Development and interpretation of a QSAR model for in vitro breast cancer (MCF-7) cytotoxicity of 2-phenylacrylonitriles

Aryl hydrocarbon receptor (AHR) signalling: A double-edged sword guiding both cancer progression and cancer therapy

Aryl Hydrocarbon Receptor (AHR) reported to be associated with major carcinogenic signalling cascades which cause cell proliferations, metastasis and invasion as well as immune imbalance. AHR Participates in cellular processes not only through genomic pathways to cause genomic alterations but also via nongenomic pathways to alter various cytoplasmic proteins. In addition, AHR senses a wide range of ligands that modulate its downstream mechanisms that are intricated in cancer induction and prevention. Thus, AHR functions as a two-sided sword where some AHR ligands contribute to enhance cancer whereas few are useful for cancer treatment. Therefore, AHR represent as a regulatory point in cancer progression and treatment. There is a need to reinvestigate the regulatory role of AHR in major intracellular pathways and to explore the potential of AHR ligand for the design of cancer therapeutics. This review emphasizes the interaction of AHR with pro-carcinogenic signalling pathways that modulate cancer induction and progression. Furthermore, it also discusses about the current discovery of AHR ligands for cancer initiation or inhibition. This information could be useful for development of therapeutic strategies for the management of cancer by targeting AHR.

Developing Heterogeneous Porous 3D-Printed SiO2-Pd-K2SiO3 Monolithic Catalyst via Surface MOF Growth and Pyrolysis for the Synthesis of Antitumoral Isatins

Background/Objectives: The isatin nucleus is a privileged scaffold in drug discovery, particularly due to its proven relevance in anticancer research. Developing reusable heterogeneous 3D catalysts for drug synthesis represents a critical challenge in both industrial and academic contexts. This multi and interdisciplinary work aimed to design and synthesize a novel 3D-printed silica-based porous catalyst functionalized with palladium, evaluate its catalytic performance in isatin drug synthesis, and assess the antiproliferative activity of the resulting compounds against tumor cell lines such as HeLa, MCF-7, and MDA-MB231. Methods: The novel multifaceted approach to synthesizing this heterogeneous catalyst involved the surface growth of a metal-organic framework (ZIF-8) on 3D-printed silica support, followed by potassium silicate coating and pyrolysis. Results: After detailed physicochemical characterization, the catalyst was tested in challenging "double" palladium-catalyzed cross-coupling reactions (Suzuki, Stille, and Heck), demonstrating robustness, reusability, and high efficiency in producing bis-1,5-aryl, alkynyl, and alkenyl-isatin derivatives. Importantly, no leaching of palladium species was detected during the catalytic cycles, further underscoring the stability of the system. These isatin-based compounds exhibited remarkable cytotoxicity, with selective molecules achieving nanomolar potency against MCF-7 cells, surpassing reference drugs such as doxorubicin and sunitinib. Conclusions: This study not only introduces a novel strategy for fabricating porous heterogeneous catalysts from sintered surfaces but also highlights new biomolecules with promising applications in cancer research.

QSAR Regression Models for Predicting HMG-CoA Reductase Inhibition

BACKGROUND/OBJECTIVES

HMG-CoA reductase is an enzyme that regulates the initial stage of cholesterol synthesis, and its inhibitors are widely used in the treatment of cardiovascular diseases.

METHODS

We have created a set of quantitative structure-activity relationship (QSAR) models for human HMG-CoA reductase inhibitors using nested cross-validation as the primary validation method. To develop the QSAR models, we employed various machine learning regression algorithms, feature selection methods, and fingerprints or descriptor datasets.

RESULTS

We built and evaluated a total of 300 models, selecting 21 that demonstrated good performance (coefficient of determination, R2 ≥ 0.70 or concordance correlation coefficient, CCC ≥ 0.85). Six of these top-performing models met both performance criteria and were used to construct five ensemble models. We identified the descriptors most important in explaining HMG-CoA inhibition for each of the six best-performing models. We used the top models to search through over 220,000 chemical compounds from a large database (ZINC 15) for potential new inhibitors. Only a small fraction (237 out of approximately 220,000 compounds) had reliable predictions with mean pIC50 values ≥ 8 (IC50 values ≤ 10 nM). Our svm-based ensemble model predicted IC50 values < 10 nM for roughly 0.08% of the screened compounds. We have also illustrated the potential applications of these QSAR models in understanding the cholesterol-lowering activities of herbal extracts, such as those reported for an extract prepared from the Iris × germanica rhizome.

CONCLUSIONS

Our QSAR models can accurately predict human HMG-CoA reductase inhibitors, having the potential to accelerate the discovery of novel cholesterol-lowering agents and may also be applied to understand the mechanisms underlying the reported cholesterol-lowering activities of herbal extracts.

Structural effects of sulfonamides on the proliferation dynamics of sulfonamide resistance genes in the sequencing batch reactors and the mechanism

Antibiotic resistance genes (ARGs) can be easily promoted by antibiotics, however, the structural effects of antibiotics on the proliferation of ARGs dynamic and the associated mechanisms remain obscure in, especially, activated sludge sequencing batch reactors. In the present study, the effects of 9 sulfonamides (SAs) with different structures on the proliferation dynamic of sulfonamide resistance genes (Suls) in the activated sludge sequencing batch reactors and the corresponding mechanisms were determined (30 days), and the results showed that the largest proliferation value (∆AR) of Suls dynamic for SAs (sulfachloropyridazine) was approximately 2.9 times than that of the smallest one (sulfadiazine). The proliferation of Suls was significantly related to the structural features (minHBint6, SssNH, SHBd and SpMax2_Bhm) that represent the biological activity of SAs. To interpret the phenomenon, a mechanistic model was developed and the results indicated that the biodegradation of SAs (T1/2) rather than conjugative transfer frequency or mutation frequency tends to be the key process for affecting Suls proliferation. T1/2 was proved to be dependent on the interactions between SAs and receptors (Ebinding), the cleavage mode (bond dissociation energy), and the site of nucleophilic assault. Besides, the metagenomic analysis showed that SAs posed significant effect on antibiotic resistome and Tnp31 played a vital role in the proliferation of Suls. Overall, our findings provide important insight into a theoretical basis for understanding the structural effects of SAs on the proliferation of ARGs in SBR systems.

Aryl Hydrocarbon Receptor as an Anticancer Target: An Overview of Ten Years Odyssey

Aryl hydrocarbon receptor (AhR), a ligand-activated transcription factor belonging to the basic helix-loop-helix (bHLH)/per-Arnt-sim (PAS) superfamily, is traditionally known to mediate xenobiotic metabolism. It is activated by structurally diverse agonistic ligands and regulates complicated transcriptional processes through its canonical and non-canonical pathways in normal and malignant cells. Different classes of AhR ligands have been evaluated as anticancer agents in different cancer cells and exhibit efficiency, which has thrust AhR into the limelight as a promising molecular target. There is strong evidence demonstrating the anticancer potential of exogenous AhR agonists including synthetic, pharmaceutical, and natural compounds. In contrast, several reports have indicated inhibition of AhR activity by antagonistic ligands as a potential therapeutic strategy. Interestingly, similar AhR ligands exert variable anticancer or cancer-promoting potential in a cell- and tissue-specific mode of action. Recently, ligand-mediated modulation of AhR signaling pathways and the associated tumor microenvironment is emerging as a potential approach for developing cancer immunotherapeutic drugs. This article reviews advances of AhR in cancer research covering publication from 2012 to early 2023. It summarizes the therapeutic potential of various AhR ligands with an emphasis on exogenous ligands. It also sheds light on recent immunotherapeutic strategies involving AhR.

The Role of the Aryl Hydrocarbon Receptor (AhR) and Its Ligands in Breast Cancer

Breast cancer is a complex disease which is defined by numerous cellular and molecular markers that can be used to develop more targeted and successful therapies. The aryl hydrocarbon receptor (AhR) is overexpressed in many breast tumor sub-types, including estrogen receptor -positive (ER+) tumors; however, the prognostic value of the AhR for breast cancer patient survival is not consistent between studies. Moreover, the functional role of the AhR in various breast cancer cell lines is also variable and exhibits both tumor promoter- and tumor suppressor- like activity and the AhR is expressed in both ER-positive and ER-negative cells/tumors. There is strong evidence demonstrating inhibitory AhR-Rα crosstalk where various AhR ligands induce ER degradation. It has also been reported that different structural classes of AhR ligands, including halogenated aromatics, polynuclear aromatics, synthetic drugs and other pharmaceuticals, health promoting phytochemical-derived natural products and endogenous AhR-active compounds inhibit one or more of breast cancer cell proliferation, survival, migration/invasion, and metastasis. AhR-dependent mechanisms for the inhibition of breast cancer by AhR agonists are variable and include the downregulation of multiple genes/gene products such as CXCR4, MMPs, CXCL12, SOX4 and the modulation of microRNA levels. Some AhR ligands, such as aminoflavone, have been investigated in clinical trials for their anticancer activity against breast cancer. In contrast, several publications have reported that AhR agonists and antagonists enhance and inhibit mammary carcinogenesis, respectively, and differences between the anticancer activities of AhR agonists in breast cancer may be due in part to cell context and ligand structure. However, there are reports showing that the same AhR ligand in the same breast cancer cell line gives opposite results. These differences need to be resolved in order to further develop and take advantage of promising agents that inhibit mammary carcinogenesis by targeting the AhR.

Prediction and Screening Model for Products Based on Fusion Regression and XGBoost Classification

Performance prediction based on candidates and screening based on predicted performance value are the core of product development. For example, the performance prediction and screening of equipment components and parts are an important guarantee for the reliability of equipment products. The prediction and screening of drug bioactivity value and performance are the keys to pharmaceutical product development. The main reasons for the failure of pharmaceutical discovery are the low bioactivity of the candidate compounds and the deficiencies in their efficacy and safety, which are related to the absorption, distribution, metabolism, excretion, and toxicity (ADMET) of the compounds. Therefore, it is very necessary to quickly and effectively perform systematic bioactivity value prediction and ADMET property evaluation for candidate compounds in the early stage of drug discovery. In this paper, a data-driven pharmaceutical products screening prediction model is proposed to screen drug candidates with higher bioactivity value and better ADMET properties. First, a quantitative prediction method for bioactivity value is proposed using the fusion regression of LGBM and neural network based on backpropagation (BP-NN). Then, the ADMET properties prediction method is proposed using XGBoost. According to the predicted bioactivity value and ADMET properties, the BVAP method is defined to screen the drug candidates. And the screening model is validated on the dataset of antagonized Erα active compounds, in which the mean square error (MSE) of fusion regression is 1.1496, the XGBoost prediction accuracy of ADMET properties are 94.0% for Caco-2, 95.7% for CYP3A4, 89.4% for HERG, 88.6% for hob, and 96.2% for Mn. Compared with the commonly used methods for ADMET properties such as SVM, RF, KNN, LDA, and NB, the XGBoost in this paper has the highest prediction accuracy and AUC value, which has better guiding significance and can help screen pharmaceutical product candidates with good bioactivity, pharmacokinetic properties, and safety.

Amino Alcohols as Potential Antibiotic and Antifungal Leads

Five focused compound libraries (forty-nine compounds), based on prior studies in our laboratory were synthesized and screened for antibiotic and anti-fungal activity against S. aureus, E. coli, K. pneumoniae, P. aeruginosa, A. baumannii, C. albicans and C. neoformans. Low levels of activity, at the initial screening concentration of 32 μg/mL, were noted with analogues of (Z)-2-(3,4-dichlorophenyl)-3-phenylacrylonitriles which made up the first two focused libraries produced. The most promising analogues possessing additional substituents on the terminal aromatic ring of the synthesised acrylonitriles. Modifications of the terminal aromatic moiety were explored through epoxide installation flowed by flow chemistry mediated ring opening aminolysis with discreet sets of amines to the corresponding amino alcohols. Three new focused libraries were developed from substituted anilines, cyclic amines, and phenyl linked heterocyclic amines. The aniline-based compounds were inactive against the bacterial and fungal lines screened. The introduction of a cyclic, such as piperidine, piperazine, or morpholine, showed >50% inhibition when evaluated at 32 μg/mL compound concentration against methicillin-resistant Staphylococcus aureus. Examination of the terminal aromatic substituent via oxirane aminolysis allowed for the synthesis of three new focused libraries of afforded amino alcohols. Aromatic substituted piperidine or piperazine switched library activity from antibacterial to anti-fungal activity with ((Z)-2-(3,4-dichlorophenyl)-3-(4-(2-hydroxy-3-(4-methylpiperazin-1-yl)propoxy)phenyl)acrylonitrile), ((Z)-2-(3,4-dichlorophenyl)-3-(4-(2-hydroxy-3-(4-(4-hydroxyphenyl)piperazin-1-yl)propoxy)-phenyl)acrylonitrile) and ((Z)-3-(4-(3-(4-cyclohexylpiperazin-1-yl)-2-hydroxypropoxy)-phenyl)-2-(3,4-dichlorophenyl)-acrylonitrile) showing >95% inhibition of Cryptococcus neoformans var. grubii H99 growth at 32 μg/mL. While (Z)-3-(4-(3-(cyclohexylamino)-2-hydroxypropoxy)phenyl)-2-(3,4-dichlorophenyl)-acrylonitrile, (S,Z)-2-(3,4-dichlorophenyl)-3-(4-(2-hydroxy-3-(piperidin-1-yl)propoxy)phenyl)acrylonitrile, (R,Z)-2-(3,4-dichlorophenyl)-3-(4-(2-hydroxy-3-(piperidin-1-yl)propoxy)phenyl)acrylonitrile, (Z)-2-(3,4-dichlorophenyl)-3-(4-(2-hydroxy-3-(D-11-piperidin-1-yl)propoxy)phenyl)-acrylonitrile, and (Z)-3-(4-(3-(4-cyclohexylpiperazin-1-yl)-2-hydroxypropoxy)-phenyl)-2-(3,4-dichlorophenyl)-acrylonitrile 32 μg/mL against Staphylococcus aureus.