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      Network pharmacology of AYUSH recommended immune-boosting medicinal plants against COVID-19

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          Abstract

          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 by the combined action of AYUSH recommended herbal tea and golden milk formulation as an immune booster against COVID-19.

          Materials and methods

          Reported phytoconstituents of all the medicinal 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, 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 involved in boosting the immunity but also modulated the multiple pathways that are contributing to the progression of multiple disease pathogenesis which would add the beneficial effect in the co-morbid patients of hypertension and diabetes. The study provides the scientific documentation of the role of the Ayurvedic formulation to combat COVID-19.

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          Most cited references25

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            Is Open Access

            The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible

            A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein–protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein–protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/.
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              Lead- and drug-like compounds: the rule-of-five revolution.

              Citations in CAS SciFinder to the rule-of-five (RO5) publication will exceed 1000 by year-end 2004. Trends in the RO5 literature explosion that can be discerned are the further definitions of drug-like. This topic is explored in terms of drug-like physicochemical features, drug-like structural features, a comparison of drug-like and non-drug-like in drug discovery and a discussion of how drug-like features relate to clinical success. Physicochemical features of CNS drugs and features related to CNS blood-brain transporter affinity are briefly reviewed. Recent literature on features of non-oral drugs is reviewed and how features of lead-like compounds differ from those of drug-like compounds is discussed. Most recently, partly driven by NIH roadmap initiatives, considerations have arisen as to what tool-like means in the search for chemical tools to probe biology space. All these topics frame the scope of this short review/perspective.: © 2004 Elsevier Ltd . All rights reserved.
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                Author and article information

                Journal
                J Ayurveda Integr Med
                J Ayurveda Integr Med
                Journal of Ayurveda and Integrative Medicine
                The Authors. Published by Elsevier B.V. on behalf of Institute of Transdisciplinary Health Sciences and Technology and World Ayurveda Foundation
                0975-9476
                0976-2809
                25 November 2020
                25 November 2020
                Affiliations
                [a ]Department of Pharmacology and Toxicology, KLE College of Pharmacy, Belagavi, KLE Academy of Higher Education and Research (KAHER), Belagavi-590010, Karnataka, India
                [b ]School of Pharmaceutical Technology, Adamas University, Kolkata-700126, West Bengal, India
                [c ]Department of Pharmacology, Orotta College of Medicine and Health Sciences, Asmara University, Asmara, Eritrea
                [d ]Regional Ayurveda Research Institute for Drug Development, Gwalior-474009, Madhya Pradesh, India
                [e ]Department of Pharmacognosy, Goa College of Pharmacy, Panjim-403001, Goa, India
                Author notes
                []Corresponding author. School of Pharmaceutical Technology, Adamas University, Kolkata-700126, West Bengal, India.
                [∗∗ ]Corresponding author. Department of Pharmacology and Toxicology, KLE College of Pharmacy, KLE Academy of Higher Education and Research (KAHER), Belagavi-590010, India.
                [1]

                equal contribution.

                Article
                S0975-9476(20)30107-8
                10.1016/j.jaim.2020.11.004
                7687402
                33250601
                e522b864-44ff-4636-8a22-36d87b5cc4bc
                © 2020 The Authors

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 21 April 2020
                : 9 November 2020
                : 11 November 2020
                Categories
                Short Communication

                Complementary & Alternative medicine
                ayush,covid-19,herbal tea,immunity promotion
                Complementary & Alternative medicine
                ayush, covid-19, herbal tea, immunity promotion

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