GC-MS- and NMR-Based Metabolomics and Molecular Docking Reveal the Potential Alpha-Glucosidase Inhibitors from Psychotria malayana Jack Leaves

Investigation of alpha-glucosidase inhibition activity of Artabotrys sumatranus leaf extract using metabolomics, machine learning and molecular docking analysis

One way to treat diabetes mellitus type II is by using α-glucosidase inhibitor, that will slow down the postprandial glucose intake. Metabolomics analysis of Artabotrys sumatranus leaf extract was used in this research to predict the active compounds as α-glucosidase inhibitors from this extract. Both multivariate statistical analysis and machine learning approaches were used to improve the confidence of the predictions. After performance comparisons with other machine learning methods, random forest was chosen to make predictive model for the activity of the extract samples. Feature importance analysis (using random feature permutation and Shapley score calculation) was used to identify the predicted active compound as the important features that influenced the activity prediction of the extract samples. The combined analysis of multivariate statistical analysis and machine learning predicted 9 active compounds, where 6 of them were identified as mangiferin, neomangiferin, norisocorydine, apigenin-7-O-galactopyranoside, lirioferine, and 15,16-dihydrotanshinone I. The activities of norisocorydine, apigenin-7-O-galactopyranoside, and lirioferine as α-glucosidase inhibitors have not yet reported before. Molecular docking simulation, both to 3A4A (α-glucosidase enzyme from Saccharomyces cerevisiae, usually used in bioassay test) and 3TOP (a part of α-glucosidase enzyme in human gut) showed strong to very strong binding of the identified predicted active compounds to both receptors, with exception of neomangiferin which only showed strong binding to 3TOP receptor. Isolation based on bioassay guided fractionation further verified the metabolomics prediction by succeeding to isolate mangiferin from the extract, which showed strong α-glucosidase activity when subjected to bioassay test. The correlation analysis also showed a possibility of 3 groups in the predicted active compounds, which might be related to the biosynthesis pathway (need further research for verification). Another result from correlation analysis was that in general the α-glucosidase inhibition activity in the extract had strong correlation to antioxidant activity, which was also reflected in the predicted active compounds. Only one predicted compound had very low positive correlation to antioxidant activity.

Cloning, expression, and characterization of a heparinase III coupled with heparinase I for enzymatic depolymerization of heparin

A heparinase III (NsHep-III) from Niabella sp. was identified, cloned, and expressed as soluble form in E. coli BL21 (DE3). With heparin as substrate, the maximum activity of NsHep-III of 90.0 U·mg- 1 was achieved at pH 7.1 Tris-HCl (containing 15 mM Mg2+) and 30oC. The half-life of NsHep-III was determined to be 5 h at 30oC. The interactions between NsHep-III and substrates were studied by molecular docking. The combination of NsHep-III and a heparinase I from Bacteroides eggthii (BeHep-I) was employed to cleave heparin. Analysis of the enzymatic products of NsHep-III by SAX-HPLC showed seven different modified disaccharides, indicating that NsHep-III has a wide range of substrate specificity. The results of GPC analysis demonstrated that the average molecular weight of the product of heparin cleavage by the combination of NsHep-III/BeHep-I was reduced to 3969 Da, which accounted for 90% of all the components, and complied with the requirements of the European Pharmacopoeia. NsHep-III has notable activity and efficiency in cleaving heparin, which is potentially useful for the industrial production of low molecular weight heparin.

New α-glucosidase inhibitors and antioxidants in optimized Psychotria malayana Jack leaves extract identified by gC-MS-based metabolomics and in silico molecular docking

Our earlier research demonstrated α-glucosidase inhibitory (AGI) and antioxidant activities of the optimised extract of Psychotria malayana leaves. It was reported having numerous compounds, although it was unclear which compounds exhibit the bioactivities as well as their binding interaction to the enzyme. This study aimed to identify the compounds possessing AGI and antioxidant activities in the extract utilising GC-MS-based metabolomics, and to analyse the ligand-enzyme binding interactions via in-silico molecular docking. A partial least square was employed to correlate the metabolite profile and bioactivities. The loading plot reveals the bioactive compounds in this extract. The AGI activity of 1-cyclohexene-1-carboxylic, propanoic, butanedioic and D-gluconic acid together with the antioxidant activity of some compounds were reported for the first time through this study. The docking study reveals that all compounds, except for 1-cyclohexene-1-carboxylic acid, exhibit binding to the enzyme's catalytic site. This discovery demonstrates the potential of this plant for diabetes therapy.

An Integrated Metabolomics Study on Antidiabetic Activity of Christia vespertilionis Leaves Extract Using Chemometric and Molecular Docking Analysis

In disease treatment, the utilisation of medicinal plants has witnessed a discernible rise, driven by concerns over the adverse effects associated with synthetic drugs available in the market. Analyses of the plant Christia vespertilionis (L.f.) Bakh. F., indigenous to Malaysia, has suggested its antidiabetic property linked to α-glucosidase inhibition, but metabolites responsible for antidiabetic are unexplored. The metabolomics approaches and molecular docking simulations were integrated to identify the putative α-glucosidase inhibitors and their enzyme interaction. In this study, the crude leaves extracted from this plant were extracted using solvents of varying polarity, followed by gas and liquid chromatography coupled with mass spectrometry metabolomics. The highest inhibition activity in a mixture of n-hexane and ethyl acetate (1:1, v/v)) was observed. Six putative metabolites corresponding to antidiabetic activity were identified: palmitic acid (2), linolenic acid (4), 7-tetradecenal (5), aloeemodin-8-monoglucoside (14), bruceine I (15), and sanjidin B (16). The mechanism of action of all the identified compounds is competitive, mainly involving hydrophobic and hydrogen bonding interactions with the protein residues. Compounds 14, 15, and 16 exhibited strong binding capabilities with both enzyme crystal structures compared to the positive control, quercetin. The metabolites extracted from C. vespertilionis leaves have demonstrated promising antidiabetic effects. These antidiabetic compounds can potentially commercialise new drug candidates in managing diabetes conditions.

Integrated skin metabolomics and network pharmacology to explore the mechanisms of Goupi Plaster for treating knee osteoarthritis

Background and aim

Goupi Plaster (GP) is topical traditional Chinese medicine preparation. It has been used to treat Knee Osteoarthritis (KOA) in clinical practice of traditional Chinese medicine (TCM). However, the mechanisms of GP relieve KOA are poorly understood.

Experimental procedure

Rabbit models of KOA were established and treated with GP. Knee cartilage pathology was analyzed using hematoxylin and eosin staining, while plasma levels of inflammatory factors (interleukin (IL)-4, IL-6, and IL-17) and skin neurotransmitters (calcitonin gene-related peptide (CGRP), substance P (SP), and5-hydroxytryptamine (5-HT)) were measured by enzyme linked immunosorbent assay. Metabolomics based on GC-TOF-MS analysis screened for skin biomarkers as well as relevant pathways. Network pharmacology screened for relevant skin targets as well as relevant pathways, and finally, MetScape software was utilized to integrate the results of metabolomics and network pharmacology to screen for key skin targets, key metabolites, and key pathways for GP treatment of KOA.

Results and conclusion

GP administration substantially repaired cartilage surface breaks in KOA and led to relatively intact cartilage structure and normal cell morphology. GP decreased plasma levels of IL-6 and IL-17 and skin levels of CGRP, SP and 5-HT while increased plasma IL-4. GP administration normalized the levels of 15 metabolites which were changed in KOA. Network pharmacology analysis identified 181 targets. Finally, 3 key targets, 5 key metabolites and 3 related pathways were identified, which suggested that GP improved skin barrier function and skin permeability by regulating skin lipid metabolism. GP treatment also regulated skin amino acid levels and subsequently affected neurotransmitters and signaling molecules. In addition, the purinergic signaling pathway was also involved in the treatment of GP against KOA.In conclusion, GP treatment is associated with changes in skin lipid metabolism, neurotransmitters, and the purinergic signaling pathway.

Synthesis,Antidiabetic and Antitubercular Evaluation of Quinoline-pyrazolopyrimidine hybrids and Quinoline-4-Arylamines

Two libraries of quinoline-based hybrids 1-(7-chloroquinolin-4-yl)-1H-pyrazolo[3,4-d]pyrimidin-4-amine and 7-chloro-N-phenylquinolin-4-amine were synthesized and evaluated for their α-glucosidase inhibitory and antioxidant properties. Compounds with 4-methylpiperidine and para-trifluoromethoxy groups, respectively, showed the most promising α-glucosidase inhibition activity with IC50=46.70 and 40.84 μM, compared to the reference inhibitor, acarbose (IC50=51.73 μM). Structure-activity relationship analysis suggested that the cyclic secondary amine pendants and para-phenyl substituents account for the variable enzyme inhibition. Antioxidant profiling further revealed that compounds with an N-methylpiperazine and N-ethylpiperazine ring, respectively, have good DPPH scavenging abilities with IC50=0.18, 0.58 and 0.93 mM, as compared to ascorbic acid (IC50=0.05 mM), while the best DPPH scavenger is NO2-substituted compound (IC50=0.08 mM). Also, compound with N-(2-hydroxyethyl)piperazine moiety emerged as the best NO radical scavenger with IC50=0.28 mM. Molecular docking studies showed that the present compounds are orthosteric inhibitors with their quinoline, pyrimidine, and 4-amino units as crucial pharmacophores furnishing α-glucosidase binding at the catalytic site. Taken together, these compounds exhibit dual potentials; i. e., potent α-glucosidase inhibitors and excellent free radical scavengers. Hence, they may serve as structural templates in the search for agents to manage Type 2 diabetes mellitus. Finally, in preliminary assays investigating the anti-tubercular potential of these compounds, two pyrazolopyrimidine series compounds and a 7-chloro-N-phenylquinolin-4-amine hybrid showed sub-10 μM whole-cell activities against Mycobacterium tuberculosis.

Compound-Specific 1D 1H NMR Pulse Sequence Selection for Metabolomics Analyses

NMR-based metabolomics approaches have been used in a wide range of applications, for example, with medical, plant, and marine samples. One-dimensional (1D) ¹H NMR is routinely used to find out biomarkers in biofluids such as urine, blood plasma, and serum. To mimic biological conditions, most NMR studies have been carried out in an aqueous solution where the high intensity of the water peak is a major problem in obtaining a meaningful spectrum. Different methods have been used to suppress the water signal, including 1D Carr-Purcell-Meiboom-Gill (CPMG) presat, consisting of a T₂ filter to suppress macromolecule signals and reduce the humped curve in the spectrum. 1D nuclear Overhauser enhancement spectroscopy (NOESY) is another method for water suppression that is used routinely in plant samples with fewer macromolecules than in biofluid samples. Other common 1D ¹H NMR methods such as 1D ¹H presat and 1D ¹H ES have simple pulse sequences; their acquisition parameters can be set easily. The proton with presat has just one pulse and the presat block causes water suppression, while other 1D ¹H NMR methods including those mentioned above have more pulses. However, it is not well known in metabolomics studies because it is used only occasionally and in a few types of samples by metabolomics experts. Another effective method is excitation sculpting to suppress water. Herein, we evaluate the effect of method selection on signal intensities of commonly detected metabolites. Different classes of samples including biofluid, plant, and marine samples were investigated, and recommendations on the advantages and limitations of each method are presented.

Metabolomics and Network Pharmacology in the Exploration of the Multi-Targeted Therapeutic Approach of Traditional Medicinal Plants

Metabolomic is generally characterized as a comprehensive and the most copious analytical technique for the identification of targeted and untargeted metabolite diversity in a biological system. Recently, it has exponentially been used for phytochemical analysis and variability among plant metabolites, followed by chemometric analysis. Network pharmacology analysis is a computational technique used for the determination of multi-mechanistic and therapeutic evaluation of chemicals via interaction with the genomes involved in targeted or untargeted diseases. In considering the facts, the present review aims to explore the role of metabolomics and network pharmacology in the scientific validation of therapeutic claims as well as to evaluate the multi-targeted therapeutic approach of traditional Indian medicinal plants. The data was collected from different electronic scientific databases such as Google Scholar, Science Direct, ACS publication, PubMed, Springer, etc., using different keywords such as metabolomics, techniques used in metabolomics, chemometric analysis, a bioinformatic tool for drug discovery and development, network pharmacology, methodology and its role in biological evaluation of chemicals, etc. The screened articles were gathered and evaluated by different experts for their exclusion and inclusion in the final draft of the manuscript. The review findings suggest that metabolomics is one of the recent most precious and effective techniques for metabolite identification in the plant matrix. Various chemometric techniques are copiously used for metabolites discrimination analysis hence validating the unique characteristic of herbal medicines and their derived products concerning their authenticity. Network pharmacology remains the only option for the unique and effective analysis of hundreds of chemicals or metabolites via genomic interaction and thus validating the multi-mechanistic and therapeutic approach to explore the pharmacological aspects of herbal medicines for the management of the disease.

Preliminary Phytochemical Screening, In Vitro Antidiabetic, Antioxidant Activities, and Toxicity of Leaf Extracts of Psychotria malayana Jack

Psychotria malayana Jack belongs to the Rubiacea and is widespread in Southeast Asian countries. It is traditionally used to treat diabetes. Despite its potential medicinal use, scientific proof of this pharmacological action and the toxic effect of this plant are still lacking. Hence, this study aimed to investigate the in vitro antidiabetic and antioxidant activities, toxicity, and preliminary phytochemical screening of P. malayana leaf extracts by gas chromatography-mass spectrometry (GC-MS) after derivatization. The antidiabetic activities of different extracts of this plant were investigated through alpha-glucosidase inhibitory (AGI) and 2-NBDG glucose uptake using 3T3-L1 cell line assays, while the antioxidant activity was evaluated using DPPH and FRAP assays. Its toxicological effect was investigated using the zebrafish embryo/larvae (Danio rerio) model. The mortality, hatchability, tail-detachment, yolk size, eye size, beat per minute (BPM), and body length were taken into account to observe the teratogenicity in all zebrafish embryos exposed to methanol extract. The LC50 was determined using probit analysis. The methanol extract showed the AGI activity (IC50 = 2.71 ± 0.11 μg/mL), insulin-sensitizing activity (at a concentration of 5 µg/mL), and potent antioxidant activities (IC50 = 10.85 μg/mL and 72.53 mg AAE/g for DPPH and FRAP activity, respectively). Similarly, the water extract exhibited AGI activity (IC50 = 6.75 μg/mL), insulin-sensitizing activity at the concentration of 10 μg/mL, and antioxidant activities (IC50 = 27.12 and 33.71 μg/mL for DPPH and FRAP activity, respectively). The methanol and water extracts exhibited the LC50 value higher than their therapeutic concentration, i.e., 37.50 and 252.45 µg/mL, respectively. These results indicate that both water and methanol extracts are safe and potentially an antidiabetic agent, but the former is preferable since its therapeutic index (LC50/therapeutic concentration) is much higher than for methanol extracts. Analysis using GC-MS on derivatized methanol and water extracts of P. malayana leaves detected partial information on some constituents including palmitic acid, 1,3,5-benzenetriol, 1-monopalmitin, beta-tocopherol, 24-epicampesterol, alpha-tocopherol, and stigmast-5-ene, that could be a potential target to further investigate the antidiabetic properties of the plant. Nevertheless, isolation and identification of the bioactive compounds are required to confirm their antidiabetic activity and toxicity.