ABSTRACT

No abstract

Box–Behnken optimized, adsorption based robust separation technique for acetyl shikonin (AS), a commercially important compound from industrial crop Arnebia nobilis.

Objective:To develop a process that involves optimization of the amount of baicalein and pinostrobin from the hydro-methanolic extract of the leaves of Scutellaria violacea by response surface methodology (RSM).Materials and Methods:The combinatorial influence of various extraction parameters on the extraction yield was investigated by adopting Box–Behnken experimental design. Preliminary experiments carried out based on the traditional one variable at a time optimization revealed four such operational parameters to play a crucial role by influencing the yield. These four process parameters at three levels were considered to obtain the Box–Behnken experimental design.Results:RSM based model fitted to the resulting experimental data suggested that 52.3% methanol/water, 12.46:1 solvent-solid ratio, 285 rpm agitation and 6.07 h of extraction time are the optimal conditions which yielded a maximized amount of baicalein and pinostrobin of 2.9 and 4.05 mg/g DM. Analysis of variance revealed a high correlation coefficient (R2 = 0.999 for baicalein and 0.994 for pinostrobin), signifying a good fit between the regression model (second order) and the experimental observations.Conclusion:The present study signifies that both the metabolites have been extracted from S. violacea for the first time. Further, this study developed an optimized extraction procedure to obtain maximum yield of the metabolites, which is unique and better than conventional extraction methodology. The operational parameters under optimized conditions accounts for the lowest cost in extraction process thus, providing an efficient, rapid and cost-effective method for isolation and scale up of these commercially vital flavonoids.

Epithelial to Mesenchymal Transition (EMT) plays an important role in tissue regeneration, embryonic development, and cancer metastasis. Several signaling pathways are known to regulate EMT, among which the modulation of TGFβ (Transforming Growth Factor-β) induced EMT is crucial in several cancer types. Several mathematical models were built explore the role of core regulatory circuit of ZEB/miR-200, SNAIL/miR-34 double negative feedback loops in modulating TGFβ induced EMT. Different emergent behavior including tristability, irreversible switching, existence of hybrid EMT states were inferred though these models. Some studies have explored the role of TGFβ receptor activation, SMADs nucleocytoplasmic shuttling and complex formation. Recent experiments have revealed that MDM2 along with SMAD complex regulates SNAIL expression driven EMT. Encouraged by this, in the present study we developed a mathematical model for p53/MDM2 dependent TGFβ induced EMT regulation. Inclusion of p53 brings in an additional mechanistic perspective in exploring the EM transition. The network formulated comprises a C1FFL moderating SNAIL expression involving MDM2 and SMAD complex, which functions as a noise filter and persistent detector. The C1FFL was also observed to operate as a coincidence detector driving the SNAIL dependent downstream signaling into phenotypic switching decision. Systems modeling and analysis of the devised network, displayed interesting dynamic behavior, systems response to various inputs stimulus, providing a better understanding of p53/MDM2 dependent TGF-β induced Epithelial to Mesenchymal Transition.

Novel Box–Behnken optimized isolation of the dietary micronutrient β-sitosterol-d-glucopyranoside by solvent assisted ‘green’ hydrotropic precipitation from Desmostachya bipinnata.

Background: Network pharmacology based identification of phytochemicals in the form of cocktails against off-targets can play a significant role in the inhibition of SARS_CoV2 viral entry and its propagation. This study includes network pharmacology, virtual screening, docking and molecular dynamics to investigate the distinct antiviral mechanisms of effective phytochemicals against SARS_CoV2. Methods: SARS_CoV2 human-protein interaction network was explored from the BioGRID database and analysed using Cytoscape. Further analysis was performed to explore biological function, proteinphytochemical/ drugs network and up-down regulation of pathological host target proteins. This led to understand the antiviral mechanism of phytochemicals against SARS_CoV2. The network was explored through g: Profiler, EnrichR, CTD, SwissTarget, STITCH, DrugBank, BindingDB, STRING and SuperPred. Virtual screening of phytochemicals against potential antiviral targets such as M-Pro, NSP1, Receptor binding domain, RNA binding domain, and ACE2 discloses the effective interaction between them. Further, the binding energy calculations through simulation of the docked complex explain the efficiency and stability of the interactions. Results: The network analysis identified quercetin, genistein, luteolin, eugenol, berberine, isorhamnetin and cinnamaldehyde to be interacting with host proteins ACE2, DPP4, COMT, TUBGCP3, CENPF, BRD2 and HMOX1 which are involved in antiviral mechanisms such as viral entry, viral replication, host immune response, and antioxidant activity, thus indicating that herbal cocktails can effectively tackle the viral hijacking of the crucial biological functions of a human host. Further exploration through virtual screening, docking and molecular dynamics recognizes the effective interaction of phytochemicals such as punicalagin, scutellarin, and solamargine with their respective potential targets. Conclusion: This work illustrates a probable strategy for the identification of phytochemical-based cocktails and off-targets which are effective against SARS_CoV 2.

No abstract