Synthesis, computational docking and molecular dynamics studies of a new class of spiroquinoxalinopyrrolidine embedded chromanone hybrids as potent anti-cholinesterase agents.

Novel structurally intriguing heterocycles embedded with spiropyrrolidine, quinoxaline and chromanone units were synthesized in good yields using a [Bmim]Br accelerated multicomponent reaction strategy. The key step of the reaction is 1,3-dipolar cycloaddition involving highly functionalized dipolarophile, viz. 3-benzylidenechroman-4-one, to afford spiroquinoxalinopyrrolidine embedded chromanone hybrid heterocycles. The formation of spiro products occurs via two C-C, two N-C and one C-N bonds possessing four adjoining stereogenic centers, two of which are spiro carbons. The newly synthesized spiro compounds showed potent acetylcholinesterase and butyrylcholinesterase inhibitory activities. Moreover, compounds with fluorine displayed the highest AChE (3.20 ± 0.16 µM) and BChE (18.14 ± 0.06 µM) inhibitory activities. Further, docking studies, followed by all-atom molecular dynamics, showed results that are consistent with in vitro experimental findings. Although docking scores for the synthesized derivatives were higher than those of the standard drug, MD MMPBSA results showed better binding of synthesized derivatives (-93.5 ± 11.9 kcal mol-1) compared to the standard drug galantamine (-66.2 ± 12.3 kcal mol-1) for AChE but exhibited similar values (-98.1 ± 11.2 and -97.9 ± 11.5 kcal mol-1) for BChE. These differences observed in drug binding with AChE/BChE are consistent with RMSD, RMSF, LIG plots, and FEL structural analysis. Taken together, these derivatives could be potential candidates as inhibitors of AChE and BChE.

In silico energetic and molecular dynamic simulations studies demonstrate potential effect of the point mutations with implications for protein engineering in BDNF.

Protein engineering by directed evolution is time-consuming. Hence, in silico techniques like FoldX-Yasara for ∆∆G calculation, and SNPeffect for predicting propensity for aggregation, amyloid formation, and chaperone binding are employed to design proteins. Here, we used in silico techniques to engineer BDNF-NTF3 interaction and validated it using mutations with known functional implications for NGF dimer. The structures of three mutants representing a positive, negative, or neutral ∆∆G involving two interface residues in BDNF and two mutations representing a neutral and positive ∆∆G in NGF, which is aligned with BDNF, were selected for molecular dynamics (MD) simulation. Our MD results conclude that the secondary structure of individual protomers of the positive and negative mutants displayed a similar or different conformation from the NTF3 monomer, respectively. The positive mutants showed fewer hydrophobic interactions and higher hydrogen bonds compared to the wild-type, negative, and neutral mutants with similar SASA, suggesting solvent-mediated disruption of hydrogen-bonded interactions. Similar results were obtained for mutations with known functional implications for NGF and BDNF. The results suggest that mutations with known effects in homologous proteins could help in validation, and in silico directed evolution experiments could be a viable alternative to the experimental technique used for protein engineering.

Activity against Mycobacterium tuberculosis of a new class of spirooxindolopyrrolidine embedded chromanone hybrid heterocycles.

A new class of structurally intriguing heterocycles embedded with spiropyrrolidine, oxindole and chromanones was prepared by regio- and stereoselectively in quantitative yields using an intermolecular tandem cycloaddition protocol. The compounds synthesized were assayed for their anti-mycobacterial activity against Mycobacterium tuberculosis (Mtb) H37Rv and isoniazid-resistant (katG and inhA promoter mutations) clinical Mtb isolates. Four compounds exhibited significant antimycobacterial activity against Mtb strains tested. In particular, a compound possessing a fluorine substituted derivative displayed potent activity at 0.39 µg mL-1 against H37Rv, while it showed 0.09 µg mL-1 and 0.19 µg mL-1 activity against inhA promoter and katG mutation isolates, respectively. A molecular docking study was conducted with the potent compound, which showed results that were consistent with the in vitro experiments.

Synthesis, topology, molecular docking and dynamics studies of o-phenylenediamine derivative.

The N, N'-(1,2-phenylene) bis (1- (4- chlorophenyl) methanimine) (CS4) was synthesized and characterized by infrared (IR), absorption (UV-vis) and NMR (1H and 13C) spectral analyses. The structural parameters, vibrational frequencies, potential energy and the distribution analysis (PED) were calculated by using DFT with the basis set of B3LYP/cc-pVDZ and these spectral values were compared to the experimental values. HOMO and LUMO studied were performed in order to understand the stability and biological activity of the compound. The most reactive sites on the compound were investigated by utilizing MEP energy surface and Fukui function descriptor with the natural population analysis (NPA) of the charges. The study of the natural bond orbitals (NBO) reveals the delocalization of the intramolecular interaction of the charges in the compound. Additionally, topological investigations (ELF, LOL), determination of thermodynamic parameters and noncovalent interaction (NCI) study by using topology (RDG) analysis were also carried out. Finally, the molecular docking and molecular dynamics simulations was carried out by examining against glycosylphosphatidylinositol phospholipase D inhibitor receptor for distinct protein targets (3MZG).Communicated by Ramaswamy H. Sarma.

Integrated Multi-Omics Analysis and Validation in Yeast Model of Amyotrophic Lateral Sclerosis.

Transcriptomics is a complex process that involves raw data extraction, normalization, differential gene expression, and analysis. The Gene Expression Omnibus (GEO) database at the National Center for Biotechnology Information (NCBI) is a repository of experimental datasets. Amyotrophic lateral sclerosis (ALS) datasets are deposited by various scientists and research investigators to expand the horizon of scientific knowledge. R-statistical tools are the most common ways for conducting these kinds of studies. The first step is the identification of appropriate datasets. Since the raw data is available in a variety of formats, a large array of software is used for extraction and analysis. Normalization is conducted for the datasets using NetworkAnalyst. Differential analysis is further conducted on the normalized data to identify significantly enriched genes. The significant genes are then grouped into pathways. The results were validated using yeast model of ALS in which the yeast is transformed with ALS plasmids encoding genes associated with ALS. The resulting GFP-tagged protein aggregates are imaged using fluorescence microscopy and subsequently validated using filter retardation assay and quantified using ImageJ software. Functional role of different genes is studied using metabolite treatment and knockout studies.

Tecoma stans Floral Extract-Based Biosynthesis for Enhanced Surface Plasmon-Coupled Emission and a Preliminary Study on Fluoroimmunoassay.

We demonstrate the synthesis of biogenic supported silver spiked star architectures and their application to increase the electromagnetic field intensity at its tips that enhance plasmon-coupled emission. Tecoma stans floral extract has been used to synthesize silver nanocubes and spiked stars. We observe ∼445-fold and ∼680-fold enhancements in spacer and cavity configurations, respectively, in the SPCE platform. The hotspot intensity and Purcell factor are evaluated by carrying out finite-difference time-domain (FDTD) simulations. Time-based studies are presented to modulate the sharpness of the edges wherein an increase in the tip sharpness with the increase in reaction time up to 5 h is observed. The unique morphology of the silver architectures allowed us to utilize them in biosensing application. A SPCE-based fluoroimmunoassay was performed, achieving a 1.9 pg/mL limit of detection of TNF-α cytokine. This combination of anisotropic architectures, SPCE and immunoassay prove to be a powerful platform for the ultrasensitive detection of biomarkers in surface-bound assays.

Metabolic deregulation associated with aging modulates protein aggregation in the yeast model of Huntington's disease.

Huntington's disease is associated with increased CAG repeat resulting in an expanded polyglutamine tract in the protein Huntingtin (HTT) leading to its aggregation resulting in neurodegeneration. Previous studies have shown that N-terminal HTT with 46Q aggregated in the stationary phase but not the logarithmic phase in the yeast model of HD. We carried out a metabolomic analysis of logarithmic and stationary phase yeast model of HD expressing different polyQ lengths attached to N-terminal HTT tagged with enhanced green fluorescent protein (EGFP). The results show significant changes in the metabolic profile and deregulated pathways in stationary phase cells compared to logarithmic phase cells. Comparison of metabolic pathways obtained from logarithmic phase 46Q versus 25Q with those obtained for presymptomatic HD patients from our previous study and drosophila model of HD showed considerable overlap. The arginine biosynthesis pathway emerged as one of the key pathways that is common in stationary phase yeast compared to logarithmic phase and HD patients. Treatment of yeast with arginine led to a significant decrease, while transfer to arginine drop-out media led to a significant increase in the size of protein aggregates in both logarithmic and stationary phase yeast model of HD. Knockout of arginine transporters in the endoplasmic reticulum and vacuole led to a significant decrease in mutant HTT aggregation. Overall our results highlight arginine as a critical metabolite that modulates the aggregation of mutant HTT and disease progression in HD.Communicated by Ramaswamy H. Sarma.

Computational analysis of sodium-dependent phosphate transporter SLC20A1/PiT1 gene identifies missense variations C573F, and T58A as high-risk deleterious SNPs.

SLC20A1/PiT1 is a sodium-dependent inorganic phosphate transporter, initially recognized as the retroviral receptor for Gibbon Ape Leukemia Virus in humans. SNPs in SLC20A1 is associated with Combined Pituitary Hormone Deficiency and Sodium Lithium Counter transport. Using in silico techniques, we have screened the nsSNPs for their deleterious effect on the structure and function of SLC20A1. Screening with sequence and structure-based tools on 430 nsSNPs, filtered 17 nsSNPs which are deleterious. To evaluate the role of these SNPs, protein modeling and MD simulations were performed. A comparative analysis of model generated with SWISS-MODEL and AlphaFold shows that many residues are in the disallowed region of Ramachandran plot. Since SWISS-MODEL structure has a 25-residue deletion, the AlphaFold structure was used to perform MD simulation for equilibration and structure refinement. Further, to understand perturbation of energetics, we performed in silico mutagenesis and ΔΔG calculation using FoldX on MD refined structures, which yielded SNPs that are neutral (3), destabilizing (12) and stabilizing (2) on protein structure. Furthermore, to elucidate the impact of SNPs on structure, we performed MD simulations to discern the changes in RMSD, Rg, RMSF and LigPlot of interacting residues. RMSF profiles of representative SNPs revealed that A114V (neutral) and T58A (positive) were more flexible & C573F (negative) was more rigid compared to wild type, which is also reflected in the changes in number of local interacting residues in LigPlot and ΔΔG. Taken together, our results show that SNPs can lead to structural perturbations and impact the function of SLC20A1 with potential implications for disease.Communicated by Ramaswamy H. Sarma.

Integrated clinical and metabolomic analysis of dengue infection shows molecular signatures associated with host-pathogen interaction in different phases of the disease.

PURPOSE: Dengue is a mosquito vector-borne disease caused by the dengue virus, which affects 125 million people globally. The disease causes considerable morbidity. The disease, based on symptoms, is classified into three characteristic phases, which can further lead to complications in the second phase. Molecular signatures that are associated with the three phases have not been well characterized. We performed an integrated clinical and metabolomic analysis of our patient cohort and compared it with omics data from the literature to identify signatures unique to the different phases. METHODS: The dengue patients are recruited by clinicians after standard-of-care diagnostic tests and evaluation of symptoms. Blood from the patients was collected. NS1 antigen, IgM, IgG antibodies, and cytokines in serum were analyzed using ELISA. Targeted metabolomics was performed using LC-MS triple quad. The results were compared with analyzed transcriptomic data from the GEO database and metabolomic data sets from the literature. RESULTS: The dengue patients displayed characteristic features of the disease, including elevated NS1 levels. TNF-α was found to be elevated in all three phases compared to healthy controls. The metabolic pathways were found to be deregulated compared to healthy controls only in phases I and II of dengue patients. The pathways represent viral replication and host response mediated pathways. The major pathways include nucleotide metabolism of various amino acids and fatty acids, biotin, etc. CONCLUSION: The results show elevated TNF-α and metabolites that are characteristic of viral infection and host response. IL10 and IFN-γ were not significant, consistent with the absence of any complications.

Integrated Omic Analysis Delineates Pathways Modulating Toxic TDP-43 Protein Aggregates in Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is a multi-systemic, incurable, amyloid disease affecting the motor neurons, resulting in the death of patients. The disease is either sporadic or familial with SOD1, C9orf72, FUS, and TDP-43 constituting the majority of familial ALS. Multi-omics studies on patients and model systems like mice and yeast have helped in understanding the association of various signaling and metabolic pathways with the disease. The yeast model system has played a pivotal role in elucidating the gene amyloid interactions. We carried out an integrated transcriptomic and metabolomic analysis of the TDP-43 expressing yeast model to elucidate deregulated pathways associated with the disease. The analysis shows the deregulation of the TCA cycle, single carbon metabolism, glutathione metabolism, and fatty acid metabolism. Transcriptomic analysis of GEO datasets of TDP-43 expressing motor neurons from mice models of ALS and ALS patients shows considerable overlap with experimental results. Furthermore, a yeast model was used to validate the obtained results using metabolite addition and gene knock-out experiments. Taken together, our result shows a potential role for the TCA cycle, cellular redox pathway, NAD metabolism, and fatty acid metabolism in disease. Supplementation of reduced glutathione, nicotinate, and the keto diet might help to manage the disease.

Integrated multi-omics analysis of Alzheimer's disease shows molecular signatures associated with disease progression and potential therapeutic targets.

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the formation of amyloid plaques implicated in neuronal death. Genetics, age, and sex are the risk factors attributed to AD. Though omics studies have helped to identify pathways associated with AD, an integrated systems analysis with the available data could help to understand mechanisms, potential biomarkers, and therapeutic targets. Analysis of transcriptomic data sets from the GEO database, and proteomic and metabolomic data sets from literature was performed to identify deregulated pathways and commonality analysis identified overlapping pathways among the data sets. The deregulated pathways included those of neurotransmitter synapses, oxidative stress, inflammation, vitamins, complement, and coagulation pathways. Cell type analysis of GEO data sets showed microglia, endothelial, myeloid, and lymphoid cells are affected. Microglia are associated with inflammation and pruning of synapses with implications for memory and cognition. Analysis of the protein-cofactor network of B2, B6, and pantothenate shows metabolic pathways modulated by these vitamins which overlap with the deregulated pathways from the multi-omics analysis. Overall, the integrated analysis identified the molecular signature associated with AD. Treatment with anti-oxidants, B2, B6, and pantothenate in genetically susceptible individuals in the pre-symptomatic stage might help in better management of the disease.

Vitamin B6, B12 and folate modulate deregulated pathways and protein aggregation in yeast model of Huntington disease.

Huntington's disease (HD) is an incurable and progressive neurodegenerative disease affecting the basal ganglia of the brain. HD is caused due to expansion of the polyglutamine tract in the protein Huntingtin resulting in aggregates. The increased PolyQ length results in aggregation of protein Huntingtin leading to neuronal cell death. Vitamin B6, B12 and folate are deficient in many neurodegenerative diseases. We performed an integrated analysis of transcriptomic, metabolomic and cofactor-protein network of vitamin B6, B12 and folate was performed. Our results show considerable overlap of pathways modulated by Vitamin B6, B12 and folate with those obtained from transcriptomic and metabolomic data of HD patients and model systems. Further, in yeast model of HD we showed treatment of B6, B12 or folate either alone or in combination showed impaired aggregate formation. Transcriptomic analysis of yeast model treated with B6, B12 and folate showed upregulation of pathways like ubiquitin mediated proteolysis, autophagy, peroxisome, fatty acid, lipid and nitrogen metabolism. Metabolomic analysis of yeast model shows deregulation of pathways like aminoacyl-tRNA biosynthesis, metabolism of various amino acids, nitrogen metabolism and glutathione metabolism. Integrated transcriptomic and metabolomic analysis of yeast model showed concordance in the pathways obtained. Knockout of Peroxisomal (PXP1 and PEX7) and Autophagy (ATG5) genes in yeast increased aggregates which is mitigated by vitamin B6, B12 and folate treatment. Taken together our results show a role for Vitamin B6, B12 and folate mediated modulation of pathways important for preventing protein aggregation with potential implications for HD. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03525-y.

Structural systems biology approach delineate the functional implications of SNPs in exon junction complex interaction network.

In eukaryotes, transcripts that carry premature termination codons (PTC) leading to truncated proteins are degraded by the Nonsense Mediated Decay (NMD) machinery. Missense and nonsense Single Nucleotide Polymorphisms (SNPs) in proteins belonging to Exon junction complex (EJC) and up-frameshift protein (UPF) will compromise NMD leading to the accumulation of truncated proteins in various diseases. The EJC and UPF which are involved in NMD is a good model system to study the effect of SNPs at a system level. Despite the availability of crystal structures, computational tools, and data on mutational and deletion studies, with functional implications, an integrated effort to understand the impact of SNPs at the systems level is lacking. To study the functional consequences of missense SNPs, sequence-based techniques like SIFT and PolyPhen which classify SNPs as deleterious or non-deleterious and structure-based methods like FoldX which calculate the Delta Delta G, (ddGs, ∆∆G) are used. Using FoldX, the ddG for mutations with experimentally validated functional effects is calculated and compared with those calculated for SNPs in the same protein-protein interaction interface. Further, a model is conceived to explain the functional implications of SNPs based on the effects observed for known mutants. The results are visualized in a network format. The effects of nonsense mutations are discerned by comparing with deletion mutation studies and loss of interaction in the crystal structure. The present work not only integrates genomics, proteomics, and classical genetics with 'Structural Biology' but also helps to integrate it into a 'systems-level functional network'.Communicated by Ramaswamy H. Sarma.

Integrated multi-omic data analysis and validation with yeast model show oxidative phosphorylation modulates protein aggregation in amyotrophic lateral sclerosis.

Amyotrophic Lateral Sclerosis is a progressive, incurable amyloid aggregating neurodegenerative disease involving the motor neurons. Identifying potential biomarkers and therapeutic targets can assist in the better management of the disease. We used an integrative approach encompassing analysis of transcriptomic datasets of human and mice from the GEO database. Our analysis of ALS patient datasets showed deregulation in Non-alcoholic fatty acid liver disease and oxidative phosphorylation. Transgenic mice datasets of SOD1, FUS and TDP-43 showed deregulation in oxidative phosphorylation and ribosome-associated pathways. Commonality analysis between the human and mice datasets showed oxidative phosphorylation as a major deregulated pathway. Further, protein-protein and protein-drug interaction network analysis of mitochondrial electron transport chain showed enrichment of proteins and inhibitors of mitochondrial Complex III and IV. The results were further validated using the yeast model system. Inhibitor studies using metformin (Complex-I inhibitor) and malonate (Complex-II inhibitor) did not show any effect in mitigating the amyloids, while antimycin (Complex-III inhibitor) and azide (Complex-IV inhibitor) reduced amyloidogenesis. Knock-out of QCR8 (Complex-III) or COX8 (Complex-IV) cleared the amyloids. Taken together, our results show a critical role for mitochondrial oxidative phosphorylation in amyloidogenesis and as a potential therapeutic target in ALS.Communicated by Ramaswamy H. Sarma.

Systems biology approach delineates critical pathways associated with disease progression in rheumatoid arthritis.

Rheumatoid Arthritis (RA) is a chronic systemic autoimmune disease leading to inflammation, cartilage cell death, synoviocyte proliferation, and increased and impaired differentiation of osteoclasts and osteoblasts leading to joint erosions and deformities. Transcriptomics, proteomics, and metabolomics datasets were analyzed to identify the critical pathways that drive the RA pathophysiology. Single nucleotide polymorphisms (SNPs) associated with RA were analyzed for the functional implications, clinical outcomes, and blood parameters later validated by literature. SNPs associated with RA were grouped into pathways that drive the immune response and cytokine production. Further gene set enrichment analysis (GSEA) was performed on gene expression omnibus (GEO) data sets of peripheral blood mononuclear cells (PBMCs), synovial macrophages, and synovial biopsies from RA patients showed enrichment of Th1, Th2, Th17 differentiation, viral and bacterial infections, metabolic signalling and immunological pathways with potential implications for RA. The proteomics data analysis presented pathways with genes involved in immunological signaling and metabolic pathways, including vitamin B12 and folate metabolism. Metabolomics datasets analysis showed significant pathways like amino-acyl tRNA biosynthesis, metabolism of amino acids (arginine, alanine aspartate, glutamate, glutamine, phenylalanine, and tryptophan), and nucleotide metabolism. Furthermore, our commonality analysis of multi-omics datasets identified common pathways with potential implications for joint remodeling in RA. Disease-modifying anti-rheumatic drugs (DMARDs) and biologics treatments were found to modulate many of the pathways that were deregulated in RA. Overall, our analysis identified molecular signatures associated with the observed symptoms, joint erosions, potential biomarkers, and therapeutic targets in RA.Communicated by Ramaswamy H. Sarma.

Integrated network pharmacology approach shows a potential role of Ginseng catechins and ginsenosides in modulating protein aggregation in Amyotrophic Lateral Sclerosis.

Amyotrophic lateral Sclerosis is an incurable, progressive neurodegenerative motor neuron disease. The disease is characterized by protein aggregates. The symptoms include weakness, denervation of muscles, atrophy and progressive paralysis of bulbar and respiratory muscles and dysphagia. Various secondary metabolites are evaluated for their ability to improve symptoms in ALS. Ginseng has been traditionally used for treating several neurodegenerative diseases. Several studies using model systems have shown a potential role of Ginseng catechins and Ginsenosides in clearing protein aggregation associated with ALS. We focus on Network pharmacology approach to understand the effect of Ginseng catechins or ginsenosides on protein aggregation associated with ALS. A catechin/ginsenoside-protein interaction network was generated and the pathways obtained were compared with those obtained from transcriptomic datasets of ALS from GEO database. Knock out of MAPK14, AKT and GSK from Catechin and BACE 1 from ginsenoside modulated pathways inhibited protein aggregation. Catechins and ginsenosides have potential as therapeutic agents in the management of ALS. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03401-1.

Integrated multi-omics analysis of Huntington disease identifies pathways that modulate protein aggregation.

Huntington disease (HD) is a neurodegenerative disease associated with polyglutamine expansion in the protein huntingtin (HTT). Although the length of the polyglutamine repeat correlates with age at disease onset and severity, psychological, cognitive and behavioral complications point to the existence of disease modifiers. Mitochondrial dysfunction and metabolic deregulation are both associated with the HD but, despite multi-omics characterization of patients and model systems, their mechanisms have remained elusive. Systems analysis of multi-omics data and its validation by using a yeast model could help to elucidate pathways that modulate protein aggregation. Metabolomics analysis of HD patients and of a yeast model of HD was, therefore, carried out. Our analysis showed a considerable overlap of deregulated metabolic pathways. Further, the multi-omics analysis showed deregulated pathways common in human, mice and yeast model systems, and those that are unique to them. The deregulated pathways include metabolic pathways of various amino acids, glutathione metabolism, longevity, autophagy and mitophagy. The addition of certain metabolites as well as gene knockouts targeting the deregulated metabolic and autophagy pathways in the yeast model system showed that these pathways do modulate protein aggregation. Taken together, our results showed that the modulation of deregulated pathways influences protein aggregation in HD, and has implications for progression and prognosis. This article has an associated First Person interview with the first author of the paper.

Integrated Transcriptome and Metabolomic Analysis Reveal Anti-Angiogenic Properties of Disarib, a Novel Bcl2-Specific Inhibitor.

Transcriptomic profiling of several drugs in cancer cell lines has been utilised to obtain drug-specific signatures and guided combination therapy to combat drug resistance and toxicity. Global metabolomics reflects changes due to altered activity of enzymes, environmental factors, etc. Integrating transcriptomics and metabolomics can provide genotype-phenotype correlation, providing meaningful insights into alterations in gene expression and its outcome to understand differential metabolism and guide therapy. This study uses a multi-omics approach to understand the global gene expression and metabolite changes induced by Disarib, a novel Bcl2-specific inhibitor in the Ehrlich adenocarcinoma (EAC) breast cancer mouse model. RNAseq analysis was performed on EAC mouse tumours treated with Disarib and compared to the controls. The expression of 6 oncogenes and 101 tumour suppressor genes interacting with Bcl2 and Bak were modulated upon Disarib treatment. Cancer hallmark pathways like DNA repair, Cell cycle, angiogenesis, and mitochondrial metabolism were downregulated, and programmed cell death platelet-related pathways were upregulated. Global metabolomic profiling using LC-MS revealed that Oncometabolites like carnitine, oleic acid, glycine, and arginine were elevated in tumour mice compared to normal and were downregulated upon Disarib treatment. Integrated transcriptomic and metabolomic profiles identified arginine metabolism, histidine, and purine metabolism to be altered upon Disarib treatment. Pro-angiogenic metabolites, arginine, palmitic acid, oleic acid, and myristoleic acid were downregulated in Disarib-treated mice. We further validated the effect of Disarib on angiogenesis by qRT-PCR analysis of genes in the VEGF pathway. Disarib treatment led to the downregulation of pro-angiogenic markers. Furthermore, the chorioallantoic membrane assay displayed a reduction in the formation of the number of secondary blood vessels upon Disarib treatment. Disarib reduces tumours by reducing oncometabolite and activating apoptosis and downregulating angiogenesis.

Proficient mycogenic synthesis of silver nanoparticles by soil derived fungus Aspergillus melleus SSS-10 with cytotoxic and antibacterial potency.

The present study aimed at evaluating the extracellular synthesis of silver nanoparticles by soil fungus Aspergillus melleus SSS-10 for antibacterial and cytotoxic activity. In this study, the formation of silver nanoparticles (AgNPs) was estimated by the colour change in cell free extract from pale yellow to golden yellow after 24 h of the reaction. UV-Vis study showed the absorbance maxima at 410 nm. Tauc plot analysis revealed the band gap energy as 2.34 eV. Dynamic Light Scattering (DLS) data revealed polydisperse anisotropic silver nanoparticles with average hydrodynamic diameter of 92.006 nm. Zeta potential of - 19.6 mV provided evidence of stable silver nanoparticles. X-ray diffraction (XRD) analysis revealed four prominent Bragg peaks corresponding to (111), (200), (220) and (311) planes characteristic of silver (Ag) in FCC structural configuration. Average crystallite size was found to be 87.3 nm from Scherrer equation. Scanning Electron Microscope (SEM) analysis revealed irregular morphology of silver nanoparticles. EDS analysis displayed characteristic energy peaks of silver from 2.72 keV to 3.52 keV confirming the presence of silver nanoparticles. Biosynthesized AgNPs exhibited strong cytotoxic potential on MG-63 cells. AgNPs also showed antibacterial activity against both Staphylococcus aureus and Escherichia coli. In conclusion, this study provides a platform to explore the utility of fungal mediated silver nanoparticles synthesized for various pharmaceutical and cosmeceutical applications.

Elevated ATP, cytokines and potential microglial inflammation distinguish exfoliation glaucoma from exfoliation syndrome.

Glaucoma is the second leading cause of blindness. Exfoliation syndrome (XFN) is a risk factor for exfoliation glaucoma (XFG) which is a secondary open angle glaucoma. XFG is difficult to manage with a worse prognosis. Though 40% of the XFN progress to XFG, there are no predictive markers to identify the susceptible patients. Herein, we analyze clinical data, ATP levels in aqueous humor and cytokines in plasma to identify alteration that help distinguish XFN from XFG. Our results show characteristic clinical features of XFG compared to XFN and controls. Elevated levels of ATP in aqueous humor were observed in XFG compared to XFN and cataract controls while elevated levels of plasma cytokines were observed in XFG compared to XFN, cataract controls and healthy controls. Microglia are immune cells in the retina implicated in glaucoma. TNFα plays a predominant role in microglial inflammation and is implicated in neurodegeneration. Using in vitro N9 microglial cell culture model, we demonstrate that TNFα modulated expression of cytokines and chemotaxis is dependent on P2 receptors like P2X7, P2Y12 and P2Y6. In addition, ATP also induce expression of TNFα which might act as a feed forward loop. The TNFα induced inflammation is dependent on downstream signaling modules like PI3K, JNK and ROS. Taken together, our results show that elevated ATP in aqueous humor, plasma cytokines and inflammation potentially involving microglia distinguish XFG from XFN. Purinergic receptors might be potential therapeutic targets in XFG.