Drug metabolism in drug discovery and development

The role of the methoxy group in approved drugs

The methoxy substituent is prevalent in natural products and, consequently, is present in many natural product-derived drugs. It has also been installed in modern drug molecules with no remnant of natural product features because medicinal chemists have been taking advantage of the benefits that this small functional group can bestow on ligand-target binding, physicochemical properties, and ADME parameters. Herein, over 230 methoxy-containing small-molecule drugs, as well as several fluoromethoxy-containing drugs, are presented from the vantage point of the methoxy group. Biochemical mechanisms of action, medicinal chemistry SAR studies, and numerous X-ray cocrystal structures are analyzed to identify the precise role of the methoxy group for many of the drugs and drug classes. Although the methoxy substituent can be considered as the hybridization of a hydroxy and a methyl group, the combination of these functionalities often results in unique effects that can amount to more than the sum of the individual parts.

Molecular probes for super-resolution imaging of drug dynamics

Super-resolution molecular probes (SRMPs) are essential tools for visualizing drug dynamics within cells, transcending the resolution limits of conventional microscopy. In this review, we provide an overview of the principles and design strategies of SRMPs, emphasizing their role in accurately tracking drug molecules. By illuminating the intricate processes of drug distribution, diffusion, uptake, and metabolism at a subcellular and molecular level, SRMPs offer crucial insights into therapeutic interventions. Additionally, we explore the practical applications of super-resolution imaging in disease treatment, highlighting the significance of SRMPs in advancing our understanding of drug action. Finally, we discuss future perspectives, envisioning potential advancements and innovations in this field. Overall, this review serves to inform and practitioners about the utility of SRMPs in driving innovation and progress in pharmacology, providing valuable insights for drug development and optimization.

Synthesis, design, and optimization of a potent and selective series of pyridylpiperazines as promising antimalarial agents

An optimization of the pyridylpiperazine series against Plasmodium falciparum has been performed, exploring a structure-activity relationship carried out on the toluyl fragment of hit 1, a compound with low micromolar activity against Plasmodium falciparum discovered by high-throughput screening. After confirming the crucial role played by this aryl fragment in the antiplasmodial activity, the replacement of the ortho-methyl substituent of 1 by halogenated ones led to an improvement for four analogs, either in terms of potency, expected pharmacokinetics profile, or both. Further introduction of endocyclic nitrogens in this fragment identified two more optimized compounds, 20 and 23, which are expected to be much more metabolically stable than 1. Additional assessment of the cytotoxicity, Ligand Lipophilic Efficiency, potency against the chloroquine-resistant Dd2 strain and in silico ADMET predictions revealed a satisfactory profile for most compounds, ultimately identifying the four optimized compounds 7, 9, 20 and 23 as promising compounds for further lead optimization of this series against Plasmodium falciparum.

Pharmacokinetics-Pharmacodynamics Modeling for Evaluating Drug-Drug Interactions in Polypharmacy: Development and Challenges

Polypharmacy is commonly employed in clinical settings. The potential risks of drug-drug interactions (DDIs) can compromise efficacy and pose serious health hazards. Integrating pharmacokinetics (PK) and pharmacodynamics (PD) models into DDIs research provides a reliable method for evaluating and optimizing drug regimens. With advancements in our comprehension of both individual drug mechanisms and DDIs, conventional models have begun to evolve towards more detailed and precise directions, especially in terms of the simulation and analysis of physiological mechanisms. Selecting appropriate models is crucial for an accurate assessment of DDIs. This review details the theoretical frameworks and quantitative benchmarks of PK and PD modeling in DDI evaluation, highlighting the establishment of PK/PD modeling against a backdrop of complex DDIs and physiological conditions, and further showcases the potential of quantitative systems pharmacology (QSP) in this field. Furthermore, it explores the current advancements and challenges in DDI evaluation based on models, emphasizing the role of emerging in vitro detection systems, high-throughput screening technologies, and advanced computational resources in improving prediction accuracy.

Computational Predictive and Electrochemical Detection of Metabolites (CP-EDM) of Piperine

In this article, we introduce a proof-of-concept strategy, Computational Predictive and Electrochemical Detection of Metabolites (CP-EDM), to expedite the discovery of drug metabolites. The use of a bioactive natural product, piperine, that has a well-curated metabolite profile but an unpredictable computational metabolism (Biotransformer v3.0) was selected. We developed an electrochemical reaction to oxidize piperine into a range of metabolites, which were detected by LC-MS. A series of chemically plausible metabolites were predicted based on ion fragmentation patterns. These metabolites were docked into the active site of CYP3A4 using Autodock4.2. From the clustered low-energy profile of piperine in the active site, it can be inferred that the most likely metabolic position of piperine (based on intermolecular distances to the Fe-oxo active site) is the benzo[d][1,3]dioxole motif. The metabolic profile was confirmed by comparison with the literature, and the electrochemical reaction delivered plausible metabolites, vide infra, thus, demonstrating the power of the hyphenated technique of tandem electrochemical detection and computational evaluation of binding poses. Taken together, we outline a novel approach where diverse data sources are combined to predict and confirm a metabolic outcome for a bioactive structure.

Identification of differential biological activity and synergy between the PARP inhibitor rucaparib and its major metabolite

The (poly)pharmacology of drug metabolites is seldom comprehensively characterized in drug discovery. However, some drug metabolites can reach high plasma concentrations and display in vivo activity. Here, we use computational and experimental methods to comprehensively characterize the kinase polypharmacology of M324, the major metabolite of the PARP1 inhibitor rucaparib. We demonstrate that M324 displays unique PLK2 inhibition at clinical concentrations. This kinase activity could have implications for the efficacy and safety of rucaparib and therefore warrants further clinical investigation. Importantly, we identify synergy between the drug and the metabolite in prostate cancer models and a complete reduction of α-synuclein accumulation in Parkinson's disease models. These activities could be harnessed in the clinic or open new drug discovery opportunities. The study reported here highlights the importance of characterizing the activity of drug metabolites to comprehensively understand drug response in the clinic and exploit our current drug arsenal in precision medicine.

In vivo and in vitro metabolite profiling of nirmatrelvir using LC-Q-ToF-MS/MS along with the in silico approaches for prediction of metabolites and their toxicity

Nirmatrelvir (NRV), a 3C-like protease or Mpro inhibitor of SARS-CoV-2, is used for the treatment of COVID-19 in adult and paediatric patients. The present study was accomplished to investigate the comprehensive metabolic fate of NRV using in vitro and in vivo models. The in vitro models used for the study were microsomes (human liver microsomes, rat liver microsomes, mouse liver microsomes) and S9 fractions (human liver S9 fractions and rat liver S9 fractions) with the appropriate cofactors, whereas Sprague-Dawley rats were used as the in vivo models. Nirmatrelvir was administered orally to Sprague-Dawley rats, which was followed by the collection of urine, faeces and blood at pre-determined time intervals. Protein precipitation was used as the sample preparation method for all the samples. The samples were then analysed by liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (LC-Q-ToF-MS/MS) using an Acquity BEH C18 column with 0.1% formic acid and acetonitrile as the mobile phase. Four metabolites were found to be novel, which were formed via amide hydrolysis, oxidation and hydroxylation. Furthermore, an in silico analysis was performed using Meteor Nexus software to predict the probable metabolic changes of NRV. The toxicity and mutagenicity of NRV and its metabolites were also determined using DEREK Nexus and SARAH Nexus.

Late-stage meta-C-H alkylation of pharmaceuticals to modulate biological properties and expedite molecular optimisation in a single step

Catalysed C-H activation has emerged as a transformative platform for molecular synthesis and provides new opportunities in drug discovery by late-stage functionalisation (LSF) of complex molecules. Notably, small aliphatic motifs have gained significant interest in medicinal chemistry for their beneficial properties and applications as sp3-rich functional group bioisosteres. In this context, we disclose a versatile strategy with broad applicability for the ruthenium-catalysed late-stage meta-C(sp2)-H alkylation of pharmaceuticals. This general protocol leverages numerous directing groups inherently part of bioactive scaffolds to selectivity install a variety of medicinally relevant bifunctional alkyl units within drug compounds. Our strategy enables the direct modification of unprotected lead structures to quickly generate an array of pharmaceutically useful analogues without resorting to de novo syntheses. Moreover, productive late-stage modulation of key biological characteristics of drug candidates upon remote C-H alkylation proves viable, highlighting the major benefits of our approach to offer in drug development programmes.

Flavonoids: A treasure house of prospective pharmacological potentials

Flavonoids are organic compounds characterized by a range of phenolic structures, which are abundantly present in various natural sources such as fruits, vegetables, cereals, bark, roots, stems, flowers, tea, and wine. The health advantages of these natural substances are renowned, and initiatives are being taken to extract the flavonoids. Apigenin, galangin, hesperetin, kaempferol, myricetin, naringenin, and quercetin are the seven most common compounds belonging to this class. A thorough analysis of bibliographic records from reliable sources including Google Scholar, Web of Science, PubMed, ScienceDirect, MEDLINE, and others was done to learn more about the biological activities of these flavonoids. These flavonoids appear to have promising anti-diabetic, anti-inflammatory, antibacterial, antioxidant, antiviral, cytotoxic, and lipid-lowering activities, according to evidence from in vitro, in vivo, and clinical research. The review contains recent trends, therapeutical interventions, and futuristic aspects of flavonoids to treat several diseases like diabetes, inflammation, bacterial and viral infections, cancers, and cardiovascular diseases. However, this manuscript should be handy in future drug discovery. Despite these encouraging findings, a notable gap exists in clinical research, hindering a comprehensive understanding of the effects of flavonoids at both high and low concentrations on human health. Future investigations should prioritize exploring bioavailability, given the potential for high inter-individual variation. As a starting point for further study on these flavonoids, this review paper may promote identifying and creating innovative therapeutic uses.

Improved Pharmacokinetic and Pharmacodynamic Profile of Deuterium-Reinforced Tricyclic Antidepressants Doxepin, Dosulepin, and Clomipramine in Animal Models

BACKGROUND AND OBJECTIVES

Doxepin, dosulepin, and clomipramine are tricyclic antidepressants (TCAs) that act as serotonin and noradrenaline reuptake inhibitors. The metabolites formed by N-dealkylation of these tricyclic antidepressants contribute to overall poor pharmacokinetics and efficacy. Deuteration of the methyl groups at metabolically active sites has been reported to be a useful strategy for developing more selective and potent antidepressants. This isotopic deuteration can lead to better bioavailability and overall effectiveness. The objective is to study the effect of site-selective deuteration of TCAs on their pharmacokinetic and pharmacodynamic profile by comparison with their nondeuterated counterparts.

METHODS

In the current study, the pharmacokinetic profile and antidepressant behavior of deuterated TCAs were evaluated using the forced swim test (FST) and tail suspension test (TST), using male Wistar rats and male Swiss albino mice, respectively; additionally, a synaptosomal reuptake study was carried out.

RESULTS

Compared with the nondeuterated parent drugs, deuterated forms showed improved efficacy in the behavior paradigm, indicating improved pharmacological activity. The pharmacokinetic parameters indicated increased maximum concentration in the plasma (Cmax), elimination half-life (t1/2), and area under the concentration-time curve (AUC)  in deuterated compounds. This can have a positive clinical impact on antidepressant treatment. Synaptosomal reuptake studies indicated marked inhibition of the reuptake mechanism of serotonin (5-HT) and norepinephrine.

CONCLUSIONS

Deuterated TCAs can prove to be potentially better molecules in the treatment of neuropsychiatric disorders as compared with nondeuterated compounds. In addition, we have demonstrated a concept that metabolically active, site-selective deuteration can be beneficial for improving the pharmacokinetic and pharmacodynamic profiles of TCAs. A further toxicological study of these compounds is needed to validate their future clinical use.

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.

Precision Deuteration in Search of Anticancer Agents: Approaches to Cancer Drug Discovery

Cancer chemotherapy has been shifted from conventional cytotoxic drug therapy to selective and target-specific therapy after the findings about DNA changes and proteins that are responsible for cancer. A large number of newer drugs were discovered as targeted therapy for particular types of neoplastic disease. The initial discovery includes the development of the first in the category, imatinib, a Bcr-Abl tyrosine kinase inhibitor (TKI) for the treatment of chronic myelocytic leukemia in 2001. But the joy did not last for long as the drug developed a point mutation within the ABL1 kinase domain of BCR-ABL1, which subsequently led to the discovery of many other TKIs. Resistance was observed for newer TKIs a few years after their launching, but the use of TKIs in life-threatening cancer therapy is considered as far better compared with the risks of disease because of its target specificity and hence less toxicity. In search of a better anticancer agent, the physiochemical properties of the lead molecule have been modified for its efficacy toward disease and delay in the development of resistance. Deuteration in the drug molecule is one of such modifications that alter the pharmacokinetic properties, generally its metabolism, as compared with its pharmacodynamic effects. Precision deuteration in many anticancer drugs has been carried out to search for better drugs for cancer. In this review, the majority of anticancer drugs and molecules for which deuteration was applied to get better anticancer molecules were discussed. This review will provide a complete guide about the benefits of deuteration in cancer chemotherapy.

Biological activity and structural modification of isosteviol over the past 15 years

Isosteviol is a tetracyclic diterpenoid obtained by hydrolysis of stevioside. Due to its unique molecular skeleton and extensive pharmacological activities, isosteviol has attracted more and more attention from researchers. This review summarized the structural modification, pharmacological activity and microbial transformation of isosteviol from 04/2008 to 10/2023. In addition, the research history, structural characterization, and pharmacokinetics of isosteviol were also briefly reviewed. This review aims to provide useful literature resources and inspirations for the exploration of diterpenoid drugs.

Chemical Catalysis Guides Structural Identification for the Major In Vivo Metabolite of the BET Inhibitor JQ1

The bromodomain inhibitor (+)-JQ1 is a highly validated chemical probe; however, it exhibits poor in vivo pharmacokinetics. To guide efforts toward improving its pharmacological properties, we identified the (+)-JQ1 primary metabolite using chemical catalysis methods. Treatment of (+)-JQ1 with tetrabutylammonium decatungstate under photochemical conditions resulted in selective formation of an aldehyde at the 2-position of the thiophene ring [(+)-JQ1-CHO], which was further reduced to the 2-hydroxymethyl analog [(+)-JQ1-OH]. Comparative LC/MS analysis of (+)-JQ1-OH to the product obtained from liver microsomes suggested (+)-JQ1-OH as the major metabolite of (+)-JQ1. The 2-thienyl position was then substituted to generate a trideuterated (-CD3, (+)-JQ1-D) analog having half-lives that were 1.8- and 2.8-fold longer in mouse and human liver microsomes, respectively. This result unambiguously confirmed (+)-JQ1-OH as the major metabolite of (+)-JQ1. These studies demonstrate an efficient process for studying drug metabolism and identifying the metabolic soft spots of bioactive compounds.

INTEDE 2.0: the metabolic roadmap of drugs

The metabolic roadmap of drugs (MRD) is a comprehensive atlas for understanding the stepwise and sequential metabolism of certain drug in living organisms. It plays a vital role in lead optimization, personalized medication, and ADMET research. The MRD consists of three main components: (i) the sequential catalyses of drug and its metabolites by different drug-metabolizing enzymes (DMEs), (ii) a comprehensive collection of metabolic reactions along the entire MRD and (iii) a systematic description on efficacy & toxicity for all metabolites of a studied drug. However, there is no database available for describing the comprehensive metabolic roadmaps of drugs. Therefore, in this study, a major update of INTEDE was conducted, which provided the stepwise & sequential metabolic roadmaps for a total of 4701 drugs, and a total of 22 165 metabolic reactions containing 1088 DMEs and 18 882 drug metabolites. Additionally, the INTEDE 2.0 labeled the pharmacological properties (pharmacological activity or toxicity) of metabolites and provided their structural information. Furthermore, 3717 drug metabolism relationships were supplemented (from 7338 to 11 055). All in all, INTEDE 2.0 is highly expected to attract broad interests from related research community and serve as an essential supplement to existing pharmaceutical/biological/chemical databases. INTEDE 2.0 can now be accessible freely without any login requirement at: http://idrblab.org/intede/.

Integrated computational approach identifies potential inhibitors of ASK1-(JNK/P38) interaction signaling: new insights into cancer therapeutics

Cancers are characterized by the aberrant expression of certain genes that trigger a cascade of molecular events that culminate in dysregulated cell division. Consequently, the inhibition of the products of these expressedgenes has emerged as a rational approach in cancer therapy. The apoptosis signal-regulating kinase 1 (ASK1) protein, encoded by the mitogen-activated protein kinase kinase kinase 5 (MAP3K5) gene, plays pertinent roles in the mediation of cell death induced by stress and inflammation, andis often found at elevated levels in cancer. Consequently, it has emerged as a molecular target for the development of potential chemotherapeutics through identification of selective inhibitors. However, there is still dearth of ASK1 inhibitors in clinical use. Hence, molecular modelling approaches were employed in this study to discover potential ASK1 inhibitors from phytochemicals. Twenty-five phytocompounds from four medicinal plants were tested for their inhibitory prowess via molecular docking. Interestingly, all the compounds exhibited promising inhibitory potentials for ASK1. However, further subjection to filtering procedures via different pipelines including drug-likeness evaluation, pharmacokinetics screening, toxicity profiling, and better affinities compared to the approved inhibitor resulted in three hit compounds namely ellagic acid, luteolin, and kaempferol with suitable properties. Profiling of the interactions formed between the hit\compounds and the targets revealed several interactions that were not present in that of the approved inhibitor, while molecular dynamics (MD) simulation revealed the complexes formed as stable. Conclusively, this study identified three compounds with ASK1 inhibitory potentials that are worthy of further exploration in in vitro and in vivo studies.Communicated by Ramaswamy H. Sarma.

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.

Unveiling the therapeutic promise of natural products in alleviating drug-induced liver injury: Present advancements and future prospects

Drug-induced liver injury (DILI) refers to adverse reactions to small chemical compounds, biological agents, and medical products. These reactions can manifest as acute or chronic damage to the liver. From 1997 to 2016, eight drugs, including troglitazone, nefazodone, and lumiracoxib, were removed from the market due to their liver-damaging effects, which can cause diseases. We aimed to review the recent research on natural products and their bioactive components as hepatoprotective agents in mitigating DILI. Recent articles were fetched via searching the PubMed, PMC, Google Scholar, and Web of Science electronic databases from 2010 to January 2023 using relevant keywords such as "natural products," "acetaminophen," "antibiotics," "paracetamol," "DILI," "hepatoprotective," "drug-induced liver injury," "liver failure," and "mitigation." The studies reveal that the antituberculosis drug (acetaminophen) is the most frequent cause of DILI, and natural products have been largely explored in alleviating acetaminophen-induced liver injury. They exert significant hepatoprotective effects by preventing mitochondrial dysfunction and inflammation, inhibiting oxidative/nitrative stress, and macromolecular damage. Due to the bioavailability and dietary nature, using natural products alone or as an adjuvant with existing drugs is promising. To advance DILI management, it is crucial to conduct well-designed randomized clinical trials to evaluate natural products' efficacy and develop new molecules clinically. However, natural products are a promising solution for remedying drug-induced hepatotoxicity and lowering the risk of DILI.

A Novel Multi-Scale Graph Neural Network for Metabolic Pathway Prediction

Predicting the metabolic pathway classes of compounds in the human body is an important problem in drug research and development. For this purpose, we propose a Multi-Scale Graph Neural Network framework, named MSGNN. The framework includes a subgraph encoder, a feature encoder and a global feature processor, and a graph augmentation strategy is adopted. The subgraph encoder is responsible for extracting the local structural features of the compound, the feature encoder learns the characteristics of the atoms, and the global feature processor processes the information from the pre-training model and the two molecular fingerprints, while the graph augmentation strategy is to expand the train set through a scientific and reasonable method. The experiment result illustrates that the accuracy, precision, recall and F1 metrics of MSGNN reach 98.17%, 94.18%, 94.43% and 94.30%, respectively, which is superior to the similar models we have known. In addition, the ablation experiment demonstrates the indispensability of MSGNN modules.

The Effect of Deuteration and Homologation of the Lactam Ring of Nirmatrelvir on Its Biochemical Properties and Oxidative Metabolism

This study explores the relationship between structural alterations of nirmatrelvir, such as homologation and deuteration, and metabolic stability of newly synthesized derivatives. We developed a reliable synthetic protocol toward dideutero-nirmatrelvir and its homologated analogues with high isotopic incorporation. Deuteration of the primary metabolic site of nirmatrelvir provides a 3-fold improvement of its human microsomal stability but is accompanied by an increased metabolism rate at secondary sites. Homologation of the lactam ring allows the capping group modification to decrease and delocalize the molecule's lipophilicity, reducing the metabolic rate at secondary sites. The effect of deuteration was less pronounced for the 6-membered lactam than for its 5-membered analogue in human microsomes, but the trend is reversed in the case of mouse microsomes. X-ray data revealed that the homologation of the lactam ring favors the orientation of the drug's nitrile warhead for interaction with the catalytic sulfur of the SARS-CoV-2 Mpro, improving its binding. Comparable potency against SARS-CoV-2 Mpro from several variants of concern and selectivity over human cysteine proteases cathepsin B, L, and S was observed for the novel deuterated/homologated derivative and nirmatrelvir. Synthesized compounds displayed a large interspecies variability in hamster, rat, and human hepatocyte stability assays. Overall, we aimed to apply a rational approach in changing the physicochemical properties of the drug to refine its biochemical and biological parameters.

Virtual screening, molecular docking, molecular dynamics, and MM-GBSA approaches identify prospective fructose-1,6-bisphosphatase inhibitors from pineapple for diabetes management

Diabetes affects millions globally and poses treatment challenges. Targeting the enzyme fructose-1,6-bisphosphatase (FBPase) in gluconeogenesis and exploring plant-based therapies offer potential solutions for improving diabetes management while supporting sustainability and medicinal advancements. Utilizing pineapple (Ananas comosus L. Merr.) waste as a source of drug precursors could be valuable for health and environmental care due to its medicinal benefits and abundant yearly biomass production. Therefore, this study conducted a virtual screening to identify potential natural compounds from pineapple that could inhibit FBPase activity. A total of 112 compounds were screened for drug-likeness and ADMET properties, and molecular docking simulations were performed on 20 selected compounds using blind docking. The lead compound, butane-2,3-diyl diacetate, was subjected to 100 ns MD simulations, revealing a binding energy of -5.4 kcal/mol comparable to metformin (-5.6 kcal/mol). The MD simulation also confirmed stable complexes with crucial hydrogen bonds. Glu20, Ala24, Thr27, Gly28, Glu29, Leu30, Val160, Met177, Asp178, and Cys179 were identified as key amino acids that stabilized the human liver FBPase-butane-2,3-diyl diacetate complex, while Tyr215 and Asp218 played a crucial role in the human liver FBPase-Metformin complex. Our study indicates that the lead compound has high intestinal solubility. Therefore, it would show rapid bloodstream distribution and effective action on the target protein, making butane-2,3-diyl diacetate a potential antidiabetic drug candidate. However, further investigations in vitro, preclinical, and clinical trials are required to thoroughly assess its efficacy and safety.Communicated by Ramaswamy H. Sarma.

Metabolism of natural and synthetic bioactive compounds in Cunninghamella fungi and their applications in drug discovery

Investigation of xenobiotic metabolism is a key step for drug discovery. Since the in vivo investigations may be associated with harmful effects attributed to production of toxic metabolites, it is deemed necessary to predict their structure especially at the preliminary clinical studies. Furthermore, the application of microorganisms that are capable of metabolizing drugs mimic human metabolism and consequently may predict possible metabolites. The genus Cunninghamella has been proven to be a potential candidate, which mimics xenobiotic metabolism occurring inside the human body, including phase I and II metabolic reactions. Moreover, biotransformation with Cunninghamella showed chemical diversity, where a lot of products were detected in relation to the initial substrates after being modified by oxidation, hydroxylation, and conjugation reactions. Some of these products are more bioactive than the parent compounds. The current review presents a comprehensive literature overview regarding the Cunninghamella organisms as biocatalysts, which simulate mammalian metabolism of natural secondary and synthetic compounds.

Novel NIR-II fluorescent probes for biliary atresia imaging

Biliary atresia is a rare infant disease that predisposes patients to liver transplantation and death if not treated in time. However, early diagnosis is challenging because the clinical manifestations and laboratory tests of biliary atresia overlap with other cholestatic diseases. Therefore, it is very important to develop a simple, safe and reliable method for the early diagnosis of biliary atresia. Herein, a novel NIR-II fluorescence probe, HZL2, with high quantum yield, excellent biocompatibility, low cytotoxicity and rapid excretion through the liver and gallbladder was developed based on the oil/water partition coefficient and permeability. A simple fecal sample after injection of HZL2 can be used to efficiently identify the success of the mouse model of biliary atresia for the first time, allowing for an early diagnosis of the disease. This study not only developed a simple and safe method for the early diagnosis of biliary atresia with great potential in clinical translation but also provides a research tool for the development of pathogenesis and therapeutic medicines for biliary atresia.

Piperacetazine Directly Binds to the PAX3::FOXO1 Fusion Protein and Inhibits Its Transcriptional Activity

The tumor-specific chromosomal translocation product, PAX3::FOXO1, is an aberrant fusion protein that plays a key role for oncogenesis in the alveolar subtype of rhabdomyosarcoma (RMS). PAX3::FOXO1 represents a validated molecular target for alveolar RMS and successful inhibition of its oncogenic activity is likely to have significant clinical applications. Even though several PAX3::FOXO1 function-based screening studies have been successfully completed, a directly binding small-molecule inhibitor of PAX3::FOXO1 has not been reported. Therefore, we screened small-molecule libraries to identify compounds that were capable of directly binding to PAX3::FOXO1 protein using surface plasmon resonance technology. Compounds that directly bound to PAX3::FOXO1 were further evaluated in secondary transcriptional activation assays. We discovered that piperacetazine can directly bind to PAX3::FOXO1 protein and inhibit fusion protein-derived transcription in multiple alveolar RMS cell lines. Piperacetazine inhibited anchorage-independent growth of fusion-positive alveolar RMS cells but not embryonal RMS cells. On the basis of our findings, piperacetazine is a molecular scaffold upon which derivatives could be developed as specific inhibitors of PAX3::FOXO1. These novel inhibitors could potentially be evaluated in future clinical trials for recurrent or metastatic alveolar RMS as novel targeted therapy options.

SIGNIFICANCE

RMS is a malignant soft-tissue tumor mainly affecting the pediatric population. A subgroup of RMS with worse prognosis harbors a unique chromosomal translocation creating an oncogenic fusion protein, PAX3::FOXO1. We identified piperacetazine as a direct inhibitor of PAX3::FOXO1, which may provide a scaffold for designing RMS-specific targeted therapy.

Transition Metal Complexes as Antimalarial Agents: A Review

In antimalarial drug development research, overcoming drug resistance has been a major challenge for researchers. Nowadays, several drugs like chloroquine, mefloquine, sulfadoxine, and artemisinin are used to treat malaria. But increment in drug resistance has pushed researchers to find novel drugs to tackle drug resistance problems. The idea of using transition metal complexes with pharmacophores as ligands/ligand pendants to show enhanced antimalarial activity with a novel mechanism of action has gained significant attention recently. The advantages of metal complexes include tunable chemical/physical properties, redox activity, avoiding resistance factors, etc. Several recent reports have successfully demonstrated that the metal complexation of known organic antimalarial drugs can overcome drug resistance by showing enhanced activities than the parent drugs. This review has discussed the fruitful research works done in the past few years falling into this criterion. Based on transition metal series (3d, 4d, or 5d), the antimalarial metal complexes have been divided into three broad categories (3d, 4d, or 5d metal-based), and their activities have been compared with the similar control complexes as well as the parent drugs. Furthermore, we have also commented on the potential issues and their possible solution for translating these metal-based antimalarial complexes into the clinic.

Insight into the corrosion inhibiting potential and anticancer activity of 1-(4-methoxyphenyl)-5-methyl-N'-(2-oxoindolin-3-ylidene)-1H-1,2,3-triazole-4-carbohydrazide via computational approaches

Cancer is a major health concern globally. Orthodox and traditional medicine have actively been explored to manage this disease. Also, corrosion is a natural catastrophe that weakens and deteriorates metallic structures and their alloys causing major structural failures and severe economic implications. Designing and exploring multi-functional materials are beneficial since they are adaptive to different fields including engineering and pharmaceutics. In this study, we examined the anti-corrosion and anti-cancer potentials of 1-(4-methoxyphenyl)-5-methyl-N'-(2-oxoindolin-3-ylidene)-1H-1,2,3-triazole-4-carbohydrazide (MAC) using computational approaches. The molecular reactivity descriptors and charge distribution parameters of MAC were studied in gas and water at density functional theory (DFT) at B3LYP/6-311++G(d,p) theory level. The binding and mechanism of interaction between MAC and iron surface was studied using Monte Carlo (MC) and molecular dynamics (MD) simulation in hydrochloric acid medium. From the DFT, MC, and MD simulations, it was observed that MAC interacted spontaneously with iron surface essentially via van der Waal and electrostatic interactions. The near-parallel alignment of the corrosion inhibitor on iron plane facilitates its adsorption and isolation of the metal surface from the acidic solution. Further, the compound was docked in the binding pocket of anaplastic lymphoma kinase (ALK: 4FNZ) protein to assess its anti-cancer potential. The binding score, pharmacokinetics, and drug-likeness of MAC were compared with the reference drug (Crizotinib). The MAC displayed binding scores of -5.729 kcal/mol while Crizotinib has -3.904 kcal/mol. MD simulation of the complexes revealed that MAC is more stable and exhibits more favourable hydrogen bonding with the ALK receptor's active site than Crizotinib.Communicated by Ramaswamy H. Sarma.

Immobilised-enzyme microreactors for the identification and synthesis of conjugated drug metabolites

The study of naturally circulating drug metabolites has been a focus of interest, since these metabolites may have different therapeutic and toxicological effects compared to the parent drug. The synthesis of metabolites outside of the human body is vital in order to conduct studies into the pharmacological activities of drugs and bioactive compounds. Current synthesis methods require significant purification and separation efforts or do not provide sufficient quantities for use in pharmacology experiments. Thus, there is a need for simple methods yielding high conversions whilst bypassing the requirement for a separation. Here we have developed and optimised flow chemistry methods in glass microfluidic reactors utilising surface-immobilised enzymes for sulfonation (SULT1a1) and glucuronidation (UGT1a1). Conversion occurs in flow, the precursor and co-factor are pumped through the device, react with the immobilised enzymes and the product is then simply collected at the outlet with no separation from a complex biological matrix required. Conversion only occurred when both the correct co-factor and enzyme were present within the microfluidic system. Yields of 0.97 ± 0.26 μg were obtained from the conversion of resorufin into resorufin sulfate over 2 h with the SULT1a1 enzyme and 0.47 μg of resorufin glucuronide over 4 h for UGT1a1. This was demonstrated to be significantly more than static test tube reactions at 0.22 μg (SULT1a1) and 0.19 μg (UGT1a1) over 4 h. With scaling out and parallelising, useable quantities of hundreds of micrograms for use in pharmacology studies can be synthesised simply.

CMMS-GCL: cross-modality metabolic stability prediction with graph contrastive learning

MOTIVATION

Metabolic stability plays a crucial role in the early stages of drug discovery and development. Accurately modeling and predicting molecular metabolic stability has great potential for the efficient screening of drug candidates as well as the optimization of lead compounds. Considering wet-lab experiment is time-consuming, laborious, and expensive, in silico prediction of metabolic stability is an alternative choice. However, few computational methods have been developed to address this task. In addition, it remains a significant challenge to explain key functional groups determining metabolic stability.

RESULTS

To address these issues, we develop a novel cross-modality graph contrastive learning model named CMMS-GCL for predicting the metabolic stability of drug candidates. In our framework, we design deep learning methods to extract features for molecules from two modality data, i.e. SMILES sequence and molecule graph. In particular, for the sequence data, we design a multihead attention BiGRU-based encoder to preserve the context of symbols to learn sequence representations of molecules. For the graph data, we propose a graph contrastive learning-based encoder to learn structure representations by effectively capturing the consistencies between local and global structures. We further exploit fully connected neural networks to combine the sequence and structure representations for model training. Extensive experimental results on two datasets demonstrate that our CMMS-GCL consistently outperforms seven state-of-the-art methods. Furthermore, a collection of case studies on sequence data and statistical analyses of the graph structure module strengthens the validation of the interpretability of crucial functional groups recognized by CMMS-GCL. Overall, CMMS-GCL can serve as an effective and interpretable tool for predicting metabolic stability, identifying critical functional groups, and thus facilitating the drug discovery process and lead compound optimization.

AVAILABILITY AND IMPLEMENTATION

The code and data underlying this article are freely available at https://github.com/dubingxue/CMMS-GCL.

Artificial Intelligence in Pharmaceutical Technology and Drug Delivery Design

Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic knowledge and provides expedited solutions to complex challenges. Remarkable advancements in AI technology and machine learning present a transformative opportunity in the drug discovery, formulation, and testing of pharmaceutical dosage forms. By utilizing AI algorithms that analyze extensive biological data, including genomics and proteomics, researchers can identify disease-associated targets and predict their interactions with potential drug candidates. This enables a more efficient and targeted approach to drug discovery, thereby increasing the likelihood of successful drug approvals. Furthermore, AI can contribute to reducing development costs by optimizing research and development processes. Machine learning algorithms assist in experimental design and can predict the pharmacokinetics and toxicity of drug candidates. This capability enables the prioritization and optimization of lead compounds, reducing the need for extensive and costly animal testing. Personalized medicine approaches can be facilitated through AI algorithms that analyze real-world patient data, leading to more effective treatment outcomes and improved patient adherence. This comprehensive review explores the wide-ranging applications of AI in drug discovery, drug delivery dosage form designs, process optimization, testing, and pharmacokinetics/pharmacodynamics (PK/PD) studies. This review provides an overview of various AI-based approaches utilized in pharmaceutical technology, highlighting their benefits and drawbacks. Nevertheless, the continued investment in and exploration of AI in the pharmaceutical industry offer exciting prospects for enhancing drug development processes and patient care.

Chitosan-Based Nano Systems for Natural Antioxidants in Breast Cancer Therapy

Breast cancer is a major cause of death globally, accounting for around 13% of all deaths. Chemotherapy, the common treatment for cancer, can have side effects that lead to the production of reactive oxygen species (ROS) and an increase in oxidative stress in the body. Antioxidants are important for maintaining the health of cells and helping the immune system function properly. They play a crucial role in balancing the body's internal environment. Using natural antioxidants is an alternative to mitigate the harmful effects of oxidative stress. However, around 80% of natural antioxidants have limited effectiveness when taken orally because they do not dissolve well in water or other solvents. This poor solubility affects their ability to be absorbed by the body and limits their bioavailability. One strategy that has been considered is to increase their water solubility to increase their oral bioavailability. Chitosan-based nanoparticle (CSNP) systems have been extensively explored due to their reliability and simpler synthesis routes. This review focuses on the various methods of chitosan-based nanoformulation for developing effective oral dosage forms for natural antioxidants based on the pharmacokinetics and pharmacodynamics properties. Chitosan (CS) could be a model, because of its wide use in polymeric NPs research, thus providing a better understanding of the role of vehicles that carry natural antioxidants in maintaining the stability and enhancing the performance of cancer drugs.

Formal Anti-Markovnikov Addition of Water to Olefins by Titanocene-Catalyzed Epoxide Hydrosilylation: From Stoichiometric to Sustainable Catalytic Reactions

Here, the evolution of the titanocene-catalyzed hydrosilylation of epoxides that yields the corresponding anti-Markovnikov alcohols is summarized. The study focuses on aspects of sustainability, efficient catalyst activation, and stereoselectivity. The latest variant of the reaction employs polymethylhydrosiloxane (PMHS), a waste product of the Müller-Rochow process as terminal reductant, features an efficient catalyst activation with benzylMgBr and the use of the bench stable Cp₂TiCl₂ as precatalyst. The combination of olefin epoxidation and epoxide hydrosilylation provides a uniquely efficient approach to the formal anti-Markovnikov addition of H₂O to olefins.

Halting aberrant DNA methylation via in silico Identification of potent inhibitors of DNMT3B enzyme: Atomistic insights

To date, Cancer remains a global threat due to its impact on growing life expectancy. With the many efforts and methods of combating the disease, complete success remains a challenge owing to several limitations including cancer cells developing resistance through mutations, off-target effect of some cancer drugs resulting in toxicities, among many others. Aberrant DNA methylation is understood to be the primary reason for improper gene silence, which can result in neoplastic transformation, carcinogenesis, and tumour progression. DNA methyltransferase B (DNMT3B) enzyme is considered a potential target for the treatment of several cancers due to its important role in DNA methylation. However, only a few DNMT3B inhibitors have been reported to date. Herein, in silico molecular recognition techniques such as Molecular docking, Pharmacophore-based virtual screen and MD simulation were employed to identify potential inhibitors of DNMT3B that can halt aberrancy in DNA methylation. Findings initially identified 878 hit compounds based on a designed pharmacophore model from the reference compound Hypericin. Molecular docking was used to rank the hits by testing their efficiency when bound to the target enzyme and the top three (3) selected. All three (3) of the top hits showed excellent pharmacokinetic properties but two (2) (Zinc33330198 and Zinc77235130) were identified to be non-toxic. Molecular dynamic simulation of the final two hits showed good stability, flexibility, and structural rigidity of the compounds on DNMT3B. Finally, thermodynamic energy estimations show both compounds had favourable free energies comprising - 26.04 kcal/mol for Zinc77235130 and - 15.73 kcal/mol for Zinc33330198. Amongst the final two hits, Zinc77235130 showed consistency in favourable results across all the tested parameters and was thus selected as the lead compound for further experimental validation. The identification of this lead compound will form important basis for the inhibition of aberrant DNA methylation in cancer therapy.

In Silico Models for Anti-COVID-19 Drug Discovery: A Systematic Review

The coronavirus disease 2019 (COVID-19) is a severe worldwide pandemic. Due to the emergence of various SARS-CoV-2 variants and the presence of only one Food and Drug Administration (FDA) approved anti-COVID-19 drug (remdesivir), the disease remains a mindboggling global public health problem. Developing anti-COVID-19 drug candidates that are effective against SARS-CoV-2 and its various variants is a pressing need that should be satisfied. This systematic review assesses the existing literature that used in silico models during the discovery procedure of anti-COVID-19 drugs. Cochrane Library, Science Direct, Google Scholar, and PubMed were used to conduct a literature search to find the relevant articles utilizing the search terms "In silico model," "COVID-19," "Anti-COVID-19 drug," "Drug discovery," "Computational drug designing," and "Computer-aided drug design." Studies published in English between 2019 and December 2022 were included in the systematic review. From the 1120 articles retrieved from the databases and reference lists, only 33 were included in the review after the removal of duplicates, screening, and eligibility assessment. Most of the articles are studies that use SARS-CoV-2 proteins as drug targets. Both ligand-based and structure-based methods were utilized to obtain lead anti-COVID-19 drug candidates. Sixteen articles also assessed absorption, distribution, metabolism, excretion, toxicity (ADMET), and drug-likeness properties. Confirmation of the inhibitory ability of the candidate leads by in vivo or in vitro assays was reported in only five articles. Virtual screening, molecular docking (MD), and molecular dynamics simulation (MDS) emerged as the most commonly utilized in silico models for anti-COVID-19 drug discovery.

Updates on drug designing approach through computational strategies: a review

The drug discovery and development (DDD) process in pursuit of novel drug candidates is a challenging procedure requiring lots of time and resources. Therefore, computer-aided drug design (CADD) methodologies are used extensively to promote proficiency in drug development in a systematic and time-effective manner. The point in reference is SARS-CoV-2 which has emerged as a global pandemic. In the absence of any confirmed drug moiety to treat the infection, the science fraternity adopted hit and trial methods to come up with a lead drug compound. This article is an overview of the virtual methodologies, which assist in finding novel hits and help in the progression of drug development in a short period with a specific medicinal solution.

Development of a Swellable and Floating Gastroretentive Drug Delivery System (sfGRDDS) of Ciprofloxacin Hydrochloride

Sangelose^® (SGL) is a novel hydroxypropyl methylcellulose (HPMC) derivative that has been hydrophobically modified. Due to its high viscosity, SGL has the potential as a gel-forming and release-rate-controlled material for application in swellable and floating gastroretentive drug delivery systems (sfGRDDS). The aim of this study was to develop ciprofloxacin (CIP)-loaded sfGRDDS tablets comprised of SGL and HPMC in order to extend CIP exposure in the body and achieve optimal antibiotic treatment regimes. Results illustrated that SGL-HPMC-based sfGRDDS could swell to a diameter above 11 mm and showed a short floating lag time (<4 s) and long total floating time (>24 h) to prevent gastric emptying. In dissolution studies, CIP-loaded SGL-HPMC sfGRDDS demonstrated a specific biphasic release effect. Among the formulations, the SGL/type-K HPMC 15,000 cps (HPMC 15K) (50:50) group exhibited typical biphasic release profiles, with F4-CIP and F10-CIP individually releasing 72.36% and 64.14% CIP within 2 h dissolution, and sustaining release to 12 h. In pharmacokinetic studies, the SGL-HPMC-based sfGRDDS demonstrated higher C_max (1.56-1.73 fold) and shorter T_max (0.67 fold) than HPMC-based sfGRDDS. Furthermore, SGL 90L in GRDDS indicated an excellent biphasic release effect and a maximum elevation of relative bioavailability (3.87 fold). This study successfully combined SGL and HPMC to manufacture sfGRDDS that retain CIP in the stomach for an optimal duration while improving its pharmacokinetic characteristics. It was concluded that the SGL-HPMC-based sfGRDDS is a promising biphasic antibiotic delivery system that can both rapidly achieve the therapeutic antibiotic concentration and maintain the plasma antibiotic concentration for an extended period to maximize antibiotic exposure in the body.

Artificial Intelligence in Drug Metabolism and Excretion Prediction: Recent Advances, Challenges, and Future Perspectives

Drug metabolism and excretion play crucial roles in determining the efficacy and safety of drug candidates, and predicting these processes is an essential part of drug discovery and development. In recent years, artificial intelligence (AI) has emerged as a powerful tool for predicting drug metabolism and excretion, offering the potential to speed up drug development and improve clinical success rates. This review highlights recent advances in AI-based drug metabolism and excretion prediction, including deep learning and machine learning algorithms. We provide a list of public data sources and free prediction tools for the research community. We also discuss the challenges associated with the development of AI models for drug metabolism and excretion prediction and explore future perspectives in the field. We hope this will be a helpful resource for anyone who is researching in silico drug metabolism, excretion, and pharmacokinetic properties.

Synthesis and biological evaluation of N-(3-fluorobenzyl)-4-(1-(methyl-d3)-1H-indazol-5-yl)-5-(6-methylpyridin-2-yl)-1H-imidazol-2-amine as a novel, potent ALK5 receptor inhibitor

Specific inhibition of ALK5 provides a novel method for controlling the development of cancers and fibrotic diseases. In this work, a novel series of N-(3-fluorobenzyl)-4-(1-(methyl-d₃)-1H-indazol-5-yl)-5-(6-methylpyridin-2-yl)-1H-imidazol-2-amine (11), a potential clinical candidate, was synthesized by strategic incorporation of deuterium at potential metabolic soft spots and identified as ALK5 inhibitors. This compound has a low potential for CYP-mediated drug-drug interactions as a CYP450 inhibitor (IC₅₀ = >10 μM) and showed potent inhibitory effects in cellular assay (IC₅₀ = 3.5 ± 0.4 nM). The pharmacokinetic evaluation of 11 in mice demonstrated moderate clearance (29.0 mL/min/kg) and also revealed high oral bioavailability in mice (F = 67.6%).

Production of a major metabolite of niclosamide using bacterial cytochrome P450 enzymes

Niclosamide has been proposed as a possible candidate for a Covid-19 drug. However, the metabolites of niclosamide are difficult to investigate because they are usually not available commercially or they are quite expensive in the commercial market. In this study, the major metabolite of niclosamide in human liver microsomes (HLMs) was confirmed to be 3-OH niclosamide. Because the production of 3-OH niclosamide using HLMs has a slow turnover rate, a new method of producing niclosamide metabolite with an easier and highly cost-efficient method was thus conducted. Bacterial CYP102A1 (BM3) is one of the bacterial cytochrome P450s (CYPs) from Bacillus megaterium that structurally show similar activities to human CYPs. Here, the BM3 mutants were used to produce niclosamide metabolites and the metabolites were analyzed using high-performance liquid chromatography and LC-mass spectrometry. Among a set of mutants tested here, BM3 M14 mutant was the most active in producing 3-OH niclosamide, the major metabolite of niclosamide. Comparing BM3 M14 and HLMs, BM3 M14 production of 3-OH niclosamide was 34-fold higher than that of HLMs. Hence, the engineering of BM3 can be a cost-efficient method to produce 3-OH niclosamide.

Papaverine: A Miraculous Alkaloid from Opium and Its Multimedicinal Application

The pharmacological actions of benzylisoquinoline alkaloids are quite substantial, and have recently attracted much attention. One of the principle benzylisoquinoline alkaloids has been found in the unripe seed capsules of Papaver somniferum L. Although it lacks analgesic effects and is unrelated to the compounds in the morphine class, it is a peripheral vasodilator and has a direct effect on vessels. It is reported to inhibit the cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP) phosphodiesterase in smooth muscles, and it has been observed to increase intracellular levels of cAMP and cGMP. It induces coronary, cerebral, and pulmonary artery dilatation and helps to lower cerebral vascular resistance and enhance cerebral blood flow. Current pharmacological research has revealed that papaverine demonstrates a variety of biological activities, including activity against erectile dysfunction, postoperative vasospasms, and pulmonary vasoconstriction, as well as antiviral, cardioprotective, anti-inflammatory, anticancer, neuroprotective, and gestational actions. It was recently demonstrated that papaverine has the potential to control SARS-CoV-2 by preventing its cytopathic effect. These experiments were carried out both in vitro and in vivo and require an extensive understanding of the mechanisms of action. With its multiple mechanisms, papaverine can be considered as a natural compound that is used to develop therapeutic drugs. To validate its applications, additional research is required into its precise therapeutic mechanisms as well as its acute and chronic toxicities. Therefore, the goal of this review is to discuss the major studies and reported clinical studies looking into the pharmacological effects of papaverine and the mechanisms of action underneath these effects. Additionally, it is recommended to conduct further research via significant pharmacodynamic and pharmacokinetic studies.

Metabolism and disposition of JNJ-10450232 (NTM-006) in rats, dogs, nonhuman primates and humans

JNJ-10450232 (NTM-006), a novel non-opioid, non-nonsteroidal anti-inflammatory drug with structural similarities to acetaminophen, demonstrated anti-pyretic and/or analgesic activities in preclinical models and humans and reduced potential to cause hepatotoxicity in preclinical species. Metabolism and disposition of JNJ-10450232 (NTM-006) following oral administration to rats, dogs, monkeys and humans are reported. Urinary excretion was the major route of elimination based on recovery of 88.6% (rats) and 73.7% (dogs) of oral dose. The compound was extensively metabolized based on low recovery of unchanged drug in excreta from rats (11.3%) and dogs (18.4%). Clearance is driven by O-glucuronidation, amide hydrolysis, O-sulfation and methyl oxidation pathways. The combination of metabolic pathways driving clearance in human is covered in at least one preclinical species despite a few species-dependent pathways. O-Glucuronidation was the major primary metabolic pathway of JNJ-10450232 (NTM-006) in dogs, monkeys and humans, although amide hydrolysis was another major primary metabolic pathway in rats and dogs. A minor bioactivation pathway to quinone-imine is observed only in monkeys and humans. Unchanged drug was the major circulatory component in all species investigated. Except for metabolic pathways unique to the 5-methyl-1H-pyrazole-3-carboxamide moiety, metabolism and disposition of JNJ-10450232 (NTM-006) are similar to acetaminophen across species.

Extracellularly Detectable Electrochemical Signals of Living Cells Originate from Metabolic Reactions

Direct detection of cellular redox signals has shown immense potential as a novel living cell analysis tool. However, the origin of such signals remains unknown, which hinders the widespread use of electrochemical methods for cellular research. In this study, the authors found that intracellular metabolic pathways that generate adenosine triphosphate (ATP) are the main contributors to extracellularly detectable electrochemical signals. This is achieved through the detection of living cells (4,706 cells/chip, linearity: 0.985) at a linear range of 7,466-48,866. Based on this discovery, the authors demonstrated that the cellular signals detected by differential pulse voltammetry (DPV) can be rapidly amplified with a developed medium containing metabolic activator cocktails (MACs). The DPV approach combined with MAC treatment shows a remarkable performance to detect the effects of the anticancer drug CPI-613 on cervical cancer both at a low drug concentration (2 µm) and an extremely short treatment time (1 hour). Furthermore, the senescence of mesenchymal stem cells could also be sensitively quantified using the DPV+MAC method even at a low passage number (P6). Collectively, their findings unveiled the origin of redox signals in living cells, which has important implications for the characterization of various cellular functions and behaviors using electrochemical approaches.

Simple In Vitro 18O Labeling for Improved Mass Spectrometry-Based Drug Metabolites Identification: Deep Drug Metabolism Study

The identification of drug metabolites formed with different in vitro systems by HPLC-MS is a standard step in preclinical research. In vitro systems allow modeling of real metabolic pathways of a drug candidate. Despite the emergence of various software and databases, identification of compounds is still a complex task. Measurement of the accurate mass, correlation of chromatographic retention times and fragmentation spectra are often insufficient for identification of compounds especially in the absence of reference materials. Metabolites can "slip under the nose", since it is often not possible to reliably confirm that a signal belongs to a metabolite and not to other compounds in complex systems. Isotope labeling has proved to be a tool that aids in small molecule identification. The introduction of heavy isotopes is done with isotope exchange reactions or with complicated synthetic schemes. Here, we present an approach based on the biocatalytic insertion of oxygen-18 isotope under the action of liver microsomes enzymes in the presence of ¹⁸O₂. Using the local anesthetic bupivacaine as an example, more than 20 previously unknown metabolites were reliably discovered and annotated in the absence of the reference materials. In combination with high-resolution mass spectrometry and modern methods of mass spectrometric metabolism data processing, we demonstrated the ability of the proposed approach to increase the degree of confidence in interpretating metabolism data.

In Silico Screening of Drugs That Target Different Forms of E Protein for Potential Treatment of COVID-19

Recently the E protein of SARS-CoV-2 has become a very important target in the potential treatment of COVID-19 since it is known to regulate different stages of the viral cycle. There is biochemical evidence that E protein exists in two forms, as monomer and homopentamer. An in silico screening analysis was carried out employing 5852 ligands (from Zinc databases), and performing an ADMET analysis, remaining a set of 2155 compounds. Furthermore, docking analysis was performed on specific sites and different forms of the E protein. From this study we could identify that the following ligands showed the highest binding affinity: nilotinib, dutasteride, irinotecan, saquinavir and alectinib. We carried out some molecular dynamics simulations and free energy MM–PBSA calculations of the protein–ligand complexes (with the mentioned ligands). Of worthy interest is that saquinavir, nilotinib and alectinib are also considered as a promising multitarget ligand because it seems to inhibit three targets, which play an important role in the viral cycle. On the other side, saquinavir was shown to be able to bind to E protein both in its monomeric as well as pentameric forms. Finally, further experimental assays are needed to probe our hypothesis derived from in silico studies.

Where Microneedle Meets Biomarkers: Futuristic Application for Diagnosing and Monitoring Localized External Organ Diseases

Extracellular tissue fluids are interesting biomatrices that have recently attracted scientists' interest. Many significant biomarkers for localized external organ diseases have been isolated from this biofluid. In the diagnostic and disease monitoring context, measuring biochemical entities from the fluids surrounding the diseased tissues may give more important clinical value than measuring them at a systemic level. Despite all these facts, pushing tissue fluid-based diagnosis and monitoring forward to clinical settings faces one major problem: its accessibility. Most extracellular tissue fluid, such as interstitial fluid (ISF), is abundant but hard to collect, and the currently available technologies are invasive and expensive. This is where novel microneedle technology can help tackle this significant obstacle. The ability of microneedle technology to minimally invasively access tissue fluid-containing biomarkers will enable ISF and other tissue fluid utilization in the clinical diagnosis and monitoring of localized diseases. This review attempts to present the current pursuit of the application of microneedle systems as a diagnostic and monitoring platform, along with the recent progress of biomarker detection in diagnosing and monitoring localized external organ diseases. Then, the potential use of various microneedles in future clinical diagnostics and monitoring of localized diseases is discussed by presenting the currently studied cases.

Precise engineering of disulfide bond-bridged prodrug nanoassemblies to balance antitumor efficacy and safety

Prodrug-based nanoassemblies, which combine the merits of prodrug technology and nanocarriers, are regarded as promising platforms for cancer treatment. Notably, the chemical structure of prodrugs is closely associated with antitumor efficacy and safety, and the intrinsic relationships among them need further exploration. Herein, paclitaxel was conjugated with 2-octyldodecan-1-ol through different positions of disulfide bond to construct the prodrug nanoassemblies. Interestingly, the minor differences in chemical structure not only dominated the assembly performance and drug release of nanoassemblies, but also significantly impacted the pharmacokinetics, antitumor efficacy, and safety. It was worth noting that prodrug nanoassemblies with one carbon atom between disulfide bond and ester bond had faster drug release and better antitumor effect, while prodrug nanoassemblies with three carbon atoms between disulfide bond and ester bond possessed moderate antitumor effect and better safety. Our findings illustrated the structure-function relationships of self-assembled prodrugs and provided a promising paradigm for the precise engineering of advanced prodrug nanoplatforms. STATEMENT OF SIGNIFICANCE: 1. The major effects of minor differences in prodrug chemical structure on pharmacodynamics and safety were explored, which had important clinical reference significance and value. 2. The in-depth exploration of structure-function relationships to balance efficacy and safety had important guiding significance for the design of prodrug nanoassemblies.

Regulation of Nuclear Receptors PXR and CAR by Small Molecules and Signal Crosstalk: Roles in Drug Metabolism and Beyond

Pregnane X receptor (PXR) and constitutive androstane receptor (CAR) are ligand-activated transcription factors that regulate the expression of drug metabolizing enzymes and drug transporters. Since their discoveries, they have been studied as important factors for regulating processes related to drug efficacy, drug toxicity, and drug-drug interactions. However, their vast ligand-binding profiles extend into additional spaces, such as endogenously produced chemicals, microbiome metabolites, dietary compounds, and environmental pollutants. Therefore, PXR and CAR can respond to an enormous abundance of stimuli, resulting in significant shifts in metabolic programs and physiologic homeostasis. Naturally, PXR and CAR have been implicated in various diseases related to homeostatic perturbations, such as inflammatory bowel disorders, diabetes, and certain cancers. Recent findings have injected the field with new signaling mechanisms and tools to dissect the complex PXR and CAR biology and have strengthened the potential for future PXR and CAR modulators in the clinic. Here, we describe the historical and ongoing importance of PXR and CAR in drug metabolism pathways and how this history has evolved into new mechanisms that regulate and are regulated by these xenobiotic receptors, with a specific focus on small molecule ligands. To effectively convey the impact of newly emerging research, we have arranged five diverse and representative key recent advances, four specific challenges, and four perspectives on future directions. SIGNIFICANCE STATEMENT: PXR and CAR are key transcription factors that regulate homeostatic detoxification of the liver and intestines. Diverse chemicals bind to these nuclear receptors, triggering their transcriptional tuning of the cellular metabolic response. This minireview revisits the importance of PXR and CAR in pharmaceutical drug responses and highlights recent results with implications beyond drug metabolism.

Qualification of Human Liver Microsomes for Antibacterial Activity Screening of Drug Metabolites

Microsomes are commonly used to perform in vitro drug metabolism, predominantly to form phase I drug metabolites. Pooled microsomes from multiple donors can contain microorganisms from underlying microbial diseases. Exposure to microbes can also occur during extraction if aseptic processing is compromised. Although microbial presence does not affect the metabolic activity of microsomes, presence of unwanted microorganisms can cause interference if the downstream application of microsomal drug metabolites is screening for antibacterial activity. In this work, traditional biochemical tests and advanced proteomics-based identification techniques were used to identify two gram-negative bacteria in pooled human liver microsomes. Several decontamination procedures were assessed to eradicate these two bacteria from the microsomes without affecting its metabolic capacity, and organic extraction was found to be the most convenient and efficient approach to decontaminate microsomes and screen drug metabolites for antibacterial activity against methicillin-resistant Staphylococcus aureus (MRSA).

Recent advances of tanshinone in regulating autophagy for medicinal research

Initially described as an ancient and highly conserved catabolic biofunction, autophagy plays a significant role in disease pathogenesis and progression. As the bioactive ingredient of Salvia miltiorrhiza, tanshinone has recently shown profound effects in alleviating and treating various diseases by regulating autophagy. However, compared to the remarkable achievements in the known pharmacological effects of this traditional Chinese medicine, there is a lack of a concise and comprehensive review deciphering the mechanism by which tanshinone regulates autophagy for medicinal research. In this context, we concisely review the advances of tanshinone in regulating autophagy for medicinal research, including human cancer, the nervous system, and cardiovascular diseases. The pharmacological effects of tanshinone targeting autophagy involve the regulation of autophagy-related proteins, such as Beclin-1, LC3-II, P62, ULK1, Bax, ATG3, ATG5, ATG7, ATG9, and ATG12; the regulation of the PI3K/Akt/mTOR, MEK/ERK/mTOR, Beclin-1-related, and AMPK-related signaling pathways; the accumulation of reactive oxygen species (ROS); and the activation of AMPK. Notably, we found that tanshinone played a dual role in human cancers in an autophagic manner, which may provide a new avenue for potential clinical application. In brief, these findings on autophagic tanshinone and its derivatives provide a new clue for expediting medicinal research related to tanshinone compounds and autophagy.

Computational Evaluation of Azadirachta indica-Derived Bioactive Compounds as Potential Inhibitors of NLRP3 in the Treatment of Alzheimer's Disease

BACKGROUND

The development of therapeutic agents against Alzheimer's disease (AD) has stalled recently. Drug candidates targeting amyloid-β (Aβ) deposition have often failed clinical trials at different stages, prompting the search for novel targets for AD therapy. The NLRP3 inflammasome is an integral part of innate immunity, contributing to neuroinflammation and AD pathophysiology. Thus, it has become a promising new target for AD therapy.

OBJECTIVE

The study sought to investigate the potential of bioactive compounds derived from Azadirachta-indica to inhibit the NLRP3 protein implicated in the pathophysiology of AD.

METHODS

Structural bioinformatics via molecular docking and density functional theory (DFT) analysis was utilized for the identification of novel NLRP3 inhibitors from A. indica bioactive compounds. The compounds were further subjected to pharmacokinetic and drug-likeness analysis. Results obtained from the compounds were compared against that of oridonin, a known NLRP3 inhibitor.

RESULTS

The studied compounds optimally saturated the binding site of the NLRP3 NACHT domain, forming principal interactions with the different amino acids at its binding site. The studied compounds also demonstrated better bioactivity and chemical reactivity as ascertained by DFT analysis and all the compounds except 7-desacetyl-7-benzoylazadiradione, which had two violations, conformed to Lipinski's rule of five.

CONCLUSION

In silico studies show that A. indica derived compounds have better inhibitory potential against NLRP3 and better pharmacokinetic profiles when compared with the reference ligand (oridonin). These compounds are thus proposed as novel NLRP3 inhibitors for the treatment of AD. Further wet-lab studies are needed to confirm the potency of the studied compounds.