Background: Tinospora cordifolia is used traditionally for the treatment of diabetes and is used in various formulations. Scientific evidence is also available for its anti-diabetic potency under various animal models. However, the probable molecular mechanism of Tinospora cordifolia in the treatment of diabetes has not been illuminated yet. Hence, the present study dealt to elucidate the probable molecular mechanism of anti-diabetic effect of Tinospora cordifolia using network pharmacology approach. Methods: The structural information of bioactive phytoconstituents was retrieved from different open source databases. Compounds were then predicted for their hits with the probable targets involved in the diabetes mellitus. Phytoconstituents were also predicted for their druglikeness score, probable side effects, and ADMET profile. The modulated protein pathways were identified by using the Kyoto Encyclopedia of Genes and Genomes pathway analysis. The interaction between the compounds, proteins, and pathways was interpreted based on the edge count. The docking study was performed using Autodock4.0. Results: Nine phytoconstituents from Tinospora cordifolia were identified to modulate the pathogenic protein molecules involved in diabetes mellitus. Among them, tembetarine scored highest druglikeness hit and had the maximum interaction with proteins involved in diabetes. Further, neuroactive ligand-receptor interaction was predicted as majorly modulated pathway. Conclusion: The current study identified an important antidiabetic constituent, tembetarine which modulated the majority of diabetic proteins majorly modulating neuroactive ligand-receptor interaction.

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Background: The Ministry of AYUSH recommended the use of a decoction of the mixture of Ocimum tenuiflorum, Cinnamomum verum, Piper nigrum, Zingiber officinale, and Vitis vinifera as a preventive measure to boost immunity and to inhibit the severity of infection caused by a novel coronavirus (COVID-19). Objective: The present study aimed to identify the probable modulated pathways via AYUSH recommended formulation as an immune booster against COVID-19.Materials and methods: Reported phytoconstituents of all the plants were retrieved from the ChEBI database, and their targets were predicted using DIGEP-Pred. STRING database and Cytoscape were used to predict the protein-protein interaction and construct the network interaction respectively. Likewise, MolSoft and admetSAR2.0 were used to predict the druglikeness score and ADMET profile of phytoconstituents. Results: The study identified the modulation of HIF-1, p53, PI3K-Akt, MAPK, cAMP, Ras, Wnt, NF-kappa B, IL-17, TNF, and cGMP-PKG signaling pathways to boost the immune system. Further, multiple pathways were also identified which are involved in the regulation of pathogenesis of the multiple infections and non-infectious diseases due to the lower immune system.Conclusion: Results indicated that the recommended herbal formulation not only modulated the pathways related to boost the immune system but also modulated the multiple pathways that are contributing in the progression of multiple disease pathogenesis which would add the beneficial effect in the special subjects like patients from hypertension and diabetes in which 4-hydroxychloroquine therapeutic approach cannot be made. The study provides the scientific documentation of the role of the Ayurvedic formulation to combat COVID-19.

Aim. The present study was aimed to identify the lead hits from reported anti-viral Indian medicinal plants to modulate the proteins through the JAK-STAT pathway and to identify the proteins that share the domain with coronavirus (COVID19) associated proteins i.e. 3CLpro, PLpro, and spike protein. Methods. The reported anti-viral plants were screened from the available databases and published literature; their phytoconstituents were retrieved, gene-expression was predicted and the modulated proteins in JAK-STAT pathway were predicted. The interaction between proteins was evaluated using STRING and the network between phytoconstituents and proteins was constructed using Cytoscape. The druglikeness score was predicted using MolSoft and the ADMET profile of phytoconstituents was evaluated using admetSAR2.0. The domain of three proteins i.e. 3CLpro, PLpro, and spike protein of coronavirus was compared using NCBI blastP against the RCSB database. Results. The majority of the phytoconstituents from the anti-viral plants were predicted to target TRAF5 protein in the JAK-STAT pathway; among them, vitexilactone was predicted to possess the highest druglikeness score. Proteins targeted in the JAK-STAT pathways were also predicted to modulate the immune system. Similarly, the docking study identified sesaminol 2-O-β-D-gentiobioside to possess the highest binding affinity with spike protein. Similarly, phylogeny comparison also identified the common protein domains with other stains of microbes like murine hepatitis virus strain A59, avian infectious bronchitis virus, and porcine epidemic diarrhea virus CV777. Conclusion. Although, the present study is based on computer simulations and database mining, it provides two important aspects in identifying the lead hits against coronavirus. First, targeting the JAK-STAT pathway in the corona-infected host by folk anti-viral agents can regulate the immune system which would inhibit spreading the virus inside the subject. Secondly, the well-known targets of coronavirus i.e. 3CLpro, PLpro, and spike protein share some common domains with other proteins of different microbial strains.

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