ion channels, nuclear receptors, allosteric modulators, oral marketed drugs, oral natural product-derived marketed drugs and iPPIs. Several trends are reported that should assist the design and optimization of future PPI inhibitors, either for drug discovery endeavors or for chemical biology projects.

Prediction of hERG Liability - Using SVM Classification, Bootstrapping and Jackknifing

Drug-induced QT prolongation leads to life-threatening cardiotoxicity, mostly through blockage of the human ether-à-go-go-related gene (hERG) encoded potassium ion (K+ ) channels. The hERG channel is one of the most important antitargets to be addressed in the early stage of drug discovery process, in order to avoid more costly failures in the development phase. Using a thallium flux assay, 4,323 molecules were screened for hERG channel inhibition in a quantitative high throughput screening (qHTS) format. Here, we present support vector classification (SVC) models of hERG channel inhibition with the averaged area under the receiver operator characteristics curve (AUC-ROC) of 0.93 for the tested compounds. Both Jackknifing and bootstrapping have been employed to rebalance the heavily biased training datasets, and the impact of these two under-sampling rebalance methods on the performance of the predictive models is discussed. Our results indicated that the rebalancing techniques did not enhance the predictive power of the resulting models; instead, adoption of optimal cutoffs could restore the desirable balance of sensitivity and specificity of the binary classifiers. In an external validation set of 66 drug molecules, the SVC model exhibited an AUC-ROC of 0.86, further demonstrating the utility of this modeling approach to predict hERG liabilities.

Computational Approach to Structural Alerts: Furans, Phenols, Nitroaromatics, and Thiophenes

Structural alerts are commonly used in drug discovery to identify molecules likely to form reactive metabolites and thereby become toxic. Unfortunately, as useful as structural alerts are, they do not effectively model if, when, and why metabolism renders safe molecules toxic. Toxicity due to a specific structural alert is highly conditional, depending on the metabolism of the alert, the reactivity of its metabolites, dosage, and competing detoxification pathways. A systems approach, which explicitly models these pathways, could more effectively assess the toxicity risk of drug candidates. In this study, we demonstrated that mathematical models of P450 metabolism can predict the context-specific probability that a structural alert will be bioactivated in a given molecule. This study focuses on the furan, phenol, nitroaromatic, and thiophene alerts. Each of these structural alerts can produce reactive metabolites through certain metabolic pathways but not always. We tested whether our metabolism modeling approach, XenoSite, can predict when a given molecule's alerts will be bioactivated. Specifically, we used models of epoxidation, quinone formation, reduction, and sulfur-oxidation to predict the bioactivation of furan-, phenol-, nitroaromatic-, and thiophene-containing drugs. Our models separated bioactivated and not-bioactivated furan-, phenol-, nitroaromatic-, and thiophene-containing drugs with AUC performances of 100%, 73%, 93%, and 88%, respectively. Metabolism models accurately predict whether alerts are bioactivated and thus serve as a practical approach to improve the interpretability and usefulness of structural alerts. We expect that this same computational approach can be extended to most other structural alerts and later integrated into toxicity risk models. This advance is one necessary step toward our long-term goal of building comprehensive metabolic models of bioactivation and detoxification to guide assessment and design of new therapeutic molecules.

Pharmacokinetic optimitzation of CCG-203971: Novel inhibitors of the Rho/MRTF/SRF transcriptional pathway as potential antifibrotic therapeutics for systemic scleroderma

We recently reported the development of a novel inhibitor of Rho-mediated gene transcription (1, CCG-203971) that is efficacious in multiple animal models of acute fibrosis, including scleroderma, when given intraperitoneally. The modest in vivo potency and poor pharmacokinetics (PK) of this lead, however, make it unsuitable for long term efficacy studies. We therefore undertook a systematic medicinal chemistry effort to improve both the metabolic stability and the solubility of 1, resulting in the identification of two analogs achieving over 10-fold increases in plasma exposures in mice. We subsequently showed that one of these analogs (8f, CCG-232601) could inhibit the development of bleomycin-induced dermal fibrosis in mice when administered orally at 50mg/kg, an effect that was comparable to what we had observed earlier with 1 at a 4-fold higher IP dose.

Acyl glucuronide metabolites: Implications for drug safety assessment

Acyl glucuronides are important metabolites of compounds with carboxylic acid moieties and have unique properties that distinguish them from other phase 2 metabolites. In particular, in addition to being often unstable, acyl glucuronide metabolites can be chemically reactive leading to covalent binding with macromolecules and toxicity. While there is circumstantial evidence that drugs forming acyl glucuronide metabolites can be associated with rare, but severe idiosyncratic toxic reactions, many widely prescribed drugs with good safety records are also metabolized through acyl glucuronidation. Therefore, there is a need to understand the various factors that can affect the safety of acyl glucuronide-producing drugs including the rate of acyl glucuronide formation, the relative reactivity of the acyl glucuronide metabolite formed, the rate of elimination, potential proteins being targeted, and the rate of aglucuronidation. In this review, these factors are discussed and various approaches to de-risk the safety liabilities of acyl glucuronide metabolites are evaluated.

Discovery of Compounds that Positively Modulate the High Affinity Choline Transporter

Cholinergic hypofunction is associated with decreased attention and cognitive deficits in the central nervous system in addition to compromised motor function. Consequently, stimulation of cholinergic neurotransmission is a rational therapeutic approach for the potential treatment of a variety of neurological conditions. High affinity choline uptake (HACU) into acetylcholine (ACh)-synthesizing neurons is critically mediated by the sodium- and pH-dependent high-affinity choline transporter (CHT, encoded by the SLC5A7 gene). This transporter is comparatively well-characterized but otherwise unexplored as a potential drug target. We therefore sought to identify small molecules that would enable testing of the hypothesis that positive modulation of CHT mediated transport would enhance activity-dependent cholinergic signaling. We utilized existing and novel screening techniques for their ability to reveal both positive and negative modulation of CHT using literature tools. A screening campaign was initiated with a bespoke compound library comprising both the Pfizer Chemogenomic Library (CGL) of 2,753 molecules designed specifically to help enable the elucidation of new mechanisms in phenotypic screens and 887 compounds from a virtual screening campaign to select molecules with field-based similarities to reported negative and positive allosteric modulators. We identified a number of previously unknown active and structurally distinct molecules that could be used as tools to further explore CHT biology or as a starting point for further medicinal chemistry.

Deep Learning to Predict the Formation of Quinone Species in Drug Metabolism

Many adverse drug reactions are thought to be caused by electrophilically reactive drug metabolites that conjugate to nucleophilic sites within DNA and proteins, causing cancer or toxic immune responses. Quinone species, including quinone-imines, quinone-methides, and imine-methides, are electrophilic Michael acceptors that are often highly reactive and comprise over 40% of all known reactive metabolites. Quinone metabolites are created by cytochromes P450 and peroxidases. For example, cytochromes P450 oxidize acetaminophen to N-acetyl-p-benzoquinone imine, which is electrophilically reactive and covalently binds to nucleophilic sites within proteins. This reactive quinone metabolite elicits a toxic immune response when acetaminophen exceeds a safe dose. Using a deep learning approach, this study reports the first published method for predicting quinone formation: the formation of a quinone species by metabolic oxidation. We model both one- and two-step quinone formation, enabling accurate quinone formation predictions in nonobvious cases. We predict atom pairs that form quinones with an AUC accuracy of 97.6%, and we identify molecules that form quinones with 88.2% AUC. By modeling the formation of quinones, one of the most common types of reactive metabolites, our method provides a rapid screening tool for a key drug toxicity risk. The XenoSite quinone formation model is available at http://swami.wustl.edu/xenosite/p/quinone .

Exposure to reactive intermediate-inducing drugs during pregnancy and the incident use of psychotropic medications among children

PURPOSE

Our study aimed to investigate the association between prenatal exposure to reactive intermediate (RI)-inducing drugs and the initiation of psychotropic medications among children.

METHODS

We designed a cohort study using a pharmacy prescription database. Pregnant women were considered exposed when they received a prescription of RI-inducing drugs. These drugs could be either used alone (RI+/FAA-) or combined with drugs exhibiting folic acid antagonism (FAA, RI+/FAA+). The reference group included pregnant women who did not receive any RI-inducing drugs or FAA drugs.

RESULTS

We analyzed 4116 exposed and 30 422 reference pregnancies. The hazard ratio (HR) with 95% confidence interval (CI) was 1.27 (95%CI 1.15-1.41) for pregnancies exposed to RI-inducing drugs as a whole. Considering subgroups of RI-inducing drugs, prenatal exposure to both RI+/FAA+ and RI+/FAA- was associated with the children's initiation of psychotropic medications, HRs being 1.35 (95%CI 1.10-1.66) and 1.26 (1.13-1.41), respectively. The HRs were increased with prolonged exposure to RI-inducing drugs, especially in the first and second trimesters. In a detailed examination of the psychotropics, the incidences of receiving antimigraine preparations and psychostimulants were significantly increased for the exposed children, compared with the reference children. The incidences of receiving antipsychotics and hypnotics were also higher for the exposed children; however, the HRs did not reach significance after adjustment.

CONCLUSIONS

We found a significantly increased incident use of psychotropic medications among children prenatally exposed to RI-inducing drugs, especially during the first and second trimesters. This suggests a detrimental effect during critical periods of brain development. Copyright © 2017 John Wiley & Sons, Ltd.

Biomonitoring Human Albumin Adducts: The Past, the Present, and the Future

Serum albumin (Alb) is the most abundant protein in blood plasma. Alb reacts with many carcinogens and/or their electrophilic metabolites. Studies conducted over 20 years ago showed that Alb forms adducts with the human carcinogens aflatoxin B1 and benzene, which were successfully used as biomarkers in molecular epidemiology studies designed to address the role of these chemicals in cancer risk. Alb forms adducts with many therapeutic drugs or their reactive metabolites such as β-lactam antibiotics, acetylsalicylic acid, acetaminophen, nonsteroidal anti-inflammatory drugs, chemotherapeutic agents, and antiretroviral therapy drugs. The identification and characterization of the adduct structures formed with Alb have served to understand the generation of reactive metabolites and to predict idiosyncratic drug reactions and toxicities. The reaction of candidate drugs with Alb is now exploited as part of the battery of screening tools to assess the potential toxicities of drugs. The use of gas chromatography-mass spectrometry, liquid chromatography, or liquid chromatography-mass spectrometry (LC-MS) enabled the identification and quantification of multiple types of Alb xenobiotic adducts in animals and humans during the past three decades. In this perspective, we highlight the history of Alb as a target protein for adduction to environmental and dietary genotoxicants, pesticides, and herbicides, common classes of medicinal drugs, and endogenous electrophiles, and the emerging analytical mass spectrometry technologies to identify Alb-toxicant adducts in humans.

The Opportunities of Metabolomics in Drug Safety Evaluation

Although safety of drug candidates is carefully monitored in preclinical and clinical studies using a variety of approaches, drug toxicity may still occur in clinical practice. Therefore, novel approaches are needed to complement the current drug safety evaluation system. Metabolomics comprehensively analyzes the metabolites altered by drug exposure, which can therefore be used to profile drug metabolism, endobiotic metabolism, and drug-microbiota interactions. The information from metabolomic analysis can be used to determine the off-targets of a drug candidate, and thus provide a mechanistic understanding of drug toxicity. We herein discuss the opportunities of metabolomics in drug safety evaluation.

LC-MS/MS reveals the formation of aldehydes and iminium reactive intermediates in foretinib metabolism: phase I metabolic profiling

Using LC-MS/MS, six phase I foretinib metabolites in addition to four potential reactive metabolites, two aldehydes and two iminium ions, were detected and the bioactivation pathways were proposed.

Identification and characterization of in vitro phase I and reactive metabolites of masitinib using a LC-MS/MS method: bioactivation pathway elucidation

In vitro phase I metabolic reactions & cyano conjugates of masitinib.

In silico prediction of the mutagenicity of nitroaromatic compounds using a novel two-QSAR approach

Certain drugs are nitroaromatic compounds, which are potentially toxic. As such, it is of practical importance to assess and predict their mutagenic potency in the process of drug discovery. A classical quantitative structure-activity relationship (QSAR) model was developed using the linear partial least square (PLS) scheme to understand the underline mutagenic mechanism and a non-classical QSAR model was derived using the machine learning-based hierarchical support vector regression (HSVR) to predict the mutagenicity of nitroaromatic compounds based on a series of mutagenicity data (TA98-S9). It was observed that HSVR performed better than PLS as manifested by the predictions of the samples in the training set, test set, and outlier set as well as various statistical validations. A mock test designated to mimic real challenges also confirmed the better performance of HSVR. Furthermore, HSVR exhibited superiority in predictivity, generalization capabilities, consistent performance, and robustness when compared with various published predictive models. PLS, conversely, revealed some mechanistically interpretable relationships between descriptors and mutagenicity. Thus, this two-QSAR approach using the predictive HSVR and interpretable PLS models in a synergistic fashion can be adopted to facilitate drug discovery and development by designing safer drug candidates with nitroaromatic moiety.

Aminomethyl-Derived Beta Secretase (BACE1) Inhibitors: Engaging Gly230 without an Anilide Functionality

A growing subset of β-secretase (BACE1) inhibitors for the treatment of Alzheimer’s disease (AD) utilizes an anilide chemotype that engages a key residue (Gly230) in the BACE1 binding site. Although the anilide moiety affords excellent potency, it simultaneously introduces a third hydrogen bond donor that limits brain availability and provides a potential metabolic site leading to the formation of an aniline, a structural motif of prospective safety concern. We report herein an alternative aminomethyl linker that delivers similar potency and improved brain penetration relative to the amide moiety. Optimization of this series identified analogues with an excellent balance of ADME properties and potency; however, potential drug–drug interactions (DDI) were predicted based on CYP 2D6 affinities. Generation and analysis of key BACE1 and CYP 2D6 crystal structures identified strategies to obviate the DDI liability, leading to compound 16, which exhibits robust in vivo efficacy as a BACE1 inhibitor.