Investigation of Janus Kinase (JAK) Inhibitors for Lung Delivery and the Importance of Aldehyde Oxidase Metabolism

Cooperation between the Cu+ and Cu2+ species in CuCoAl layered double hydroxide and the substrate promoting effect afford a really simple protocol for the efficient synthesis of quinazolines

In this study, a really simple and efficient catalytic protocol for the construction of quinazolines from alcohol and diamine has been developed based on CuCoAl layered double hydroxide (CuCoAl-LDH). The developed CuCoAl-LDH catalyst could accelerate the cascade reactions without any additives and tolerate various alcohols with satisfactory yields. Cooperation between the Cu+ and Cu2+ species in CuCoAl-LDH was observed in the cascade reaction, and they are believed to be responsible for the oxidation of alcohol and dehydrogenation of the intermediate, respectively. The promoting effect of the substrate diamine was observed in the oxidation of alcohol, which simplifies the reaction system by eliminating the requirement for a base additive. The catalytic system exhibited highly practical potential for the synthesis of quinazolines, as demonstrated through recyclability investigations and scale-up experiments. A possible catalytic mechanism has been proposed based on a series of control experiments and EPR analysis.

Designing inhaled small molecule drugs for severe respiratory diseases: an overview of the challenges and opportunities

INTRODUCTION

Inhaled drugs offer advantages for the treatment of respiratory diseases over oral drugs by delivering the drug directly to the lung, thus improving the therapeutic index. There is an unmet medical need for novel therapies for lung diseases, exacerbated by a multitude of challenges for the design of inhaled small molecule drugs.

AREAS COVERED

The authors review the challenges and opportunities for the design of inhaled drugs for respiratory diseases with a focus on new target discovery, medicinal chemistry, and pharmacokinetic, pharmacodynamic, and toxicological evaluation of drug candidates.

EXPERT OPINION

Inhaled drug discovery is facing multiple unique challenges. Novel biological targets are scarce, as is the guidance for medicinal chemistry teams to design compounds with inhalation-compatible features. It is exceedingly difficult to establish a PK/PD relationship given the complexity of pulmonary PK and the impact of physical properties of the drug substance on PK. PK, PD and toxicology studies are technically challenging and require large amounts of drug substance. Despite the current challenges, the authors foresee that the design of inhaled drugs will be facilitated in the future by our increasing understanding of pathobiology, emerging medicinal chemistry guidelines, advances in drug formulation, PBPK models, and in vitro toxicology assays.

Transfer learning enhanced graph neural network for aldehyde oxidase metabolism prediction and its experimental application

Aldehyde oxidase (AOX) is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics. AOX-mediated metabolism can result in unexpected outcomes, such as the production of toxic metabolites and high metabolic clearance, which can lead to the clinical failure of novel therapeutic agents. Computational models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism liability. In this study, we developed a novel graph neural network called AOMP for predicting AOX-mediated metabolism. AOMP integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction, while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both tasks. AOMP significantly outperformed the benchmark methods in both cross-validation and external testing. Using AOMP, we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability, which were validated through in vitro experiments. Furthermore, for the convenience of the community, we established the first online service for AOX metabolism prediction based on AOMP, which is freely available at https://aomp.alphama.com.cn.

Priority index for asthma (PIA): In silico discovery of shared and distinct drug targets for adult- and childhood-onset disease

Asthma is a chronic disease that is caused by a combination of genetic risks and environmental triggers and can affect both adults and children. Genome-wide association studies have revealed partly distinct genetic architectures for its two age-of-onset subtypes (namely, adult-onset and childhood-onset). We reason that identifying shared and distinct drug targets between these subtypes may inform the development of subtype-specific therapeutic strategies. In attempting this, we here introduce Priority Index for Asthma or PIA, a genetics-led and network-driven drug target prioritisation tool for asthma. We demonstrate the validity of the tool in improving drug target prioritisation for asthma compared to the status quo methods, as well as in capturing the underlying etiology and existing therapeutics for the disease. We also illustrate how PIA can be used to prioritise drug targets for adult- and childhood-onset asthma, as well as to identify shared and distinct pathway crosstalk genes. Shared crosstalk genes are mostly involved in JAK-STAT signaling, with clinical evidence supporting that targeting this pathway may be a promising drug repurposing opportunity for both subtypes. Crosstalk genes specific to childhood-onset asthma are enriched for PI3K-AKT-mTOR signaling, and we identify genes that are already targeted by licensed medications as repurposed drug candidates for this subtype. We make all our results accessible and reproducible at http://www.genetictargets.com/PIA. Collectively, our study has significant implications for asthma computational medicine research and can guide the future development of subtype-specific therapeutic strategies for the disease.

Comparative Anticancer Potentials of Taxifolin and Quercetin Methylated Derivatives against HCT-116 Cell Lines: Effects of O-Methylation on Taxifolin and Quercetin as Preliminary Natural Leads

Six flavonoids present in Pulicaria jaubertii, i.e., 7,3'-di-O-methyltaxifolin (1), 3'-O-methyltaxifolin (2), 7-O-methyltaxifolin (3), taxifolin (4), 3-O-methylquercetin (5), and quercetin (6), were tested for their anticancer activities. The methylated flavonoids, compounds 1-3 and 5, were evaluated for their anticancer activities in comparison to the non-methylated parent flavonoids taxifolin (4) and quercetin (6). The structures of the known compounds were reconfirmed by spectral analyses using ¹H and ¹³C NMR data comparisons and HRMS spectrometry. The anticancer activity of these compounds was evaluated in colon cancer, HCT-116, and noncancerous, HEK-293, cell lines using the MTT antiproliferative assays. The caspase-3 and caspase-9 expressions and DAPI (4', 6-diamidino-2-phenylindole) staining assays were used to evaluate the apoptotic activity. All the compounds exhibited antiproliferative activity against the HCT-116 cell line with IC₅₀ values at 33 ± 1.25, 36 ± 2.25, 34 ± 2.15, 32 ± 2.35, 34 ± 2.65, and 36 ± 1.95 μg/mL for compounds 1 to 6, respectively. All the compounds produced a significant reduction in HCT-116 cell line proliferation, except compounds 2 and 6. The viability of the HEK-293 normal cells was found to be significantly higher than the viability of the cancerous cells at all of the tested concentrations, thus suggesting that all the compounds have better inhibitory activity on the cancer cell line. Apoptotic features such as chromatin condensation and nuclear shrinkage were also induced by the compounds. The expression of caspase-3 and caspase-9 genes increased in HCT-116 cell lines after 48 h of treatment, suggesting cell death by the apoptotic pathways. The molecular docking studies showed favorable binding affinity against different pro- and antiapoptotic proteins by these compounds. The docking scores were minimum as compared to the caspase-9, caspase-3, Bcl-xl, and JAK2.

Drug clearance by aldehyde oxidase: can we avoid clinical failure?

Despite increased awareness of aldehyde oxidase (AO) as a major drug-metabolising enzyme, predicting the pharmacokinetics of its substrates remains challenging. Several drug candidates have been terminated due to high clearance, which were subsequently discovered to be AO substrates. Even retrospective extrapolation of human clearance, from models more sensitive to AO activity, often resulted in underprediction.The questions of the current work thus were: Is there an acceptable degree of in vitro AO metabolism that does not result in high in vivo human clearance? And, if so, how can this be predicted?We built an in vitro/in vivo correlation using known AO substrates, combining multiple in vitro parameters to calculate the blood metabolic clearance mediated by AO (CLb_AO). This value was compared with observed blood clearance (CLb_-obs), establishing cut-off CLb_AO values, to discriminate between low and high CLb_-obs. The model was validated using additional literature compounds, and CLb_-obs was predicted in the correct category.This simple, categorical, semi-quantitative yet multi-factorial model is readily applicable in drug discovery. Further, it is valuable for high-clearance compounds, as it predicts the CLb group, rather than an exact CLb value, for the substrates of this poorly-characterised enzyme.

Roles of selected non-P450 human oxidoreductase enzymes in protective and toxic effects of chemicals: review and compilation of reactions

This is an overview of the metabolic reactions of drugs, natural products, physiological compounds, and other (general) chemicals catalyzed by flavin monooxygenase (FMO), monoamine oxidase (MAO), NAD(P)H quinone oxidoreductase (NQO), and molybdenum hydroxylase enzymes (aldehyde oxidase (AOX) and xanthine oxidoreductase (XOR)), including roles as substrates, inducers, and inhibitors of the enzymes. The metabolism and bioactivation of selected examples of each group (i.e., drugs, “general chemicals,” natural products, and physiological compounds) are discussed. We identified a higher fraction of bioactivation reactions for FMO enzymes compared to other enzymes, predominately involving drugs and general chemicals. With MAO enzymes, physiological compounds predominate as substrates, and some products lead to unwanted side effects or illness. AOX and XOR enzymes are molybdenum hydroxylases that catalyze the oxidation of various heteroaromatic rings and aldehydes and the reduction of a number of different functional groups. While neither of these two enzymes contributes substantially to the metabolism of currently marketed drugs, AOX has become a frequently encountered route of metabolism among drug discovery programs in the past 10–15 years. XOR has even less of a role in the metabolism of clinical drugs and preclinical drug candidates than AOX, likely due to narrower substrate specificity.