Metabolomics and In Silico Docking-Directed Discovery of Small-Molecule Enzyme Targets

Medium-Chain Chlorinated Paraffins Trigger Thyroid Hormone Synthesis and Interfere with Mitochondrial Function in the Thyroid Gland

Medium-chain chlorinated paraffins (MCCPs, C14-C17) are frequently detected in diverse environmental media. It has been proposed to be listed in Annex A of the Convention on Persistent Organic Pollutants in 2023. Although MCCPs are a crucial health concern, their toxicity remains unclear. This study investigated the toxic effects of MCCPs (0.1-50 mg/kg body weight/day) on the thyroid gland of female Sprague-Dawley rats and characterized the potential toxic pathways via transcriptomics and metabolomics approaches. MCCPs exposure caused histopathological changes to the endoplasmic reticula and mitochondria in thyroid follicular cells at a dose of 50 mg/kg bw/d and increased serum thyrotropin-releasing hormone, thyroid-stimulating hormones, and thyroxine when exposed to a higher dose of MCCPs. Transcriptomic analysis indicated the excessive expression of key genes related to thyroid hormone synthesis induced by MCCPs. Integrating the dual-omics analysis revealed mitochondrial dysfunction of the thyroid by mediating fatty acid oxidation, Kreb's cycle, and oxidative phosphorylation. Significant metabolic toxicity on the thyroid might be linked to the characteristics of the chlorine content of MCCPs. This study revealed the toxicity of MCCPs to the thyroid gland via triggering thyroid hormone synthesis and interfering with mitochondrial function, which can provide new insights into the modes of action and mechanism-based risk assessment of MCCPs.

Synthesis of dimeric 1,2-benzothiazine 1,1-dioxide scaffolds: molecular structures, Hirshfeld surface analysis, DFT and enzyme inhibition studies

1,2-Benzothiazines are bioactive compounds with diverse pharmacological properties. We report here the synthesis of a series of dimers containing 1,2-benzothiazine scaffolds as potential pharmacophores. The characterization of compounds was done using analytical techniques such as FT-IR, 1H NMR, and elemental analyses. The molecular structures of the compounds (5-8) were confirmed by X-ray crystallography. The molecular interactions in compounds (5-8) were determined by Hirshfeld Surface Analysis (HSA). Density functional theory (DFT) investigations were carried out to calculate vibrational properties, NMR behaviour, dipole moments, molecular electrostatic potential (MEP), frontier molecular orbital (FMO), natural bonding orbital (NBO) analysis and global reactivity descriptors. The global reactivity descriptors indicated the charge transfer reactions and stabilized as follows: 8 > 7 > 6 > 5. In FMO analysis a substantial HOMO-LUMO gap, ranging from 4.43 to 5.12 eV, with high LUMO values was observed for all compounds, while the highest value for linear polarizability was found in compound 8. The in vitro and in silico studies confirm that compound 8 is more active toward AChE and BChE enzymes.

Metabolomics and mitochondrial dysfunction in cardiometabolic disease

Circulating metabolites are indicators of systemic metabolic dysfunction and can be detected through contemporary techniques in metabolomics. These metabolites are involved in numerous mitochondrial metabolic processes including glycolysis, fatty acid β-oxidation, and amino acid catabolism, and changes in the abundance of these metabolites is implicated in the pathogenesis of cardiometabolic diseases (CMDs). Epigenetic regulation and direct metabolite-protein interactions modulate metabolism, both within cells and in the circulation. Dysfunction of multiple mitochondrial components stemming from mitochondrial DNA mutations are implicated in disease pathogenesis. This review will summarize the current state of knowledge regarding: i) the interactions between metabolites found within the mitochondrial environment during CMDs, ii) various metabolites' effects on cellular and systemic function, iii) how harnessing the power of metabolomic analyses represents the next frontier of precision medicine, and iv) how these concepts integrate to expand the clinical potential for translational cardiometabolic medicine.

In Vitro and In Silico Activities of E. radiata and E. cinerea as an Enhancer of Antibacterial, Antioxidant, and Anti-Inflammatory Agents

Eucalyptus, a therapeutic plant mentioned in the ancient Algerian pharmacopeia, specifically two species belonging to the Myrtaceae family, E. radiata and E. cinerea, were investigated in this study for their antibacterial, antioxidant, and anti-inflammatory properties. The study used aqueous extracts (AE) obtained from these plants, and the extraction yields were found to be different. The in vitro antibacterial activity was evaluated using a disc diffusion assay against three typical bacterial strains. The results showed that the two extracts were effective against all three strains. Both extracts displayed significant antioxidant activity compared to BHT. The anti-inflammatory impact was evaluated using a protein (BSA) inhibition denaturation test. The E. radiata extract was found to inhibit inflammation by 85% at a concentration of 250 µg/mL, significantly higher than the Aspirin. All phytoconstituents present good pharmacokinetic characteristics without toxicity except very slight toxicity of terpineol and cineol and a maximum binding energy of -7.53 kcal/mol for its anti-TyrRS activity in silico. The study suggests that the extracts and their primary phytochemicals could enhance the efficacy of antibiotics, antioxidants, and non-steroidal anti-inflammatory drugs (NSAIDs). As pharmaceutical engineering experts, we believe this research contributes to developing natural-based drugs with potential therapeutic benefits.

Natural compounds as lactate dehydrogenase inhibitors: potential therapeutics for lactate dehydrogenase inhibitors-related diseases

Lactate dehydrogenase (LDH) is a crucial enzyme involved in energy metabolism and present in various cells throughout the body. Its diverse physiological functions encompass glycolysis, and its abnormal activity is associated with numerous diseases. Targeting LDH has emerged as a vital approach in drug discovery, leading to the identification of LDH inhibitors among natural compounds, such as polyphenols, alkaloids, and terpenoids. These compounds demonstrate therapeutic potential against LDH-related diseases, including anti-cancer effects. However, challenges concerning limited bioavailability, poor solubility, and potential toxicity must be addressed. Combining natural compounds with LDH inhibitors has led to promising outcomes in preclinical studies. This review highlights the promise of natural compounds as LDH inhibitors for treating cancer, cardiovascular, and neurodegenerative diseases.

An integrated strategy to study the combination mechanisms of Bupleurum chinense DC and Paeonia lactiflora Pall for treating depression based on correlation analysis between serum chemical components profiles and endogenous metabolites profiles

ETHNOPHARMACOLOGICAL RELEVANCE

Bupleurum chinense DC-Paeonia lactiflora Pall (BCD-PLP) is a common clinical herb pair in traditional Chinese medicine (TCM) prescriptions commonly used to treat depression. However, its combination mechanisms with its anti-depressive effects remain highly unclear.

AIM OF THE STUDY

Here, an effective strategy has been developed to study the combination mechanisms of Bupleurum chinense DC (BCD) and Paeonia lactiflora Pall (PLP) by integrating serum pharmacochemistry analysis, metabolomics technology, and molecular docking technology.

MATERIALS AND METHODS

First, the depression model rats were replicated by the chronic unpredictable mild stress (CUMS) procedure, and the difference in the chemical composition in vivo before and after the combination of BCD and PLP was analyzed by integrating background subtraction and multivariate statistical analysis techniques. Then, UPLC/HRMS-based serum metabolomics was performed to analyze the synergistic effect on metabolite regulation before and after the combination of BCD and PLP. Further, the correlation analysis between the differential exogenous chemical components and the differential endogenous metabolites before and after the combination was employed to dissect the combination mechanisms from a global perspective of combining metabolomics and serum pharmacochemistry. Finally, the molecular docking between the differential chemical components and the key metabolic enzymes was applied to verify the regulatory effect of the differential exogenous chemical components on the differential endogenous metabolites.

RESULTS

The serum pharmacochemistry analysis results demonstrated that the combination of BCD and PLP could significantly affect the content of 10 components in BCD (including 5 prototype components were significantly decreased and 5 metabolites were significantly increased) and 8 components in PLP (including 4 prototype components and 3 metabolites were significantly increased, 1 metabolite was significantly decreased), which indicated that the combination could enhance BCD prototype components' metabolism and the absorption of the PLP prototype components. Besides, metabolomics results indicated that the BCD-PLP herb pair group significantly reversed more metabolites (8) than BCD and PLP single herb group (5 & 4) and has a stronger regulatory effect on metabolite disorders caused by CUMS. Furthermore, the correlation analysis results suggested that saikogenin F and saikogenin G were significantly positively correlated with the endogenous metabolite itaconate, an endogenous anti-inflammatory metabolite; and benzoic acid was significantly positively correlated with D-serine, an endogenous metabolite with an antidepressant effect. Finally, the molecular docking results further confirmed that the combination of BCD and PLP could affect the activities of cis-aconitic acid decarboxylase and D-amino acid oxidase by increasing the in vivo concentration of saikogenin F and benzoic acid, which further enhances its anti-inflammatory activity and anti-depressive effect.

CONCLUSIONS

In this study, an effective strategy has been developed to study the combination mechanisms of BCD and PLP by integrating serum pharmacochemistry analysis, multivariate statistical analysis, metabolomics technology, and molecular docking technology. Based on this strategy, the present study indicated that the combination of BCD and PLP could affect the activities of cis-aconitic acid decarboxylase and D-amino acid oxidase by increasing the concentration of saikogenin F and benzoic acid in vivo, which further enhances its anti-depressive effect. In short, this strategy will provide a reliable method for elucidating the herb-herb compatibility mechanism of TCM.

Chiral zinc oxide functionalized quartz crystal microbalance sensor for enantioselective recognition of amino acids

Chiral transition metal oxides with tunable structures and multiple physicochemical features have been increasingly applied for chiral sensing and detection. In this work, chiral zinc oxide (ZnO) was first applied as selector to construct quartz crystal microbalance (QCM) sensor for enantioselective recognition of amino acids. The chiral ZnO was prepared by a methionine-induced self-assembly strategy and its high topological chirality was confirmed by several techniques such as circular dichroism spectrum. The chiral discrimination factors were calculated by frequency shifts in response to aspartic acid, phenylalanine, lysine and arginine on L-ZnO surface, achieving 1.89 ± 0.04, 1.76 ± 0.11, 1.66 ± 0.07 and 1.54 ± 0.09, respectively. Notably, L-enantiomers preferred stronger absorptions on L-ZnO surface as compared to D-forms. It was further found that this sensor was appropriate for quantitative analysis and enantiomer excess analysis and adsorption kinetics study. Furthermore, molecular docking revealed the recognition mechanism, where chiral distinction was caused by the different steric interactions between enantiomers and chiral ZnO. This method enjoyed merits of high enantioselectivity, simple preparation and low cost, offering newly chiral sensing method for other molecules.

Inhibition of SARS-CoV2 viral infection with natural antiviral plants constituents: An in-silico approach

Background and Objective

In 2019, a novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) was declared pandemic. Advancement in computational technology has provided rapid and cost-effective techniques to test the efficacy of newer therapeutic agents. This study evaluated some of the potent phytochemicals obtained from AYUSH (Ayurveda, Yoga, Naturopathy, Unani, Siddha, Sowa-Rigpa, and Homeopathy)-listed medicinal plants against SARS-CoV-2 proteins using computational techniques.

Materials and methods

The potential SARS-CoV-2 protein targets were utilized to study the ligand-protein binding characteristics. The bioactive agents were obtained from ashwagandha, liquorice, amla, neem, tinospora, pepper, and stevia. Ivermectin was utilized as a reference agent to compare its efficacy with phytochemicals.

Results

The computational analysis suggested that all the bioactive components from the selected plants possessed negative docking scores (ranging from -6.24 to -10.53). The phytoconstituents were well absorbed, distributed in the body except for the CNS, metabolized by liver enzymes, well cleared from the body, and well tolerated. The data suggest that AYUSH-recommended plants demonstrated therapeutic efficacy against SARS CoV-2 virus infection with significantly reduced toxicity.

Conclusion

The phytoconstituents were found to hinder the early stages of infection, such as absorption and penetration, while ivermectin prevented the passage of genetic material from the cytoplasm to the nucleus. Additional research involving living tissues and clinical trials are suggested to corroborate the computational findings.

Liquid Crystal Monomer: A Potential PPARγ Antagonist

Liquid crystal monomers (LCMs) are a large family of artificial ingredients that have been widely used in global liquid crystal display (LCD) industries. As a major constituent in LCDs as well as the end products of e-waste dismantling, LCMs are of growing research interest with regard to their environmental occurrences and biochemical consequences. Many studies have analyzed LCMs in multiple environmental matrices, yet limited research has investigated the toxic effects upon exposure to them. In this study, we combined in silico simulation and in vitro assay validation along with omics integration analysis to achieve a comprehensive toxicity elucidation as well as a systematic mechanism interpretation of LCMs for the first time. Briefly, the high-throughput virtual screen and reporter gene assay revealed that peroxisome proliferator-activated receptor gamma (PPARγ) was significantly antagonized by certain LCMs. Besides, LCMs induced global metabolome and transcriptome dysregulation in HK2 cells. Notably, fatty acid β-oxidation was conspicuously dysregulated, which might be mediated through multiple pathways (IL-17, TNF, and NF-kB), whereas the activation of AMPK and ligand-dependent PPARγ antagonism may play particularly important parts. This study illustrated LCMs as a potential PPARγ antagonist and explored their toxicological mode of action on the trans-omics level, which provided an insightful overview in future chemical risk assessment.

Recent advances in metabolomics analysis for early drug development

The pharmaceutical industry adapted proteomics and other 'omics technologies for drug research early following their initial introduction. Although metabolomics lacked behind in this development, it has now become an accepted and widely applied approach in early drug development. Over the past few decades, metabolomics has evolved from a pure exploratory tool to a more mature and quantitative biochemical technology. Several metabolomics-based platforms are now applied during the early phases of drug discovery. Metabolomics analysis assists in the definition of the physiological response and target engagement (TE) markers as well as elucidation of the mode of action (MoA) of drug candidates under investigation. In this review, we highlight recent examples and novel developments of metabolomics analyses applied during early drug development.

Dose-response metabolomics and pathway sensitivity to map molecular cartography of bisphenol A exposure

In the toxicological regime, the toxicological endpoint and its dose-response relationship are two of the most prominent characters in conducting a risk assessment for chemical exposure. Systems biological methods have been used to comprehensively characterize the impact of toxicants on the biochemical pathways. However, the majority of the current studies are only based on single-dose, and limited information can be extrapolated to other doses from these experiments, regardless of the sensitivity of each endpoint. This study aims to understand the dose-response metabolite dysregulation pattern and metabolite sensitivity at the system-biological level. Here, we applied bisphenol A (BPA), an endocrine-disrupting chemical (EDC), as the model chemical. We first employed the global metabolomics method to characterize the metabolome of breast cancer cells (MCF-7) upon exposure to different doses (0, 20, 50, and 100 µM) of BPA. The dysregulated features with a clear dose-response relationship were also effectively picked up with an R-package named TOXcms. Overall, most metabolites were dysregulated by showing a significant dose-dependent behaviour. The results suggested that BPA exposure greatly perturbed purine metabolism and pyrimidine metabolism. Interestingly, most metabolites within the purine metabolism were described as a biphasic dose-response relationship. With the established dose-response relationship, we were able to fully map the metabolite cartography of BPA exposure within a wide range of concentrations and observe some unique patterns. Furthermore, an effective concentration of certain fold changes (e.g., EC₊₁₀ means the dose at which metabolite is 10% upregulated) and metabolite sensitivity were defined and introduced to this dose-response omics information. The result showed that the purine metabolism pathway is the most venerable target of BPA, which can be a potential endogenous biomarker for its exposure. Overall, this study applied the dose-response metabolomics method to fully understand the biochemical pathway disruption of BPA treatment at different doses. Both dose-response omics strategy and metabolite sensitivity analysis can be further considered and emphasized in future chemical risk assessments.

A review of environmental metabolism disrupting chemicals and effect biomarkers associating disease risks: Where exposomics meets metabolomics

Humans are exposed to an ever-increasing number of environmental toxicants, some of which have gradually been elucidated to be important risk factors for metabolic diseases, such as diabetes and obesity. These metabolism-sensitive diseases typically occur when key metabolic and signaling pathways were disrupted, which can be influenced by the exposure to contaminants such as endocrine disrupting chemicals (EDCs), along with genetic and lifestyle factors. This promotes the concept and research on environmental metabolism disrupting chemicals (MDCs). In addition, identifying endogenous biochemical markers of effect linked to disease states is becoming an important tool to screen the biological targets following environmental contaminant exposure, as well as to provide an overview of toxicity risk assessment. As such, the current review aims to contribute to the further understanding of exposome and human health and disease by characterizing environmental exposure and effect metabolic biomarkers. We summarized MDC-associated metabolic biomarkers in laboratory animal and human cohort studies using high throughput targeted and nontargeted metabolomics techniques. Contaminants including heavy metals and organohalogen compounds, especially EDCs, have been repetitively associated with metabolic disorders, whereas emerging contaminants such as perfluoroalkyl substances and microplastics have also been found to disrupt metabolism. In addition, we found major limitations in the effective identification of metabolic biomarkers especially in human studies, toxicological research on the mixed effect of environmental exposure has also been insufficient compared to the research on single chemicals. Thus, it is timely to call for research efforts dedicated to the study of combined effect and metabolic alterations for the better assessment of exposomic toxicology and health risks. Moreover, advanced computational and prediction tools, further validation of metabolic biomarkers, as well as systematic and integrative investigations are also needed in order to reliably identify novel biomarkers and elucidate toxicity mechanisms, and to further utilize exposome and metabolome profiling in public health and safety management.