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

Bioactivation and reactivity research advances - 2023 year in review

Advances in the field of bioactivation have significantly contributed to our understanding and prediction of drug-induced liver injury (DILI). It has been established that many adverse drug reactions, including DILI, are associated with the formation and reactivity of metabolites. Modern methods allow us to detect and characterize these reactive metabolites in earlier stages of drug development, which helps anticipate and circumvent the potential for DILI. Improved in silico models and experimental techniques that better reflect in vivo environments are enhancing predictive capabilities for DILI risk. Further, studies on the mechanisms of bioactivation, including enzyme interactions and the role of individual genetic differences, have provided valuable insights for drug optimizations. Cumulatively, this progress is continually refining our approaches to drug safety evaluation and personalized medicine.

Teratogenicity is more likely a function of primary and secondary pharmacology than caused by chemically reactive metabolites: a critical evaluation of 40 years of scientific research

The number of therapeutic drugs known to be human teratogens is actually relatively small. This may reflect the rigorous animal testing and well defined labelling. Some of these drugs were identified to have reactive metabolites and this has been postulated, historically, to be their teratogenic mechanism. These drugs include thalidomide, various anticonvulsants and retinoic acid derivatives.Many of these experiments were conducted in a period where chemically reactive metabolites were being intensely investigated and associated with all forms of toxicity. The legacy of this is that these examples are routinely cited as well established mechanisms.Examination of mechanism leads to the conclusion that the teratogenicity in humans of these compounds is likely due to the primary and secondary pharmacology of the parent drug and stable circulating metabolites and that association of reactive metabolites to this toxicity is unwarranted.

An update on lipophilic efficiency as an important metric in drug design

INTRODUCTION

Lipophilic efficiency (LipE) and lipophilic metabolic efficiency (LipMetE) are valuable tools that can be utilized as part of a multiparameter optimization process to advance a hit to a clinical quality compound.

AREAS COVERED

This review covers recent, effective use cases of LipE and LipMetE that have been published in the literature over the past 5 years. These use cases resulted in the delivery of high-quality molecules that were brought forward to in vivo work and/or to clinical studies. The authors discuss best-practices for using LipE and LipMetE analysis, combined with lipophilicity-focused compound design strategies, to increase the speed and effectiveness of the hit to clinical quality compound optimization process.

EXPERT OPINION

It has become well established that increasing LipE and LipMetE within a series of analogs facilitates the improvement of broad selectivity, clearance, solubility, and permeability and, through this optimization, also facilitates the achievement of desired pharmacokinetic properties, efficacy, and tolerability. Within this article, we discuss lipophilic efficiency-focused optimization as a tool to yield high-quality potential clinical candidates. It is suggested that LipE/LipMetE-focused optimization can facilitate and accelerate the drug-discovery process.

Identification of an Epoxide Metabolite of Amitriptyline In Vitro and In Vivo

Amitriptyline (ATL), a tricyclic antidepressant, has been reported to cause various adverse effects, particularly hepatotoxicity. The mechanisms of ATL-induced hepatotoxicity remain unknown. The study was performed to identify the olefin epoxidation metabolite of ATL and determine the possible toxicity mechanism. Two glutathione (GSH) conjugates (M1 and M2) and two N-acetylcysteine (NAC) conjugates (M3 and M4) were detected in rat liver microsomal incubations supplemented with GSH and NAC, respectively. Moreover, M1/M2 and M3/M4 were respectively found in ATL-treated rat primary hepatocytes and in bile and urine of rats given ATL. Recombinant P450 enzyme incubations demonstrated that CYP3A4 was the primary enzyme involved in the olefin epoxidation of ATL. Treatment of hepatocytes with ATL resulted in significant cell death. Inhibition of CYP3A attenuated the susceptibility to the observed cytotoxicity of ATL. The metabolic activation of ATL most likely participates in the cytotoxicity of ATL.

Cyanide Trapping of Iminium Ion Reactive Metabolites: Implications for Clinical Hepatotoxicity

Reactive metabolite formation is a major mechanism of hepatotoxicity. Although reactive electrophiles can be soft or hard in nature, screening strategies have generally focused on the use of glutathione trapping assays to screen for soft electrophiles, with many data sets available to support their use. The use of a similar assay for hard electrophiles using cyanide as the trapping agent is far less common, and there is a lack of studies with sufficient supporting data. Using a set of 260 compounds with a defined hepatotoxicity status by the FDA, a comprehensive literature search yielded cyanide trapping data on an unbalanced set of 20 compounds that were all clinically hepatotoxic. Thus, a further set of 19 compounds was selected to generate cyanide trapping data, resulting in a more balanced data set of 39 compounds. Analysis of the data demonstrated that the cyanide trapping assay had high specificity (92%) and a positive predictive value (83%) such that hepatotoxic compounds would be confidently flagged. Structural analysis of the adducts formed revealed artifactual methylated cyanide adducts to also occur, highlighting the importance of full structural identification to confirm the nature of the adduct formed. The assay was demonstrated to add the most value for compounds containing typical structural alerts for hard electrophile formation: half of the severe hepatotoxins with these structural alerts formed cyanide adducts, while none of the severe hepatotoxins with no relevant structural alerts formed adducts. The assay conditions used included cytosolic enzymes (e.g., aldehyde oxidase) and an optimized cyanide concentration to minimize the inhibition of cytochrome P450 enzymes by cyanide. Based on the demonstrated added value of this assay, it is to be initiated for use at GSK as part of the integrated hepatotoxicity strategy, with its performance being reviewed periodically as more data is generated.

Ion Trap LC/MS reveals the generation of reactive intermediates in acalabrutinib metabolism: phase I metabolic profiling and bioactivation pathways elucidation

Acalabrutinib (CALQUENCE; ACB) is a Bruton tyrosine kinase inhibitor (BTKI) used to treat mantle cell lymphoma, small lymphocytic lymphoma (SLL), and chronic lymphocytic leukemia (CLL). On 21 November 2019, ACB was approved by the U.S. FDA for the use as a single therapy for the treatment of CLL/SLL. In silico studies were first done to propose vulnerable sites of metabolism and reactivity pathways by StarDrop software and Xenosite online software; respectively. ACB metabolites and stable adducts were characterized in vitro from rat liver microsomes (RLMs) using Ion Trap LC/MS. Generation of reactive intermediates (RIs) in the in vitro metabolism of ACB was investigated using glutathione, potassium cyanide, and methoxylamine as trapping nucleophiles for the RIs including iminopyridinone, iminium, and aldehyde, respectively, to form stable adducts that can be identified and characterized by Ion Trap LC/MS. Five phase I metabolites, seven 6-iminopyridin-3(6H)-one and five aldehyde RIs of ACB were identified. Based on literature reviews, the generation of RIs of ACB, and the subsequent drug-induced organ toxicity (DIOT) reactions may provide an explanation of ACB ADRs. Additional drug discovery investigations can be performed to facilitate the creation of novel medications with improved safety characteristics.

Prediction of cytochrome P450-mediated bioactivation using machine learning models and in vitro validation

Cytochrome P450 (P450)-mediated bioactivation, which can lead to the hepatotoxicity through the formation of reactive metabolites (RMs), has been regarded as the major problem of drug failures. Herein, we purposed to establish machine learning models to predict the bioactivation of P450. On the basis of the literature-derived bioactivation dataset, models for Benzene ring, Nitrogen heterocycle and Sulfur heterocycle were developed with machine learning methods, i.e., Random Forest, Random Subspace, SVM and Naïve Bayes. The models were assessed by metrics like "Precision", "Recall", "F-Measure", "AUC" (Area Under the Curve), etc. Random Forest algorithms illustrated the best predictability, with nice AUC values of 0.949, 0.973 and 0.958 for the test sets of Benzene ring, Nitrogen heterocycle and Sulfur heterocycle models, respectively. 2D descriptors like topological indices, 2D autocorrelations and Burden eigenvalues, etc. contributed most to the models. Furthermore, the models were applied to predict the occurrence of bioactivation of an external verification set. Drugs like selpercatinib, glafenine, encorafenib, etc. were predicted to undergo bioactivation into toxic RMs. In vitro, IC50 shift experiment was performed to assess the potential of bioactivation to validate the prediction. Encorafenib and tirbanibulin were observed of bioactivation potential with shifts of 3-6 folds or so. Overall, this study provided a reliable and robust strategy to predict the P450-mediated bioactivation, which will be helpful to the assessment of adverse drug reactions (ADRs) in clinic and the design of new candidates with lower toxicities.

Small molecule drug metabolite synthesis and identification: why, when and how?

The drug discovery and development process encompasses the interrogation of metabolites arising from the biotransformation of drugs. Here we look at why, when and how metabolites of small-molecule drugs are synthesised from the perspective of a specialist contract research organisation, with particular attention paid to projects for which regulatory oversight is relevant during this journey. To illustrate important aspects, we look at recent case studies, trends and learnings from our experience of making and identifying metabolites over the past ten years, along with with selected examples from the literature.

Pharmacokinetics Profiler (PhaKinPro): Model Development, Validation, and Implementation as a Web Tool for Triaging Compounds with Undesired Pharmacokinetics Profiles

Computational models that predict pharmacokinetic properties are critical to deprioritize drug candidates that emerge as hits in high-throughput screening campaigns. We collected, curated, and integrated a database of compounds tested in 12 major end points comprising over 10,000 unique molecules. We then employed these data to build and validate binary quantitative structure-activity relationship (QSAR) models. All trained models achieved a correct classification rate above 0.60 and a positive predictive value above 0.50. To illustrate their utility in drug discovery, we used these models to predict the pharmacokinetic properties for drugs in the NCATS Inxight Drugs database. In addition, we employed the developed models to predict the pharmacokinetic properties of all compounds in the DrugBank. All models described in this paper have been integrated and made publicly available via the PhaKinPro Web-portal that can be accessed at https://phakinpro.mml.unc.edu/.

Visible-Light-Induced Radical Sulfonylative-Cyclization Cascade of 1,6-Enynol Derivatives with Sulfinic Acids: A Sustainable Approach for the Synthesis of 2,3-Disubstituted Benzoheteroles

Benzoheteroles are promising structural scaffolds in the realm of medicinal chemistry, but sustainable synthesis of 2,3-difunctionalized benzoheterole derivatives is still in high demand. Indeed, we have conceptually rationalized the intrinsic reactivity of propargylic-enyne systems for the flexible construction of 2,3-disubstituted benzoheteroles through radical sulfonylative-cyclization cascade under organophotoredox catalysis. We hereby report an efficient visible-light-induced sulfonyl radical-triggered cyclization of 1,6-enynols with sulfinic acids under the dual catalytic influence of 4CzIPN and NiBr2⋅DME, which led to the formation of 2,3-disubstituted benzoheteroles in good to high yields. Additionally, the Rose Bengal (RB)-catalyzed radical sulfonylative-cycloannulation of acetyl-derived 1,6-enynols with sulfinic acids under blue LED irradiation allowed to access 3-(E-styryl)-derived benzofurans and benzothiophenes in moderate to good yields. The scope and limitations of the present strategies were successfully established using different classes of 1,6-enynols and sulfinic acids bearing various sensitive functional groups, yielding the desired products in a highly stereoselective fashion. Plausible mechanistic pathways were also proposed based on the current experimental and control experiments.

Advancing Adverse Drug Reaction Prediction with Deep Chemical Language Model for Drug Safety Evaluation

The accurate prediction of adverse drug reactions (ADRs) is essential for comprehensive drug safety evaluation. Pre-trained deep chemical language models have emerged as powerful tools capable of automatically learning molecular structural features from large-scale datasets, showing promising capabilities for the downstream prediction of molecular properties. However, the performance of pre-trained chemical language models in predicting ADRs, especially idiosyncratic ADRs induced by marketed drugs, remains largely unexplored. In this study, we propose MoLFormer-XL, a pre-trained model for encoding molecular features from canonical SMILES, in conjunction with a CNN-based model to predict drug-induced QT interval prolongation (DIQT), drug-induced teratogenicity (DIT), and drug-induced rhabdomyolysis (DIR). Our results demonstrate that the proposed model outperforms conventional models applied in previous studies for predicting DIQT, DIT, and DIR. Notably, an analysis of the learned linear attention maps highlights amines, alcohol, ethers, and aromatic halogen compounds as strongly associated with the three types of ADRs. These findings hold promise for enhancing drug discovery pipelines and reducing the drug attrition rate due to safety concerns.

Discovery of Clinical Candidate GLPG3970: A Potent and Selective Dual SIK2/SIK3 Inhibitor for the Treatment of Autoimmune and Inflammatory Diseases

The salt-inducible kinases (SIKs) SIK1, SIK2, and SIK3 belong to the adenosine monophosphate-activated protein kinase (AMPK) family of serine/threonine kinases. SIK inhibition represents a new therapeutic approach modulating pro-inflammatory and immunoregulatory pathways that holds potential for the treatment of inflammatory diseases. Here, we describe the identification of GLPG3970 (32), a first-in-class dual SIK2/SIK3 inhibitor with selectivity against SIK1 (IC50 of 282.8 nM on SIK1, 7.8 nM on SIK2 and 3.8 nM on SIK3). We outline efforts made to increase selectivity against SIK1 and improve CYP time-dependent inhibition properties through the structure-activity relationship. The dual activity of 32 in modulating the pro-inflammatory cytokine TNFα and the immunoregulatory cytokine IL-10 is demonstrated in vitro in human primary myeloid cells and human whole blood, and in vivo in mice stimulated with lipopolysaccharide. Compound 32 shows dose-dependent activity in disease-relevant mouse pharmacological models.

Research progress on the pharmacological mechanism, in vivo metabolism and structural modification of Erianin

Erianin is an important bibenzyl compound in dendrobium and has a wide spectrum of pharmacological properties. Since Erianin was discovered, abundant results have been achieved in the in vitro synthesis, structural modification, and pharmacological mechanism research. Researchers have developed a series of simple and efficient in vitro synthesis methods to improve the shortcomings of poor water solubility by replacing the chemical structure or coating it in nanomaterials. Erianin has a broad anti-tumor spectrum and significant anti-tumor effects. In addition, Erianin also has pharmacological actions like immune regulation, anti-inflammatory, and anti-angiogenesis. A comprehensive understanding of the synthesis, metabolism, structural modification, and pharmacological action pathways of Erianin is of great value for the utilization of Erianin. Therefore, this review conducts a relatively systematic look back at Erianin from the above four aspects, to give a reference for the evolvement and further appliance of Erianin.

Deconvoluting low yield from weak potency in direct-to-biology workflows with machine learning

High throughput and rapid biological evaluation of small molecules is an essential factor in drug discovery and development. Direct-to-biology (D2B), whereby compound purification is foregone, has emerged as a viable technique in time efficient screening, specifically for PROTAC design and biological evaluation. However, one notable limitation is the prerequisite of high yielding reactions to ensure the desired compound is indeed the compound responsible for biological activity. Herein, we report a machine learning based yield-assay deconfounder capable of deconvoluting low yield from low potency to identify false negatives. We validated this approach by identifying promising SARS-CoV-2 main protease inhibitors with nanomolar activity that rivaled potency observed from the standard D2B workflow. Furthermore, we show how our framework can be utilized in a broad, in silico screen to produce compounds of similar potency as a D2B assay.

Role of microsomal metabolism in bromfenac-induced cytotoxicity

This study delves into the intricate mechanisms underlying drug-induced liver injury (DILI) with a specific focus on bromfenac, the withdrawn nonsteroidal anti-inflammatory drug. DILI is a pervasive concern in drug development, prompting market withdrawals and posing significant challenges to healthcare. Despite the withdrawal of bromfenac due to DILI, the exact role of its microsomal metabolism in inducing hepatotoxicity remains unclear. Herein, employing HepG2 cells with human liver microsomes and UDP-glucuronic acid (UDPGA), our investigation revealed a substantial increase in bromfenac-induced cytotoxicity in the presence of UDPGA, pointing to the significance of UDP-glucuronosyltransferase (UGT)-dependent metabolism in augmenting toxicity. Notably, among the recombinant UGTs examined, UGT2B7 emerged as a pivotal enzyme in the metabolic activation of bromfenac. Metabolite identification studies disclosed the formation of reactive intermediates, with bromfenac indolinone (lactam) identified as a potential mediator of hepatotoxic effects. Moreover, in cytotoxicity experiments, the toxicity of bromfenac lactam exhibited a 34-fold increase, relative to bromfenac. The toxicity of bromfenac lactam was mitigated by nicotinamide adenine dinucleotide phosphate-dependent metabolism. This finding underscores the role of UGT-dependent metabolism in generating reactive metabolites that contribute to the observed hepatotoxicity associated with bromfenac. Understanding these metabolic pathways and the involvement of specific enzymes, such as UGT2B7, provides crucial insights into the mechanisms of bromfenac-induced liver injury. In conclusion, this research sheds light on the metabolic intricacies leading to cytotoxicity induced by bromfenac, especially emphasizing the role of UGT-dependent metabolism and the formation of reactive intermediates like bromfenac lactam. These findings offer insight into the mechanistic basis of DILI and emphasize the importance of understanding metabolism-mediated toxicity.

Rapid sp3-Enriched Scaffold Generation via a Selective Aziridine Amide Ring-Opening Reaction

Sp3-enriched small molecules play a critical role in developing drug candidates. While designing analogues with greater sp3 character, a methodology utilizing a less explored cyclic-aziridine amide ring-opening reaction to generate sp3-enriched scaffolds has been developed and reported. This methodology enables rapid access to substructures with higher fsp3 values, attracting greater attention within the past few decades. The reaction exhibits a wide reaction scope, featuring a highly sterically hindered phenolic ether, thiophenolic ethers, protected aniline formations, and aliphatic/heteroaromatic ring-containing aziridine amides as substrates. Additionally, this reaction provides access to congested tertiary ether formations through regioselective transformation, applicable to an extensive range of drug discovery targets, construction of complex small molecules, and natural product syntheses. The scaffolds developed show improved physicochemical properties.

Structure-Based Design of AG-946, a Pyruvate Kinase Activator

Pyruvate kinase (PK) is the enzyme that catalyzes the conversion of phosphoenolpyruvate and adenosine diphosphate to pyruvate and adenosine triphosphate in glycolysis and plays a crucial role in regulating cell metabolism. We describe the structure-based design of AG-946, an activator of PK isoforms, including red blood cell-specific forms of PK (PKR). This was designed to have a pseudo-C2-symmetry matching its allosteric binding site on the PK enzyme, which increased its potency toward PKR while reducing activity against off-targets observed from the original scaffold. AG-946 (1) demonstrated activation of human wild-type PK (half-maximal activation concentration [AC50 ]=0.005 μM) and a panel of mutated PK proteins (K410E [AC50 =0.0043 μM] and R510Q [AC50 =0.0069 μM]), (2) displayed a significantly longer half-time of activation (>150-fold) compared with 6-(3-methoxybenzyl)-4-methyl-2-(methylsulfinyl)-4,6-dihydro-5H-thieno[2',3':4,5]pyrrolo[2,3-d]pyridazin-5-one, and (3) stabilized PKR R510Q, an unstable mutant PKR enzyme, and preserved its catalytic activity under increasingly denaturing conditions. As a potent, oral, small-molecule allosteric activator of wild-type and mutant PKR, AG-946 was advanced to human clinical trials.

Involvement of Extracellular Vesicles in the Proinflammatory Response to Clozapine: Implications for Clozapine-Induced Agranulocytosis

Most idiosyncratic drug reactions (IDRs) appear to be immune-mediated, but mechanistic events preceding severe reaction onset remain poorly defined. Damage-associated molecular patterns (DAMPs) may contribute to both innate and adaptive immune phases of IDRs, and changes in extracellular vesicle (EV) cargo have been detected post-exposure to several IDR-associated drugs. To explore the hypothesis that EVs are also a source of DAMPs in the induction of the immune response preceding drug-induced agranulocytosis, the proteome and immunogenicity of clozapine- (agranulocytosis-associated drug) and olanzapine- (non-agranulocytosis-associated drug) exposed EVs were compared in two preclinical models: THP-1 macrophages and Sprague-Dawley rats. Compared with olanzapine, clozapine induced a greater increase in the concentration of EVs enriched from both cell culture media and rat serum. Moreover, treatment of drug-naïve THP-1 cells with clozapine-exposed EVs induced an inflammasome-dependent response, supporting a potential role for EVs in immune activation. Proteomic and bioinformatic analyses demonstrated an increased number of differentially expressed proteins with clozapine that were enriched in pathways related to inflammation, myeloid cell chemotaxis, wounding, transforming growth factor-β signaling, and negative regulation of stimuli response. These data indicate that, although clozapine and olanzapine exposure both alter the protein cargo of EVs, clozapine-exposed EVs carry mediators that exhibit significantly greater immunogenicity. Ultimately, this supports the working hypothesis that drugs associated with a risk of IDRs induce cell stress, release of proinflammatory mediators, and early immune activation that precedes severe reaction onset. Further studies characterizing EVs may elucidate biomarkers that predict IDR risk during development of drug candidates. SIGNIFICANCE STATEMENT: This work demonstrates that clozapine, an idiosyncratic drug-induced agranulocytosis (IDIAG)-associated drug, but not olanzapine, a safer structural analogue, induces an acute proinflammatory response and increases extracellular vesicle (EV) release in two preclinical models. Moreover, clozapine-exposed EVs are more immunogenic, as measured by their ability to activate inflammasomes, and contain more differentially expressed proteins, highlighting a novel role for EVs during the early immune response to clozapine and enhancing our mechanistic understanding of IDIAG and other idiosyncratic reactions.

Evidence for cytochrome P450 3A4-mediated metabolic activation of SCO-267

SCO-267 is a potent G-protein-coupled receptor 40 agonist that is undergoing clinical development for the treatment of type 2 diabetes mellitus. The current work was undertaken to investigate the bioactivation potential of SCO-267 in vitro and in vivo. Three SCO-267-derived glutathione (GSH) conjugates (M1-M3) were found both in rat and human liver microsomal incubations supplemented with GSH and nicotinamide adenine dinucleotide phosphate. Two GSH conjugates (M1-M2) together with two N-acetyl-cysteine conjugates (M4-M5) were detected in the bile of rats receiving SCO-267 at 10 mg/kg. The identified conjugates suggested the generation of quinone-imine and ortho-quinone intermediates. CYP3A4 was demonstrated to primarily catalyze the bioactivation of SCO-267. In addition, SCO-267 concentration-, time-, and NADPH-dependently inactivated CYP3A in human liver microsomes using testosterone as a probe substrate, along with KI and kinact values of 4.91 μM and 0.036 min-1 , respectively. Ketoconazole (a competitive inhibitor of CYP3A) displayed no significant protective effect on SCO-267-induced CYP3A inactivation. However, inclusion of GSH showed significant protection. These findings revealed that SCO-267 undergoes a facile CYP3A4-catalyzed bioactivation with the generation of quinone-imine and ortho-quinone intermediates, which were assumed to be involved in SCO-267 induced CYP3A inactivation. These findings provide further insight into the bioactivation pathways involved in the generation of reactive, potentially toxic metabolites of SCO-267. Further studies are needed to evaluate the influence of SCO-267 metabolism on the safety of this drug in vivo.

Metabolic bioactivation of antidepressants: advance and underlying hepatotoxicity

Many drugs that serve as first-line medications for the treatment of depression are associated with severe side effects, including liver injury. Of the 34 antidepressants discussed in this review, four have been withdrawn from the market due to severe hepatotoxicity, and others carry boxed warnings for idiosyncratic liver toxicity. The clinical and economic implications of antidepressant-induced liver injury are substantial, but the underlying mechanisms remain elusive. Drug-induced liver injury may involve the host immune system, the parent drug, or its metabolites, and reactive drug metabolites are one of the most commonly referenced risk factors. Although the precise mechanism by which toxicity is induced may be difficult to determine, identifying reactive metabolites that cause toxicity can offer valuable insights for decreasing the bioactivation potential of candidates during the drug discovery process. A comprehensive understanding of drug metabolic pathways can mitigate adverse drug-drug interactions that may be caused by elevated formation of reactive metabolites. This review provides a comprehensive overview of the current state of knowledge on antidepressant bioactivation, the metabolizing enzymes responsible for the formation of reactive metabolites, and their potential implication in hepatotoxicity. This information can be a valuable resource for medicinal chemists, toxicologists, and clinicians engaged in the fields of antidepressant development, toxicity, and depression treatment.

Deep Learning Algorithm Based on Molecular Fingerprint for Prediction of Drug-Induced Liver Injury

Drug-induced liver injury (DILI) is one the rare adverse drug reaction (ADR) and multifactorial endpoints. Current preclinical animal models struggle to anticipate it, and in silico methods have emerged as a way with significant potential for doing so. In this study, a high-quality dataset of 1573 compounds was assembled. The 48 classification models, which depended on six different molecular fingerprints, were built via deep neural network (DNN) and seven machine learning algorithms. Comparing the results of the DNN and machine learning models, the optional performing model was found as the one developed based on the DNN with ECFP_6 as input, which achieved the area under the receiver operating characteristic curve (AUC) of 0.713, balanced accuracy (BA) of 0.680, and F1 of 0.753. In addition, we used the SHapley Additive exPlanations (SHAP) algorithm to interpret the models, identified the crucial structural fragments related to DILI risk, and selected the top ten substructures with the highest contribution rankings to serve as warning indicators for subsequent drug hepatotoxicity screening studies. The study demonstrates that the DNN models developed based on molecular fingerprints can be a trustworthy and efficient tool for determining the risk of DILI during the pre-development of novel medications.

Evaluation of the Drug-Induced Liver Injury Potential of Saxagliptin through Reactive Metabolite Identification in Rats

A liver injury was recently reported for saxagliptin, which is a dipeptidyl peptidase-4 (DPP-4) inhibitor. However, the underlying mechanisms of saxagliptin-induced liver injury remain unknown. This study aimed to evaluate whether saxagliptin, a potent and selective DPP-4 inhibitor that is globally used for treating type 2 diabetes mellitus, binds to the nucleophiles in vitro. Four DPP-4 inhibitors, including vildagliptin, were evaluated for comparison. Only saxagliptin and vildagliptin, which both contain a cyanopyrrolidine group, quickly reacted with L-cysteine to enzyme-independently produce thiazolinic acid metabolites. This saxagliptin-cysteine adduct was also found in saxagliptin-administered male Sprague-Dawley rats. In addition, this study newly identified cysteinyl glycine conjugates of saxagliptin and 5-hydroxysaxagliptin. The observed metabolic pathways were hydroxylation and conjugation with cysteine, glutathione, sulfate, and glucuronide. In summary, we determined four new thiazoline-containing thiol metabolites (cysteine and cysteinylglycine conjugates of saxagliptin and 5-hydroxysaxagliptin) in saxagliptin-administered male rats. Our results reveal that saxagliptin can covalently bind to the thiol groups of cysteine residues of endogenous proteins in vivo, indicating the potential for saxagliptin to cause drug-induced liver injury.

Rapid Access to Densely Functionalized Cyclopentenyl Sulfoximines through a Sc-Catalyzed Aza-Piancatelli Reaction

Sulfoximines make up a class of compounds of growing interest for crop science and medicinal chemistry, but methods for directly incorporating them into complex molecular scaffolds are lacking. Here we report a scandium-catalyzed variant of the aza-Piancatelli cyclization that can directly incorporate sulfoximines as nucleophiles rather than the classical aniline substrates. Starting from 2-furylcarbinols and sulfoximines, the reaction provides direct access to 4-sulfoximinocyclopentenones, a new scaffold bearing cyclopentenone and sulfoximine motifs, both of interest for bioactive compounds.

InterDILI: interpretable prediction of drug-induced liver injury through permutation feature importance and attention mechanism

Safety is one of the important factors constraining the distribution of clinical drugs on the market. Drug-induced liver injury (DILI) is the leading cause of safety problems produced by drug side effects. Therefore, the DILI risk of approved drugs and potential drug candidates should be assessed. Currently, in vivo and in vitro methods are used to test DILI risk, but both methods are labor-intensive, time-consuming, and expensive. To overcome these problems, many in silico methods for DILI prediction have been suggested. Previous studies have shown that DILI prediction models can be utilized as prescreening tools, and they achieved a good performance. However, there are still limitations in interpreting the prediction results. Therefore, this study focused on interpreting the model prediction to analyze which features could potentially cause DILI. For this, five publicly available datasets were collected to train and test the model. Then, various machine learning methods were applied using substructure and physicochemical descriptors as inputs and the DILI label as the output. The interpretation of feature importance was analyzed by recognizing the following general-to-specific patterns: (i) identifying general important features of the overall DILI predictions, and (ii) highlighting specific molecular substructures which were highly related to the DILI prediction for each compound. The results indicated that the model not only captured the previously known properties to be related to DILI but also proposed a new DILI potential substructural of physicochemical properties. The models for the DILI prediction achieved an area under the receiver operating characteristic (AUROC) of 0.88-0.97 and an area under the Precision-Recall curve (AUPRC) of 0.81-0.95. From this, we hope the proposed models can help identify the potential DILI risk of drug candidates at an early stage and offer valuable insights for drug development.

The validation of new CHD1L inhibitors as a therapeutic strategy for cancer

Chromodomain helicase DNA-binding protein 1 like (CHD1L) is an oncogene that promotes tumor progression, metastasis, and multidrug resistance. CHD1L expression is indicative of poor outcomes and low survival in cancer patients with various cancer types. Herein, we report a set of CHD1L inhibitors (CHD1Li) discovered from high-throughput screening and evaluated using enzyme inhibition, 3D tumor organoid cytotoxicity and mechanistic assays. The structurally distinct compounds 8-11 emerged as hits with promising bioactivity by targeting CHD1L. CHD1Li were further examined for their stability in human and mouse liver microsomes, which showed compounds 9 and 11 to be the most metabolically stable. Additionally, molecular modeling studies of CHD1Li with the target protein shed light on key pharmacophore features driving CHD1L binding. Taken together, these results expand the chemical space of CHD1Li as a potential targeted therapy for colorectal cancer and other cancers.

Species-specific Bioactivation of Morpholines as a Causative of Drug Induced Liver Injury Observed in Monkeys

BACKGROUND

Everolimus, an allosteric mechanistic target of rapamycin (mTOR) inhibitor, recently demonstrated the therapeutic value of mTOR inhibitors for Central Nervous System (CNS) indications driven by hyperactivation of mTOR. A newer, potent brain-penetrant analog of everolimus, referred to as (1) in this manuscript [(S)-3-methyl-4-(7-((R)-3-methylmorpholino)-2- (thiazol-4-yl)-3H-imidazo[4,5-b]pyridin-5-yl)morpholine,(1)] catalytically inhibits mTOR function in the brain and increases the lifespan of mice with neuronal mTOR hyperactivation.

INTRODUCTION

Early evaluation of the safety of 1 was conducted in cynomolgus monkeys in which oral doses were administered to three animals in a rising-dose fashion (from 2 to 30 mg/kg/day). 1 produced severe toxicity including the evidence of hepatic toxicity, along with non-dose proportional increases in drug exposure. Investigations of cross-species hepatic bioactivation of 1 were conducted to assess whether the formation of reactive drug metabolites was associated with the mechanism of liver toxicity.

METHODS

1 contained two morpholine rings known as structural alerts and can potentially form reactive intermediates through oxidative metabolism. Bioactivation of 1 was investigated in rat, human and monkey liver microsomes fortified with trapping agents such as methoxylamine or potassium cyanide.

RESULTS

Our results suggest that bioactivation of the morpholine moieties to reactive intermediates may have been involved in the mechanism of liver toxicity observed with 1. Aldehyde intermediates trappable by methoxylamine were identified in rat and monkey liver microsomal studies. In addition, a total of four cyano conjugates arising from the formation of iminium ion intermediates were observed and identified. These findings may potentially explain the observed monkey toxicity. Interestingly, methoxylamine or cyano adducts of 1 were not observed in human liver microsomes.

CONCLUSION

The bioactivation of 1 appears to be species-specific. Circumstantial evidence for the toxicity derived from 1 point to the formation of iminium ion intermediates trappable by cyanide in monkey liver microsomes. The cyano conjugates were only observed in monkey liver microsomes, potentially pointing to cause at least the hepatotoxicity observed in monkeys. In contrast, methoxylamine conjugates were detected in both rat and monkey liver microsomes, with only a trace amount in human liver microsomes. Cyano conjugates were not observed in human liver microsomes, challenging the team on the drugability and progressivity of 1 through drug development. The mechanisms for drug-induced liver toxicity are multifactorial. These results are highly suggestive that the iminium ion may be an important component in the mechanism of liver toxicity 1 observed in the monkey.

The Importance of Tracking "Missing" Metabolites: How and Why?

Technologies currently employed to find and identify drug metabolites in complex biological matrices generally yield results that offer a comprehensive picture of the drug metabolite profile. However, drug metabolites can be missed or are captured only late in the drug development process. This could be due to a variety of factors, such as metabolism that results in partial loss of the molecule, covalent bonding to macromolecules, the drug being metabolized in specific human tissues, or poor ionization in a mass spectrometer. These scenarios often draw a great deal of attention from chemistry, safety assessment, and pharmacology. This review will summarize scenarios of missing metabolites, why they are missing, and associated uncovering strategies from deeper investigations. Uncovering previously missed metabolites can have ramifications in drug development with toxicological and pharmacological consequences, and knowledge of these can help in the design of new drugs.

Metabolite profiling and identification of enzymes responsible for the metabolism of hirsutine, a major alkaloid from Uncaria rhynchophylla

The in vitro metabolism of hirsutine was determined using liver microsomes and human recombinant cytochrome P450 enzymes. Under the current conditions, a total of 14 phase I metabolites were tentatively identified.Ketoconazole showed significant inhibitory effect on the metabolism of hirsutine. Human recombinant cytochrome P450 enzyme analysis revealed that metabolism of hirsutine was mainly catalysed by CYP3A4.Our data revealed that hirsutine was metabolised via mono-oxygenation, di-oxygenation, N-oxygenation, dehydrogenation, demethylation and hydrolysis.In glutathione (GSH)-supplemented liver microsomes, four GSH adducts were identified. Hirsutine underwent facile P450-mediated metabolic activation, forming reactive 3-methyleneindolenine and iminoquinone intermediates.This study provided valuable information on the metabolic fates of hirsutine in liver microsomes, which would aid in understanding the hepatotoxicity caused by hirsutine or hirsutine-containing herb preparation.

Discovery of a Hydroxylamine-Based Brain-Penetrant EGFR Inhibitor for Metastatic Non-Small-Cell Lung Cancer

Metastases to the brain remain a significant problem in lung cancer, as treatment by most small-molecule targeted therapies is severely limited by efflux transporters at the blood-brain barrier (BBB). Here, we report the discovery of a selective, orally bioavailable, epidermal growth factor receptor (EGFR) inhibitor, 9, that exhibits high brain penetration and potent activity in osimertinib-resistant cell lines bearing L858R/C797S and exon19del/C797S EGFR resistance mutations. In vivo, 9 induced tumor regression in an intracranial patient-derived xenograft (PDX) murine model suggesting it as a potential lead for the treatment of localized and metastatic non-small-cell lung cancer (NSCLC) driven by activating mutant bearing EGFR. Overall, we demonstrate that an underrepresented functional group in medicinal chemistry, the trisubstituted hydroxylamine moiety, can be incorporated into a drug scaffold without the toxicity commonly surmised to accompany these units, all while maintaining potent biological activity and without the molecular weight creep common to drug optimization campaigns.

GeoDILI: A Robust and Interpretable Model for Drug-Induced Liver Injury Prediction Using Graph Neural Network-Based Molecular Geometric Representation

Drug-induced liver injury (DILI) is a significant cause of drug failure and withdrawal due to liver damage. Accurate prediction of hepatotoxic compounds is crucial for safe drug development. Several DILI prediction models have been published, but they are built on different data sets, making it difficult to compare model performance. Moreover, most existing models are based on molecular fingerprints or descriptors, neglecting molecular geometric properties and lacking interpretability. To address these limitations, we developed GeoDILI, an interpretable graph neural network that uses a molecular geometric representation. First, we utilized a geometry-based pretrained molecular representation and optimized it on the DILI data set to improve predictive performance. Second, we leveraged gradient information to obtain high-precision atomic-level weights and deduce the dominant substructure. We benchmarked GeoDILI against recently published DILI prediction models, as well as popular GNN models and fingerprint-based machine learning models using the same data set, showing superior predictive performance of our proposed model. We applied the interpretable method in the DILI data set and derived seven precise and mechanistically elucidated structural alerts. Overall, GeoDILI provides a promising approach for accurate and interpretable DILI prediction with potential applications in drug discovery and safety assessment. The data and source code are available at GitHub repository (https://github.com/CSU-QJY/GeoDILI).

Metabophore-mediated retro-metabolic ('MeMeReMe') approach in drug design

Preclinical toxicity assessments of new drugs require the use of in silico prediction techniques as ethics, cost, time, and complexity limit in vitro and in vivo methods. This review discusses the fundamental concepts of biophores especially toxicophores and their detection methodologies, tools and techniques, as well as ongoing challenges, and methods for overcoming them. This will guide the design community in manipulating lead compounds via a pre-determined pathway based on the MeMeReMe approach. The ideas discussed will be useful both for predicting toxicity and for de-risking leads through optimization.

Development and validation for bioanalysis of VK2809, its active metabolite VK2809A and glutathione-conjugated metabolite MB06588 in rat liver using LC-MS/MS

VK2809 is a promising drug candidate in Phase II clinical trials for the treatment of non-alcoholic steatohepatitis (NASH). It is a prodrug with a HepDirect strategy, which can achieve selective hepatic metabolic activation, generating an active metabolite VK2809A as a potent and selective agonist for thyroid hormone receptor beta (TRβ), a concomitant reactive metabolite VK2809B, and a glutathione (GSH) conjugate MB06588. Currently, there is no convenient and sensitive bioanalytical method for the simultaneous determination of the above three metabolites. Herein, we established an LC-MS/MS method to separate VK2809 and its metabolites on the XSelect HSS T3 column and quantified them in negative electrospray ionization mode. Subsequently, several factors were investigated such as the use of 60% acetonitrile for homogenization to stabilize the analytes, the addition of 20 mM glutathione for the derivation of VK2809B, and the protein precipitation with methanol containing Sobetirome as the internal standard (IS). The method exhibited good linearity for all compounds (19.4-388.4 nM for VK2809; 27.4-2744.4 nM for VK2809A and 10.6-211.0 nM for MB06588) with great correlation coefficients (r > 0.996). The method validation also demonstrated acceptable precision (RSD < 13.0% for VK2809, RSD < 7.9% for VK2809A, RSD < 14.4% for MB06588) and accuracy (92.7%-103% for VK2809, 91.2%-107.3% for VK2809A, 96%-106.7% for MB06588). The matrix effect, recovery, and stability were also suitable to determine all the analytes. This method is suitable for the bioanalysis of VK2809 and its metabolites and has been successfully applied to the study of intrahepatic exposure in rats. It is expected to be further practiced in drug design, optimization, and metabolism study in the following research.

Using Proteins As Markers for Anabolic Steroid Abuse: A New Perspective in Doping Control?

Drug toxicity is a major concern and has motivated numerous studies to elucidate specific adverse mechanisms, with acetaminophen being the favorite candidate in toxicology studies. Conversely, androgenic anabolic steroids (AASs) also represent a severe public health issue in sports for elite and non-elite athletes. Supraphysiological dosages of AASs are associated with various adverse effects, from cardiovascular to neurological repercussions including liver dysfunction. Yet, few studies have addressed the toxicity of anabolic steroids, and a significant amount of work will be needed to elucidate and understand steroid toxicity properly. This Perspective suggests ideas on how proteomics and liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) can contribute to (1) pinpoint serum proteins affected by substantial doses of anabolic steroids that would represent interesting novel candidates for routine testing and (2) provide additional knowledge on androgenic anabolic steroid toxicity to help raise awareness on the harmful effects.

Machine Learning-Based Prediction of Drug-Induced Hepatotoxicity: An OvA-QSTR Approach

Drug-induced hepatotoxicity, also known as drug-induced liver injury (DILI), is among the possible adverse effects of pharmacotherapy. This clinical condition is accepted as one of the factors leading to patient mortality and morbidity. The LiverTox database was built by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) to predict potential liver damage from medications and take appropriate precautions. The database has classified medicines into seven risk categories (A, B, C, D, E, E*, and X) to avoid medicine-induced liver toxicity. The hepatic damage risk decreases from group A to group E. This study did not include the E* and X classes because they contained unverified and unknown data groups. Our study aims to predict potential liver damage of new drug molecules without using experimental animals. We predict which of the LiverTox risk category drugs with unknown liver toxicity potential will fall into using our one-vs-all quantitative structure-toxicity relationship (OvA-QSTR) model. Our dataset, consisting of 678 organic drug molecules from different pharmacological classes, was collected from LiverTox. The OvA-QSTR models implemented by Bayesian Network (BayesNet) performed well based on the selected descriptors, with the precision-recall curve (PRC) areas ranging from 0.718 to 0.869. Our OvA-QSTR models provide a reliable premarketing risk evaluation of pharmaceutical-induced liver damage potential and offer predictions for different risk levels in DILI.

Arylcyanomethylenequinone Oximes: An Overview of Synthesis, Chemical Transformations, and Biological Activity

Quinone methides are a class of biologically active compounds that can be used in medicine as antibacterial, antifungal, antiviral, antioxidant, and anti-inflammatory agents. In addition, quinone methides have the potential to be used as pesticides, dyes, and additives for rubber and plastics. In this paper, we discuss a subclass of quinone methides: methylenequinone oximes. Although the first representatives of the subgroup were synthesized in the distant past, they still need to be additionally studied, while their chemistry, biological properties, and perspective of practical applications require to be comprehensively summarised. Based on the analysis of the literature, it can be concluded that methylenequinone oximes exhibit a diversified profile of properties and outstanding potential as new drug candidates and reagents in organic synthesis, both of electrophilic and nucleophilic nature, worthy of wide-ranging further research.

Identifying chemicals based on receptor binding/bioactivation/mechanistic explanation associated with potential to elicit hepatotoxicity and to support structure activity relationship-based read-across

The liver is the most common target organ in toxicology studies. The development of chemical structural alerts for identifying hepatotoxicity will play an important role in in silico model prediction and help strengthen the identification of analogs used in structure activity relationship (SAR)- based read-across. The aim of the current study is development of an SAR-based expert-system decision tree for screening of hepatotoxicants across a wide range of chemistry space and proposed modes of action for clustering of chemicals using defined core chemical categories based on receptor-binding or bioactivation. The decision tree is based on ∼ 1180 different chemicals that were reviewed for hepatotoxicity information. Knowledge of chemical receptor binding, metabolism and mechanistic information were used to group these chemicals into 16 different categories and 102 subcategories: four categories describe binders to 9 different receptors, 11 categories are associated with possible reactive metabolites (RMs) and there is one miscellaneous category. Each chemical subcategory has been associated with possible modes of action (MOAs) or similar key structural features. This decision tree can help to screen potential liver toxicants associated with core structural alerts of receptor binding and/or RMs and be used as a component of weight of evidence decisions based on SAR read-across, and to fill data gaps.

Investigation of Fenebrutinib Metabolism and Bioactivation Using MS3 Methodology in Ion Trap LC/MS

Fenebrutinib is an orally available Bruton tyrosine kinase inhibitor. It is currently in multiple phase III clinical trials for the management of B-cell tumors and autoimmune disorders. Elementary in-silico studies were first performed to predict susceptible sites of metabolism and structural alerts for toxicities by StarDrop WhichP450™ module and DEREK software; respectively. Fenebrutinib metabolites and adducts were characterized in-vitro in rat liver microsomes (RLM) using MS3 method in Ion Trap LC-MS/MS. Formation of reactive and unstable intermediates was explored using potassium cyanide (KCN), glutathione (GSH) and methoxylamine as trapping nucleophiles to capture the transient and unstable iminium, 6-iminopyridin-3(6H)-one and aldehyde intermediates, respectively, to generate a stable adducts that can be investigated and analyzed using mass spectrometry. Ten phase I metabolites, four cyanide adducts, five GSH adducts and six methoxylamine adducts of fenebrutinib were identified. The proposed metabolic reactions involved in formation of these metabolites are hydroxylation, oxidation of primary alcohol to aldehyde, n-oxidation, and n-dealkylation. The mechanism of reactive intermediate formation of fenebrutinib can provide a justification of the cause of its adverse effects. Formation of iminium, iminoquinone and aldehyde intermediates of fenebrutinib was characterized. N-dealkylation followed by hydroxylation of the piperazine ring is proposed to cause the bioactivation to iminium intermediates captured by cyanide. Oxidation of the hydroxymethyl group on the pyridine moiety is proposed to cause the generation of reactive aldehyde intermediates captures by methoxylamine. N-dealkylation and hydroxylation of the pyridine ring is proposed to cause formation of iminoquinone reactive intermediates captured by glutathione. FBB and several phase I metabolites are bioactivated to fifteen reactive intermediates which might be the cause of adverse effects. In the future, drug discovery experiments utilizing this information could be performed, permitting the synthesis of new drugs with better safety profile. Overall, in silico software and in vitro metabolic incubation experiments were able to characterize the FBB metabolites and reactive intermediates using the multistep fragmentation capability of ion trap mass spectrometry.

Preclinical evaluation of chemically reactive metabolites and mitigation of bioactivation in drug discovery

The formation of reactive metabolites (RMs) is thought to be one of the pathogeneses for some idiosyncratic adverse drug reactions (IADRs) which are considered one of the leading causes of some drug attritions and/or recalls. Minimizing or eliminating the formation of RMs via chemical modification is a useful tactic to reduce the risk of IADRs and time-dependent inhibition (TDI) of cytochrome P450 enzymes (CYPs). The RMs should be carefully handled before making a go-no-go decision. Herein, we highlight the role of RMs in the occurrence of IADRs and CYP TDI, the risk of structural alerts, the approaches of RM assessment at the discovery stage and strategies to minimize or eliminate RM liability. Finally, some considerations for developing a RM-positive drug candidate are suggested.

Mitigating a Bioactivation Liability with an Azetidine-Based Inhibitor of Diacylglycerol Acyltransferase 2 (DGAT2) En Route to the Discovery of the Clinical Candidate Ervogastat

We recently disclosed SAR studies on systemically acting, amide-based inhibitors of diacylglycerol acyltransferase 2 (DGAT2) that addressed metabolic liabilities with the liver-targeted DGAT2 inhibitor PF-06427878. Despite strategic placement of a nitrogen atom in the dialkoxyaromatic ring in PF-06427878 to evade oxidative O-dearylation, metabolic intrinsic clearance remained high due to extensive piperidine ring oxidation as exemplified with compound 1. Piperidine ring modifications through alternate N-linked heterocyclic ring/spacer combination led to azetidine 2 that demonstrated lower intrinsic clearance. However, 2 underwent a facile cytochrome P450 (CYP)-mediated α-carbon oxidation followed by azetidine ring scission, resulting in the formation of ketone (M2) and aldehyde (M6) as stable metabolites in NADPH-supplemented human liver microsomes. Inclusion of GSH or semicarbazide in microsomal incubations led to the formation of Cys-Gly-thiazolidine (M3), Cys-thiazolidine (M5), and semicarbazone (M7) conjugates, which were derived from reaction of the nucleophilic trapping agents with aldehyde M6. Metabolites M2 and M5 were biosynthesized from NADPH- and l-cysteine-fortified human liver microsomal incubations with 2, and proposed metabolite structures were verified using one- and two-dimensional NMR spectroscopy. Replacement of the azetidine substituent with a pyridine ring furnished 8, which mitigated the formation of the electrophilic aldehyde metabolite, and was a more potent DGAT2 inhibitor than 2. Further structural refinements in 8, specifically introducing amide bond substituents with greater metabolic stability, led to the discovery of PF-06865571 (ervogastat) that is currently in phase 2 clinical trials for the treatment of nonalcoholic steatohepatitis.

Phthalazinone-based lactams and cyclic ureas as ROCK2 selective inhibitors

Derivatives of lactam, cyclic urea and carbamate were explored as aniline amide replacements in a series of phthalazinone-based ROCK inhibitors. Potent ROCK2 inhibitors such as 22 were identified with excellent overall kinase selectivity as well as good isoform selectivity over ROCK1.

Exhaustive in silico design and screening of novel antipsychotic compounds with improved pharmacodynamics and blood-brain barrier permeation properties

Antipsychotic drugs or neuroleptics are widely used in the treatment of psychosis as a manifestation of schizophrenia and bipolar disorder. However, their effectiveness largely depends on the blood-brain barrier (BBB) permeation (pharmacokinetics) and drug-receptor pharmacodynamics. Therefore, in this study, we developed and implemented the in silico pipeline to design novel compounds (n = 260) as leads using the standard drug scaffolds with improved PK/PD properties from the standard scaffolds. As a result, the best candidates (n = 3) were evaluated in molecular docking to interact with serotonin and dopamine receptors. Finally, haloperidol (HAL) derivative (1-(4-fluorophenyl)-4-(4-hydroxy-4-{4-[(2-phenyl-1,3-thiazol-4-yl)methyl]phenyl}piperidin-1-yl)butan-1-one) was identified as a "magic shotgun" lead compound with better affinity to the 5-HT2A, 5-HT1D, D2, D3, and 5-HT1B receptors than the control molecule. Additionally, this hit substance was predicted to possess similar BBB permeation properties and much lower toxicological profiles in comparison to HAL. Overall, the proposed rational drug design platform for novel antipsychotic drugs based on the BBB permeation and receptor binding might be an invaluable asset for a medicinal chemist or translational pharmacologist.Communicated by Ramaswamy H. Sarma.

Message Passing Neural Networks Improve Prediction of Metabolite Authenticity

Cytochrome P450 enzymes aid in the elimination of a preponderance of small molecule drugs, but can generate reactive metabolites that may adversely react with protein and DNA and prompt drug candidate attrition or market withdrawal. Previously developed models help understand how these enzymes modify molecule structure by predicting sites of metabolism or characterizing formation of metabolite-biomolecule adducts. However, the majority of reactive metabolites are formed by multiple metabolic steps, and understanding the progenitor molecule's network-level behavior necessitates an integrative approach that blends multiple site of metabolism and structure inference models. Our previously developed tool, XenoNet 1.0, generates metabolic networks, where nodes are molecules and weighted edges are metabolic transformations. We extend XenoNet with a bidirectional message passing neural network that integrates edge feature information and local network structure using edge-conditioned graph convolutions and jumping knowledge to predict the authenticity of inferred Phase I metabolite structures. Our model significantly outperformed prior work and algorithmic baselines on a data set of 311 networks and 6606 intermediates annotated using a chemically diverse set of 20 736 individual in vitro and in vivo reaction records accounting for 92.3% of all human Phase I metabolism in the Accelrys Metabolite Database. Cross-validated predictions resulted in area under the receiver operating characteristic curves of 88.5% and 87.6% for separating experimentally observed and unobserved metabolites at global and network levels, respectively. Further analysis verified robustness to networks of varying depth and breadth, accurate detection of metabolites, such as d,l-methamphetamine, that are experimentally observed or unobserved in different network contexts, extraction of important metabolic subnetworks, and identification of known bioactivation pathways, such as for nimesulide and terbinafine. By exploiting network structures, our approach accurately suggests unreported metabolites for experimental study and may rationalize modifications for avoiding deleterious pathways antecedent to reactive metabolite formation.

Synthesis and Structure-Activity Analysis of Icaritin Derivatives as Potential Tumor Growth Inhibitors of Hepatocellular Carcinoma Cells

The prenylated flavonoid icaritin (ICT, 1), a new drug for treating advanced hepatocellular carcinoma (HCC), was selected as a template to develop more potent inhibitors. An initial semisynthetic modification of ICT was performed to obtain a structure-activity relationship (SAR), which indicated that the cytotoxicity is enhanced by OH-3 rhamnosylation and that OH-7 is an important modification site. Based on the results of the SAR study, 46 N-containing ICT derivatives were synthesized and evaluated as the anti-HCC inhibitors. The results showed that most of the derivatives produced inhibited three HCC cell lines used (Hep3B, HepG2 and SMMC-7721). The modification strategy was validated by 3D-QSAR, which provided information for the further design and optimization of ICT. The most potent compound, 11c, exhibited IC₅₀ values of 7.6 and 3.1 μM against HepG2 and SMMC-7721 cells, respectively, which were more potent than those of ICT and sorafenib, respectively. Further mechanistic studies indicated that 11c caused arrest at the G₀/G₁ phase in the cell cycle and induced cell apoptosis in HepG2 and SMMC-7721 cells.

Riluzole and novel naphthalenyl substituted aminothiazole derivatives prevent acute neural excitotoxic injury in a rat model of temporal lobe epilepsy

Epileptogenic seizures, or status epilepticus (SE), leads to excitotoxic injury in hippocampal and limbic neurons in the kainic acid (KA) animal model of temporal lobe epilepsy (TLE). Here, we have further characterized neural activity regulated methylaminoisobutryic acid (MeAIB)/glutamine transport activity in mature rat hippocampal neurons in vitro that is inhibited by riluzole (IC₅₀ = 1 μM), an anti-convulsant benzothiazole agent. We screened a library of riluzole derivatives and identified SKA-41 followed by a second screen and synthesized several novel chlorinated aminothiazoles (SKA-377, SKA-378, SKA-379) that are also potent MeAIB transport inhibitors in vitro, and brain penetrant following systemic administration. When administered before KA, SKA-378 did not prevent seizures but still protected the hippocampus and several other limbic areas against SE-induced neurodegeneration at 3d. When SKA-377 - 379, (30 mg/kg) were administered after KA-induced SE, acute neural injury in the CA3, CA1 and CA4/hilus was also largely attenuated. Riluzole (10 mg/kg) blocks acute neural injury. Kinetic analysis of SKA-378 and riluzoles' blockade of Ca²⁺-regulated MeAIB transport in neurons in vitro indicates that inhibition occurs via a non-competitive, indirect mechanism. Sodium channel Na_V1.6 antagonism blocks neural activity regulated MeAIB/Gln transport in vitro (IC₅₀ = 60 nM) and SKA-378 is the most potent inhibitor of Na_V1.6 (IC₅₀ = 28 μM) compared to Na_V1.2 (IC₅₀ = 118 μM) in heterologous cells. However, pharmacokinetic analysis suggests that sodium channel blockade may not be the predominant mechanism of neuroprotection here. Riluzole and our novel aminothiazoles are agents that attenuate acute neural hippocampal injury following KA-induced SE and may help to understand mechanisms involved in the progression of epileptic disease.

Discovery of a Novel Potent and Selective HSD17B13 Inhibitor, BI-3231, a Well-Characterized Chemical Probe Available for Open Science

Genome-wide association studies in patients revealed HSD17B13 as a potential new target for the treatment of nonalcoholic steatohepatitis (NASH) and other liver diseases. However, the physiological function and the disease-relevant substrate of HSD17B13 remain unknown. In addition, no suitable chemical probe for HSD17B13 has been published yet. Herein, we report the identification of the novel potent and selective HSD17B13 inhibitor BI-3231. Through high-throughput screening (HTS), using estradiol as substrate, compound 1 was identified and selected for subsequent optimization resulting in compound 45 (BI-3231). In addition to the characterization of compound 45 for its functional, physicochemical, and drug metabolism and pharmacokinetic (DMPK) properties, NAD⁺ dependency was investigated. To support Open Science, the chemical HSD17B13 probe BI-3231 will be available to the scientific community for free via the opnMe platform, and thus can help to elucidate the pharmacology of HSD17B13.

Overview of Adductomics in Toxicology

Adductomics is epidemiology at the molecular level. Untargeted adductomics compares levels of chemical adducts on albumin, hemoglobin, and DNA between healthy and exposed individuals. The goal is to determine a cause-and-effect relationship between chemical exposure and illness. Chemical exposures are not necessarily due to synthetic chemicals but are often due to oxidation products of naturally occurring lipids, for example, 4-hydroxynonenal and acrolein produced by lipid peroxidation of arachidonic and linoleic acids. The preferred method used in adductomics is ultra-high pressure liquid chromatography coupled to with nanoelectrospray tandem mass spectrometry. The mass of the adduct indicates its structure and identifies the chemical. The advantages of molecular epidemiology include information about the many toxicants to which a person is exposed over a period of weeks or months and the relative exposure levels. The disadvantage is the absence of information about the mechanism of toxicity. Untargeted adductomics examines albumin and hemoglobin adducts, which serve as biomarkers of exposure but do not identify the proteins and genes responsible for the toxicity. Targeted adductomics is used when the origin of the toxicity is known. This can be either an adducted protein, such as the butyrylcholinesterase protein modified by nerve agents, or a toxicant, such as acetaminophen. Untargeted adductomics methods have identified potential protein adduct biomarkers of breast cancer, colorectal cancer, childhood leukemia, and lung cancer. Adductomics is a new research area that offers structural insights into chemical exposures and a platform for the discovery of disease biomarkers. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.

Rational Design of a New RXR Agonist Scaffold Enabling Single-Subtype Preference for RXRα, RXRβ, and RXRγ

The three retinoid X receptor subtypes (RXRα, RXRβ, RXRγ) exhibit critical regulatory roles in cell proliferation and differentiation, metabolism, and inflammation. Due to their importance in nuclear receptor signaling, RXRs are widely distributed and pan-RXR agonists cause adverse effects, but the three highly conserved RXR ligand binding sites render the development of subtype-selective ligands a major challenge. We have fused elements of known RXR ligands to obtain a new RXR agonist chemotype on which minor structural modifications enabled the development of tools with single-subtype preference for RXRα, RXRβ, and RXRγ. Molecular modeling indicated different binding conformations and interaction patterns with the RXR LBDs as factors of preferential binding. In a phenotypic adipocyte differentiation experiment, only the RXRα preferential tool enhanced the adipogenic effects of pioglitazone, suggesting this subtype as particularly relevant in adipogenesis and highlighting the set of subtype-preferential RXR agonist tools as suitable for functional cellular studies.

The Role of Myeloperoxidase in Clozapine-Induced Inflammation: A Mechanistic Update for Idiosyncratic Drug-Induced Agranulocytosis

The risk of idiosyncratic drug-induced agranulocytosis (IDIAG) markedly constrains the use of clozapine, a neuroleptic with unparalleled efficacy. Most clozapine patients experience an early inflammatory response, likely a necessary step in IDIAG onset. However, most patients do not progress to IDIAG, presumably because of the requirement of specific human leukocyte antigen (HLA) haplotypes, T cell receptors, and other unknown factors. We established that clozapine activates inflammasomes and that myeloperoxidase bioactivation of clozapine generates neoantigens, but the connection between these early mechanistic events remained unknown and, thus, was the aim of this work. We found that the myeloperoxidase inhibitor PF-1355 attenuated myeloperoxidase activity in phorbol myristate acetate (PMA)-differentiated THP-1 macrophages, and it also attenuated clozapine-induced release of inflammatory mediators (e.g., IL-1β, CXCL1, and C-reactive protein). In vivo, pretreatment of Sprague Dawley rats with PF-1355 significantly attenuated clozapine-induced increases in neutrophil mobilization from the bone marrow to the blood and spleen, as determined using differential blood counts and flow cytometry. Moreover, the clozapine-triggered release of inflammatory mediators (e.g., IL-1β, calprotectin, CXCL1, and α-1-acid glycoprotein) from the liver, spleen, and bone marrow was dampened by myeloperoxidase inhibition. These data support the working hypothesis that oxidation of clozapine to a reactive metabolite by myeloperoxidase is critical for induction of the inflammatory response to clozapine. Ultimately, a better mechanistic understanding of the early events involved in the immune response to clozapine may elucidate ways to prevent IDIAG, enabling safer, more frequent therapeutic use of this and potentially other highly efficacious drugs.

Practical application of the interim internal threshold of toxicological concern (iTTC): a case study based on clinical data

We present a case study that provides a practical step-by-step example of how the internal Threshold of Toxicological Concern (iTTC) can be used as a tool to refine a TTC-based assessment for dermal exposures to consumer products. The case study uses a theoretical scenario where there are no systemic toxicity data for the case study chemicals (avobenzone, oxybenzone, octocrylene, homosalate, octisalate, octinoxate, and ecamsule). Human dermal pharmacokinetic data following single and repeat dermal exposure to products containing the case study chemicals were obtained from data published by the US FDA. The clinical studies utilized an application procedure that followed maximal use conditions (product applied as 2 mg/cm² to 75% of the body surface area, 4 times a day). The case study chemicals were first reviewed to determine if they were in the applicability domain of the iTTC, and then, the human plasma concentrations were compared to an iTTC limit of 1 µM. When assessed under maximum usage, the external exposure of all chemicals exceeded the external dose TTC limits. By contrast, the internal exposure to all chemicals, except oxybenzone, was an order of magnitude lower than the 1 µM interim iTTC threshold. This work highlights the importance of understanding internal exposure relative to external dose and how the iTTC can be a valuable tool for assessing low-level internal exposures; additionally, the work demonstrates how to use an iTTC, and highlights considerations and refinement opportunities for the approach.

Discovery of Potent and Selective Dual Leucine Zipper Kinase/Leucine Zipper-Bearing Kinase Inhibitors with Neuroprotective Properties in In Vitro and In Vivo Models of Amyotrophic Lateral Sclerosis

Dual leucine zipper kinase (DLK) and leucine zipper-bearing kinase (LZK) are regulators of neuronal degeneration and axon growth. Therefore, there is a considerable interest in developing DLK/LZK inhibitors for neurodegenerative diseases. Herein, we use ligand- and structure-based drug design approaches for identifying novel amino-pyrazine inhibitors of DLK/LZK. DN-1289 (14), a potent and selective dual DLK/LZK inhibitor, demonstrated excellent in vivo plasma half-life across species and is anticipated to freely penetrate the central nervous system with no brain impairment based on in vivo rodent pharmacokinetic studies and human in vitro transporter data. Proximal target engagement and disease relevant pathway biomarkers were also favorably regulated in an in vivo model of amyotrophic lateral sclerosis.