Identification of phytocompounds from Houttuynia cordata Thunb. as potential inhibitors for SARS-CoV-2 replication proteins through GC-MS/LC-MS characterization, molecular docking and molecular dynamics simulation.

The COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a massive viral disease outbreak of international concerns. The present study is mainly intended to identify the bioactive phytocompounds from traditional antiviral herb Houttuynia cordata Thunb. as potential inhibitors for three main replication proteins of SARS-CoV-2, namely Main protease (Mpro), Papain-Like protease (PLpro) and ADP ribose phosphatase (ADRP) which control the replication process. A total of 177 phytocompounds were characterized from H. cordata using GC-MS/LC-MS and they were docked against three SARS-CoV-2 proteins (receptors), namely Mpro, PLpro and ADRP using Epic, LigPrep and Glide module of Schrödinger suite 2020-3. During docking studies, phytocompounds (ligand) 6-Hydroxyondansetron (A104) have demonstrated strong binding affinity toward receptors Mpro (PDB ID 6LU7) and PLpro (PDB ID 7JRN) with G-score of - 7.274 and - 5.672, respectively, while Quercitrin (A166) also showed strong binding affinity toward ADRP (PDB ID 6W02) with G-score -6.788. Molecular Dynamics Simulation (MDS) performed using Desmond module of Schrödinger suite 2020-3 has demonstrated better stability in the ligand-receptor complexes A104-6LU7 and A166-6W02 within 100 ns than the A104-7JRN complex. The ADME-Tox study performed using SwissADMEserver for pharmacokinetics of the selected phytocompounds 6-Hydroxyondansetron (A104) and Quercitrin (A166) demonstrated that 6-Hydroxyondansetron passes all the required drug discovery rules which can potentially inhibit Mpro and PLpro of SARS-CoV-2 without causing toxicity while Quercitrin demonstrated less drug-like properties but also demonstrated as potential inhibitor for ADRP. Present findings confer opportunities for 6-Hydroxyondansetron and Quercitrin to be developed as new therapeutic drug against COVID-19.

Identification of tyrosine kinase inhibitors from Panax bipinnatifidus and Panax pseudoginseng for RTK-HER2 and VEGFR2 receptors, by in silico approach.

Breast and stomach cancer is reported as a leading cause for human mortality across the world. The overexpression of receptor tyrosine kinase (RTK) proteins, namely the human epidermal growth factor receptor2 (HER2) and the vascular endothelial growth factor receptor2 (VEGFR2), is reported to be responsible for development and metastasis of breast and stomach cancer. Although several synthetic tyrosine kinase inhibitors (TKIs) as drug candidates targeting RTK-HER2 and VEGFR2 are currently available in the market, these are expensive with the reported side effects. This confers an opportunity for development of alternative novel tyrosine kinase inhibitors (TKIs) for RTK-HER2 and VEGFR2 receptors from the botanical sources. In the present study, we characterized 47 bioactive phytocompounds from the methanol extracts of the rhizomes of Asiatic traditional medicinal herbs-Panax bipinnatifidus and Panax pseudoginseng, of Indian Himalayan landraces using HPLC, GC-MS and high-sensitivity LC-MS tools. We performed molecular docking and molecular dynamics simulation analysis using Schrödinger suite 2020-3 to confirm the TKI phytocompounds showing the best binding affinity towards RTK-HER2 and VEGFR2 receptors. The results of molecular docking studies confirmed that the phytocompound (ligand) luteolin 7-O-glucoside (IHP15) showed the highest binding affinity towards receptor HER2 (PDB ID: 3PP0) with docking score and Glide g score (G-Score) of - 13.272, while chlorogenic acid (IHP12) showed the highest binding affinity towards receptor VEGFR2 (PDB ID: 4AGC) with docking score and Glide g score (G-Score) of - 10.673. Molecular dynamics (MD) simulation analysis carried out for 100 ns has confirmed strong binding interaction between the ligand and receptor complex [luteolin 7-O-glucoside (IHP15) and HER2 (PDB ID: 3PP0)] and is found to be stabilized within 40 to 100 ns of MD simulation, whereas ligand-receptor complex [chlorogenic acid (IPH12) and VEGFR2 (PDB ID: 4AGC)] also showed strong binding interaction and is found to be stabilized within 18-30 ns but slightly deviated during 100 ns of MD simulation. In silico ADME-Tox study using SwissADME revealed that the ligands luteolin 7-O-glucoside (IHP15) and chlorogenic acid (IHP12) have passed majority parameters of the common drug discovery rules. The present study has confirmed luteolin 7-O-glucoside (IHP15) and chlorogenic acid (IHP12) as potential tyrosine kinase inhibitors (TKIs) which were found to inhibit RTKs-HER2 and VEGFR2 receptor proteins, and thus paving the way for development of alternative potential TKIs (drug molecules) for treatment of HER2- and VEGFR2-positive breast and stomach cancer.

Phytochemical Fingerprints and Bioactivities of Ripe Disseminules (Fruit-Seeds) of Seventeen Gundelia (Kenger-Kereng Dikeni) Species from Anatolia with Chemometric Approach.

Gundelia species are known as "Kenger-kereng dikeni" in Anatolia, and their aerial parts are consumed as food. Also, roots and seeds (disseminules) of the Gundelia species are used to prepare gum and coffee. The chemical contents of ethanol and hexane extracts of disseminules of 17 Gundelia species, 13 of them are endemic, were studied using LC/MS/MS and GC/MS. Additionally, their antioxidant potential and enzyme inhibitory capacity against acetyl- and butyryl-cholinesterase, urease, and tyrosinase were determined. The unsaturated fatty acid ratios of Gundelia species were higher than their saturated fatty acid ratio. The highest sum of oleic and linoleic acid was detected in G. tournefortii var. tenuisecta (70.42 %). ß-Sitosterol, α-amyrin, 3-acetyllupeol were identified in 17 Gundelia species by GC/MS, while chlorogenic acid and luteolin by LC/MS/MS as major compounds. The ethanol and hexane extracts of G. siirtica, G. rosea, and G. mesopotamica indicated good cholinesterase inhibitory activity. Among all species, ethanol extract of G. colemerikensis exhibited the best activity in ABTS (IC50 : 32.30±0.98 µg/mL), DPPH (IC50 : 59.91±0.89 µg/mL), and CUPRAC (A0.5 : 57.41±1.03 µg/mL) assays. Ethanol extract of G. colemerikensis also displayed the highest inhibitory activity against butyrylcholinesterase (51.14±0.25 % at 200 µg/mL), urease (51.71±1.75 % at 200 µg/mL), and tyrosinase (39.50±0.85 % at 200 µg/mL) enzymes. According to the chemometric analysis of fatty acids, four groups were observed. Therefore, it is suggested that G. colemerikensis can be used in the pharmaceutical, food, and cosmetic industries due to its antioxidant and enzyme inhibition properties.

Non-Targeted Metabolomics Reveals Sorghum Rhizosphere-Associated Exudates are Influenced by the Belowground Interaction of Substrate and Sorghum Genotype.

Root exudation is an important plant process by which roots release small molecules into the rhizosphere that serve in overall plant functioning. Yet, there is a major gap in our knowledge in translating plant root exudation in artificial systems (i.e., hydroponics, sterile media) to crops, specifically for soils expected in field conditions. Sorghum (Sorghum bicolor L. Moench) root exudation was determined using both ultra-performance liquid chromatography and gas chromatography mass spectrometry-based non-targeted metabolomics to evaluate variation in exudate composition of two sorghum genotypes among three substrates (sand, clay, and soil). Above and belowground plant traits were measured to determine the interaction between sorghum genotype and belowground substrate. Plant growth and quantitative exudate composition were found to vary largely by substrate. Two types of changes to rhizosphere metabolites were observed: rhizosphere-enhanced metabolites (REMs) and rhizosphere-abated metabolites (RAMs). More REMs and RAMs were detected in sand and clay substrates compared to the soil substrate. This study demonstrates that belowground substrate influences the root exudate profile in sorghum, and that two sorghum genotypes exuded metabolites at different magnitudes. However, metabolite identification remains a major bottleneck in non-targeted metabolite profiling of the rhizosphere.

Metabolomics technology and bioinformatics for precision medicine.

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

Urinary and Plasma Metabolomics Identify the Distinct Metabolic Profile of Disease State in Chronic Mouse Model of Multiple Sclerosis.

Identification of non-invasive biomarkers of disease progression in multiple sclerosis (MS) is critically needed for monitoring the disease progression and for effective therapeutic interventions. Urine is an attractive source for non-invasive biomarkers because it is easily obtained in the clinic. In search of a urine metabolite signature of progression in chronic experimental autoimmune encephalomyelitis (EAE), we profiled urine at the chronic stage of the disease (day 45 post immunization) by global untargeted metabolomics. Using a combination of high-throughput liquid-and-gas chromatography with mass spectrometry, we found 105 metabolites (P < 0.05) significantly altered at the chronic stage, indicating a robust alteration in the urine metabolite profile during disease. Assessment of altered metabolites against the Kyoto Encyclopedia of Genes and Genomes revealed distinct non-overlapping metabolic pathways and revealed phenylalanine-tyrosine and associated metabolism being the most impacted. Combined with previously performed plasma profiling, eight common metabolites were significantly altered in both of the biofluids. Metaboanalyst analysis of these common metabolites revealed that phenylalanine metabolism and Valine, leucine, and isoleucine biosynthetic pathways are central metabolic pathways in both bio-fluids and could be analyzed further, either for the discovery of therapeutics or biomarker development. Overall, our study suggests that urine and plasma metabolomics may contribute to the identification of a distinct metabolic fingerprint of EAE disease discriminating from the healthy control which may aid in the development of an objective non-invasive monitoring method for progressive autoimmune diseases like MS. Graphical Abstract Untargeted urinary metabolomics of a chronic mouse model of multiple sclerosis identified Phenylalanine, tyrosine & tryptophan metabolism as the significantly altered metabolic pathway. Eight common metabolites were identified when we combined urinary and plasma metabolic signature, which revealed a perturbation of Phenylalanine metabolism and valine, leucine & isoleucine metabolic pathways, involved in CNS dysfunction during diseases. The identified eight metabolic signature of urine and plasma may be of clinical relevance as potential biomarkers and guide towards the identification of specific metabolic pathways as novel drug targets.