Untargeted metabolomics using UHPLC-Q-Orbitrap HRMS for identifying cytotoxic compounds on MCF-7 breast cancer cells from Annona muricata Linn leaf extracts as potential anticancer agents.

INTRODUCTION: The leaves of Annona muricata L., known as "soursop" or "sirsak" in Indonesia, are used traditionally for cancer treatment. However, the bioactive components remain largely unidentified. OBJECTIVE: This study used untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics to identify potential cytotoxic compounds in A. muricata leaf extracts on MCF-7 breast cancer cells in vitro. METHODS: A. muricata leaves were macerated with water, 99% ethanol, and aqueous mixtures containing 30%, 50%, and 80% ethanol. Cytotoxic activity of the extracts against MCF-7 breast cancer cells was determined using the MTT assay. Ultra-high-performance liquid chromatography-Q-Orbitrap high-resolution mass spectroscopy (UHPLC-Q-Orbitrap-HRMS) was used to characterize the metabolite composition of each extract. The correlations between metabolite profile and cytotoxic activities were evaluated using orthogonal partial least square discriminant analysis (OPLS-DA). The binding of these bioactive compounds to the tumorigenic alpha-estrogen receptor (3ERT) was then evaluated by in silico docking simulations. RESULTS: Ninety-nine percent ethanol extracts demonstrated the greatest potency for reducing MCF-7 cell viability (IC50 = 22 µg/ml). We detected 35 metabolites in ethanol extracts, including alkaloids, flavonoids, and acetogenins. OPLS-DA predicted that annoreticuin, squadiolin C, and xylopine, and six unknown acetogenin metabolites, might reduce MCF-7 cell viability. In silico analysis predicted that annoreticuin, squadiolin C, and xylopine bind to 3ERT with an affinity comparable to doxorubicin. CONCLUSION: Untargeted metabolomics and in silico modeling identified cytotoxic compounds on MCF-7 cells and binding affinity to 3ERT in A. muricata leaf extracts. The findings need to be further verified to prove the screening results.

Antioxidant Activity and Metabolite Profiling of Xylocarpus granatum Extracts Using Gas Chromatography-Mass Spectrometry.

The potential application of Xylocarpus granatum, a mangrove species, as traditional medicine has been widely linked to its high secondary metabolite and antioxidant contents. However, few studies have been reported to identify and classify active metabolites responsible for such excellent biological activities. Therefore, the aim of this work was to determine the antioxidant activity, identify the metabolite profiles, and predict the metabolites acting as antioxidants in X. granatum extract using a gas chromatography-mass spectrometry (GC-MS)-based metabolomics approach. The seeds, stems, fruit peel, pulp, leaves, and twigs of X. granatum were macerated with ethanol. Each extract was analyzed with GC-MS, and the data were processed using mass spectrometry data-independent analysis (MS-DIAL) software to identify the metabolites. The IC50 value of plant parts of X. granatum ranged from 7.73 to 295 ppm. A total of 153 metabolites were identified and confirmed in the X. granatum extracts. Among the identified metabolites, epicatechin and epigallocatechin were the two most abundant in the stem extracts and are expected to have the greatest potential as antioxidants. Principal component analysis (PCA) succeeded in grouping all parts of the plant into three groups based on the composition of the metabolites: group 1 (stems, fruit peel, and twigs), group 2 (seeds and pulp), and group 3 (leaves).

Indonesian Mangrove Sonneratia caseolaris Leaves Ethanol Extract Is a Potential Super Antioxidant and Anti Methicillin-Resistant Staphylococcus aureus Drug.

Methicillin-resistant Staphylococcus aureus (MRSA) is an S. aureus strain that has developed resistance against ß-lactam antibiotics, resulting in a scarcity of a potent cure for treating Staphylococcus infections. In this study, the anti-MRSA and antioxidant activity of the Indonesian mangrove species Sonneratia caseolaris, Avicennia marina, Rhizophora mucronata, and Rhizophora apiculata were studied. Disk diffusion, DPPH, a brine shrimp lethality test, and total phenolic and flavonoid assays were conducted. Results showed that among the tested mangroves, ethanol solvent-based S. caseolaris leaves extract had the highest antioxidant and anti-MRSA activities. An antioxidant activity assay showed comparable activity when compared to ascorbic acid, with an IC50 value of 4.2499 ± 3.0506 ppm and 5.2456 ± 0.5937 ppm, respectively, classifying the extract as a super-antioxidant. Moreover, S. caseolaris leaves extract showed the highest content of strongly associated antioxidative and antibacterial polyphenols, with 12.4% consisting of nontoxic flavonoids with the minimum inhibitory concentration of the ethanol-based S. caseolaris leaves extract being approximately 5000 ppm. LC-MS/MS results showed that phenolic compounds such as azelaic acid and aspirin were found, as well as flavonoid glucosides such as isovitexin and quercitrin. This strongly suggested that these compounds greatly contributed to antibacterial and antioxidant activity. Further research is needed to elucidate the interaction of the main compounds in S. caseolaris leaves extract in order to confirm their potential either as single or two or more compounds that synergistically function as a nontoxic antioxidant and antibacterial against MRSA.

Selective non-enzymatic uric acid sensing in the presence of dopamine: electropolymerized poly-pyrrole modified with a reduced graphene oxide/PEDOT:PSS composite.

A highly selective electrochemical sensor based on a molecularly imprinted polymer (MIP) to be developed for uric acid detection in the presence of dopamine as an interference molecule was demonstrated in this study. This non-enzymatic uric acid sensor was developed by electropolymerizing poly-pyrrole onto a composite of electrochemically reduced graphene oxide (ErGO) and poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) on a glassy carbon electrode (GCE) to give MIP/ErGO/PEDOT:PSS electrodes. The structural properties, surface morphology, and electrochemical interface of this fabricated uric acid sensor was then characterized using infrared spectroscopy, scanning electron microscopy, atomic force microscopy, and electrochemical impedance spectroscopy. This fabricated non-enzymatic electrochemical sensor (MIP/ErGO/PEDOT:PSS modified GCE) also showed excellent analytical performance at the optimum ratio of monomer/template concentration and optimized electropolymerization conditions, for example in the low concentration range of 0.1-100 µM with a detection limit of 0.05 µM towards uric acid detection in the presence of dopamine. Furthermore, this fabricated uric acid sensor also exhibited good reproducibility and stability for uric acid measurements in the presence of dopamine for 5 consecutive days. In addition, this sensor demonstrates highly selective detection of uric acid in the presence of several interfering species such as dopamine, urea, glucose, magnesium ions, and ascorbic acid. This fabricated uric acid sensor ultimately showed satisfactory uric acid measurement in samples of human urine and is expected to be used in early-stage disease diagnosis.

Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.

Jamu is an Indonesian traditional herbal medicine that has been practiced for generations. Jamu is made from various medicinal plants. Each plant has several compounds directly related to the target protein that are directly associated with a disease. A pharmacological graph can form relationships between plants, compounds, and target proteins. Research related to the prediction of Jamu formulas for some diseases has been carried out, but there are problems in finding combinations or compositions of Jamu formulas because of the increase in search space size. Some studies adopted the drug-target interaction (DTI) implemented using machine learning or deep learning to predict the DTI for discovering the Jamu formula. However, this approach raises important issues, such as imbalanced and high-dimensional dataset, overfitting, and the need for more procedures to trace compounds to their plants. This study proposes an alternative approach by implementing bipartite graph search optimization using the branch and bound algorithm to discover the combination or composition of Jamu formulas by optimizing the search on a plant-protein bipartite graph. The branch and bound technique is implemented using the search strategy of breadth first search (BrFS), Depth First Search, and Best First Search. To show the performance of the proposed method, we compared our method with a complete search algorithm, searching all nodes in the tree without pruning. In this study, we specialize in applying the proposed method to search for the Jamu formula for type II diabetes mellitus (T2DM). The result shows that the bipartite graph search with the branch and bound algorithm reduces computation time up to 40 times faster than the complete search strategy to search for a composition of plants. The binary branching strategy is the best choice, whereas the BrFS strategy is the best option in this research. In addition, the the proposed method can suggest the composition of one to four plants for the T2DM Jamu formula. For a combination of four plants, we obtain Angelica Sinensis, Citrus aurantium, Glycyrrhiza uralensis, and Mangifera indica. This approach is expected to be an alternative way to discover the Jamu formula more accurately.

A facile electrochemical sensor based on a composite of electrochemically reduced graphene oxide and a PEDOT:PSS modified glassy carbon electrode for uric acid detection.

A glassy carbon electrode modified with electrochemically reduced graphene oxide (ErGO) and poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) was developed for uric acid determination with dopamine as interference in artificial saliva. The electrochemical performance of the fabricated electrode was studied using both techniques of cyclic voltammetry (CV) and differential pulse voltammetry (DPV), under optimized conditions. Using DPV, the sensor based on ErGO/PEDOT:PSS modified GCE displayed a linear relationship in the concentration ranges of 10-100 µM for uric acid. This uric acid sensor exhibited a high sensitivity with detection limits of 1.08 µM and quantitation limit of 3.61 µM. This sensor also showed good reproducibility for uric acid detection in artificial saliva in 5 consecutive days of measurements. This device was successfully used to analyze uric acid in artificial saliva as well as in a human saliva sample using the standard addition method.

Metabolite profiling of Andrographis paniculata leaves and stem extract using UHPLC-Orbitrap-MS/MS.

Andrographis paniculata is known as the king of bitter and it has been widely used as a medicinal plant. The properties of A. paniculata are generally determined by the metabolite composition, which may be influenced by several factors, one of which is the part of the plant extracted. The objectives of this research are to identify putatively the metabolite composition of the stem and the leaves extracts using LC-MS/MS and classify them using PCA. The stem and the leaves samples were separated and extracted using sonication with 70% ethanol. A total of 31 metabolite compounds has been putatively identified. All compounds were identified in the stem and the leaves extracts, which only differed in their intensity. These metabolite compounds were divided into diterpene lactones, flavonoids, and phenolic acid groups. By using the peak intensities of the 18 compounds identified, the leaves and stem extracts were grouped using PCA.

Xanthine Oxidase-Induced Inflammatory Responses in Respiratory Epithelial Cells: A Review in Immunopathology of COVID-19.

Xanthine oxidase (XO) is an enzyme that catalyzes the production of uric acid and superoxide radicals from purine bases: hypoxanthine and xanthine and is also expressed in respiratory epithelial cells. Uric acid, which is also considered a danger associated molecule pattern (DAMP), could trigger a series of inflammatory responses by activating the inflammasome complex path and NF-κB within the endothelial cells and by inducing proinflammatory cytokine release. Concurrently, XO also converts the superoxide radicals into hydroxyl radicals that further induce inflammatory responses. These conditions will ultimately sum up a hyperinflammation condition commonly dubbed as cytokine storm syndrome (CSS). The expression of proinflammatory cytokines and neutrophil chemokines may be reduced by XO inhibitor, as observed in human respiratory syncytial virus (HRSV)-infected A549 cells. Our review emphasizes that XO may have an essential role as an anti-inflammation therapy for respiratory viral infection, including coronavirus disease 2019 (COVID-19).

HPLC fingerprint and simultaneous quantitative analysis of phyllanthin and hypophyllanthin for identification and authentication of Phyllanthus niruri from related species

Abstract A precise and accurate method for the identification and authentication of Phyllanthus niruri L. from P. debilis Klein ex Willd. and P. urinaria L., Phyllanthaceae, was developed using high-performance liquid chromatography. Chromatographic fingerprint analysis was combined with simultaneous quantification of phyllanthin and hypophyllanthin for the developed method. Phyllanthin and hypophyllanthin were successfully separated and quantified under this proposed method. The highest amount of phyllanthin and hypophyllanthin was found in P. niruri compared to P. debilis and P. urinaria. Fingerprint chromatogram of the three Phyllanthus species showed distinct profiles that these may be used to identify and authenticate each Phyllanthus species, which improved by marker compounds present in each species. The combination of chromatographic fingerprint analysis and discriminant analysis was successfully discriminated all three species, including P. niruri adulterated with P. debilis or P. urinaria. The method can be used for the identification and authentication of P. niruri from related species, such as P. debilis and P. urinaria.

Melanogenesis inhibitory activity of components from Salam leaf (Syzygium polyanthum) extract.

In order to identify a novel whitening agent, the methanol extract of S. polyanthum leaf was focused on by the screening test using nine Indonesian medicinal plants for the inhibition of melanogenesis and tyrosinase activity in B16 melanoma cells. Three novel compounds [(1) 1-(2,3,5-trihydroxy-4-methylphenyl)hexane-1-one, (2) 1-(2,3,5-trihydroxy methylphenyl)octane-1-one, and (3) (4E)-1-(2,3,5-trihydroxy-4-methylphenyl)decan-1-one and one known compound [(4) 1-(2,3,5-trihydroxy-4-methylphenyl)decan-1-one were isolated from the methanol extract. Our study demonstrated that S. polyanthum leaf methanol extract at 25-200 µg/mL decreased extracellular melanin formation ca. 20-80%, with high cell viability. Compounds 1-4 were found to be active in melanogenesis and tyrosinase inhibition. Compound 3 was the most active against tyrosinase activity (83.98 µM), particularly when L-tyrosine was the substrate. Compounds 1-4 significantly diminished extracellular melanin formation in B16 melanoma cells (> 80%), with high cell viability. Thus, our study suggested that compounds 1-4 isolated from the methanol extract of S. polyanthum leaf play important roles in decreasing extracellular melanogenesis and inhibiting tyrosinase.

Fourier transform infrared spectroscopy combined with chemometrics for discrimination of Curcuma longa, Curcuma xanthorrhiza and Zingiber cassumunar.

Turmeric (Curcuma longa), java turmeric (Curcuma xanthorrhiza) and cassumunar ginger (Zingiber cassumunar) are widely used in traditional Indonesian medicines (jamu). They have similar color for their rhizome and possess some similar uses, so it is possible to substitute one for the other. The identification and discrimination of these closely-related plants is a crucial task to ensure the quality of the raw materials. Therefore, an analytical method which is rapid, simple and accurate for discriminating these species using Fourier transform infrared spectroscopy (FTIR) combined with some chemometrics methods was developed. FTIR spectra were acquired in the mid-IR region (4000-400 cm(-1)). Standard normal variate, first and second order derivative spectra were compared for the spectral data. Principal component analysis (PCA) and canonical variate analysis (CVA) were used for the classification of the three species. Samples could be discriminated by visual analysis of the FTIR spectra by using their marker bands. Discrimination of the three species was also possible through the combination of the pre-processed FTIR spectra with PCA and CVA, in which CVA gave clearer discrimination. Subsequently, the developed method could be used for the identification and discrimination of the three closely-related plant species.