With the current pandemic of the novel coronavirus disease 2019 (COVID-19) in hand, researchers around the globe are dexterously working to find the best suitable drug candidates and overcome vaccination-related challenges, to achieve efficient control over the second surge of COVID-19. The medical consultants time and again have been reiterating the need to abide by the precautionary steps to prevent the spread of the coronavirus by maintaining social distancing when outside, sanitizing hands regularly, and wearing masks and gloves. They also suggest taking a good and hygienic meal so as to boost immunity. Indians have an inborn nature of using natural spices, food, and medicines in their daily lives. Indian researchers have paid heed to deploy compounds from natural sources to explore potential antiviral agents against COVID-19 as the chances of acquiring side effects are perceived as less, and the efficacy of phytochemicals from medicinal plants is sometimes greater when compared to their synthetic counterparts. In the present study, we performed an in silico molecular docking and molecular dynamic simulation analysis of screened phytochemicals from a comprehensive list of Ayurvedic herbs/functional foods that are present in natural food products against key receptor proteins of severe acute respiratory syndrome coronavirus 2. We found that Aegle marmelos, Vetiveria zizanoides, Moringaolifera, and Punica granatum have antiviral potential to prevent coronavirus infection in the populace.

Even after one and a half years since the outbreak of COVID-19, its complete and effective control is still far from being achieved despite vaccination drives, symptomatic management with available drugs, and wider lockdowns. This has inspired researchers to screen potential phytochemicals from medicinal plants against SARS-CoV-2, adopting a bio-informatics approach. The current study aimed to assess anti-viral activity of the phytochemicals derived from Ayurvedic medicinal plants against SARS-CoV-2 drug targets [3-chymotrypsin-like protease (3CLpro) and RNA dependent RNA polymerase (RdRp)] using validated in silico methods.3D Structures of 196 phytochemicals from three Ayurvedic plants were retrieved from PubChem and KNApSAcK databases and screened for Absorption Distribution Metabolism Excretion and Toxicity(ADMET) to predict drug-likeness. The phytochemicals were subjected to molecular docking and only three showed promise: Acetovanillonewith a binding affinity of −4.7Kcal/mol with RdRp and −4.1 Kcal/mol with 3CL pro; myrtenol with equivalent values of −4.3 Kcal/mol with RdRP and −3.2 Kcal/mol with 3CLpro; and nimbochalcin with equivalent values of −5.0Kcal/mol with RdRp and −4.9 Kcal/mol with 3CLpro. Molecular dynamics simulation (50ns) analysis was made of 3CLpro and RdRp using Autodock Vina 1.1.2 software and VMD software. After ADMET analysis, 78 phytochemicals were found suitable for molecular docking. Three, namely acetovanillone, myrtenol and nimbochalcin from Picrorhiza kurroa, Azadirachta indica and Cyperus rotundus,respectively,exhibited good binding affinity with 3CLproand RdRp of SARS-CoV-2. Interaction analysis, molecular dynamics simulations and MM-PBSA calculations were executed for two complexes, acetovanillone_RdRp and myrtenol_3CL pro.Acetovanillone_RdRpcomplex did not display any structural change after MD simulation as compared to myrtenol_3CL pro. The overall stability of acetovanillone_6NUR was 154.7 kJ/mol, and for myrtenol_1UJ1 90.5 kJ/mol. In silico analysis revealed that acetovanillone ( Picrorhiza kurroa) and myrtenol ( Cyperus rotundus) possess anti SARS-CoV-2 activity. Further studies are needed to validate their efficacy in biological models.

The COVID-19 pandemic has posed a significant threat to human health due to the lack of drugs that can potentially act against SARS-CoV -2. Also, even after the emergency approval of WHO, the vaccines’ efficacy is still a question, and people are getting reinfections. Previous studies have demonstrated the efficacy of traditional medicinal plants against influenza and SARS coronavirus. The present article aims to review potential phytochemicals from Indian medicinal plants that may be used against SARS-CoV-2. Articles published in the English language between 1992 and 2021 were retrieved from Embase, PubMed, and Google scholar using relevant keywords, and the scientific literature on efficacies of Indian medicinal plants against SARS-CoV and influenza virus were analyzed. The initial search revealed 1304 studies, but, on subsequent screening, 115 eligible studies were reported. Twenty research articles investigating traditional medicinal plant extracts and metabolites against SARS-CoV and influenza A virus in in vitro and in vivo systems satisfied the search criteria. The studies reported that plant extracts and active compounds such as glycyrrhizin, 14-α-lipoyl andrographolide, and curcumin from medicinal plants such as Yashtimadhu ( Glycyrrhiza glabra), Bhunimba ( Andrographis paniculata), and Haridra ( Curcuma longa) are effective against the various phases of the virus life cycle, viz., virus-host cell attachment, viral replication, 3CL protease activity, neuraminidase activity, adsorption and penetration of the virus. As per ancient Indian literature, plants in Ayurveda possess Rasayana (revitalizing) and Jwara hara (antipyretic, anti-inflammatory) properties. This evidence may be used to conduct experimental and clinical trials to study the underlying mechanisms and efficacy of antiviral properties of Indian medicinal plants against SARS-CoV-2.

Nisha Amalaki (NA), an Indian herbal formulation consisting of two herbs, Curcuma longa and Emblica officinalis, has been commonly used to treat Type 2 diabetes mellitus (T2DM). However, the pharmacological mechanism of NA remains unknown. In this study, a network pharmacology-based approach was used to explore its underlying mechanism. NA phytochemicals were collected from PubChem, KNApSAcK, IMPPAT, and ChEBI databases, and their potential targets were investigated using similarity ensemble approach (Tanimoto coefficient ≥ 0.6). A protein-protein interaction network was constructed to study the interactions among the targets and clustered into separate modules using NetworkAnalyst 3.0. A significant module (P ≤ .01) was identified, and DAVID web tool was utilized for the enrichment analysis. A total of 201 phytochemicals and 262 targets of NA were selected. Forty-five nodes of the significant module were identified as potential targets of NA. The enrichment analysis exhibited 27 biological processes and 78 pathways (P ≤ .01). Out of 45, 18 nodes were associated with T2DM as probable targets of NA. The metabolite-target-pathway network revealed that anti-diabetic effect of NA is a synergy of multi-target and multi-pathway efforts via regulation of glucose, lipid metabolism, insulin resistance, β-cell survival and proliferation, inflammation, apoptosis, and cell cycle.

Objective: Trikatu is an Indian polyherbal formulation comprising three herbs, i.e., Zingiber officinale, Piper longum, and Piper nigrum. It is traditionally used to treat metabolic disorders such as type 2 diabetes mellitus (T2DM), dyslipidemia, and obesity. However, its mechanism of action remains unknown. This study aims to explore the underlying therapeutic mechanism of Trikatu in T2DM and lipid metabolic disorders using network pharmacology (NP). Methods: Trikatu phytochemicals were retrieved from various databases and screened on the basis of druglikeness and oral bioavailability (>30%) score. Putative targets of the bioactive phytochemicals were identified using TargetNet, Similarity Ensemble Approach, and Swiss Target Prediction databases. Protein-protein interaction (PPI) network of overlapping targets of phytochemicals and metabolic disorders was constructed using NetworkAnalyst 3.0. The Bioactive Phytochemical-Target-Pathway (BP-T-P) network was constructed using cytoscape v3.8.2, and the key targets of Trikatu were analyzed by Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Results: Twenty bioactive phytochemicals and 102 targets of Trikatu were identified. PPI network and enrichment analysis showed that 51 targets of Trikatu phytochemicals such as RXRA, STAT3 and ESR1, GSK3B, TNF, NOS2/3 regulate pathways like insulin resistance, steroid hormone biosynthesis, regulation of lipolysis in adipocytes, adipocytokine & cGMP-PKG signalling pathways, arachidonic acid metabolism and bile secretion. The results were validated by molecular docking which showed that RXRA, STAT3 and ESR1 strongly interact with their ligands alpha gurjunene, beta-sitosterol, piperlongumine, genistein and E-beta carotene, respectively. Conclusion: Hence, the multiple target and multiple pathway approach of Trikatu can be further explored in pharmacokinetics / Pharmacodynamics studies.

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Background:: The scientific community has supported from the medicinal flora of ancient as well as modern times in extracting chemicals, which holds therapeutic potential. In many previous studies, it was discovered Amentoflavone as an anti-viral agent and its presence as a bioactive constituent in many plants of different families Selaginellaceae, Euphorbiaceae, and Calophyllaceae etc. Withania somnifera (Ashwagandha) is already considered significant anti-viral agent in traditional medicine, and it is the main source of Somniferine-A, Withanolide-B. Objective:: In this study phytochemicals such as Withanolide-B, Somniferine-A, Stigmasterol, Amentoflavone, and Chavicine were analyzed to screen protein inhibitors out of them; such proteins are involved in SARS-Cov-2's internalization and interaction with human cytological domains. This will help in developing check point for SARS-Cov-2 internalization. Material and methods:: Chemi-informatic tools like basic local alignment search tool (BLAST), AutoDock-vina, SwissADME, MDWeb, Molsoft, ProTox-II, and LigPlot were deployed to examine the action of pharmacoactive agents against SARS-Cov-2. The many tools deployed in the study were based on finest algorithms like Artificial neural networking, Machine Learning, and Artificial intelligence. Results:: On the basis of binding energies less than equal to -8.5 kcal/mol. Amentoflavone, Stigmasterol, and Somniferine-A were found to be most effective against COVID-19 disease as these chemical agents exhibit hydrogen bond interactions and competitively inhibit major proteins (SARS-Cov-2 Spike, Human ACE-2 receptor, Human Furin protease, SARS-Cov-2 RNA binding protein) that are found to involved in its infection and pathogenesis. Simulation analysis provides more validity to the selection of drug candidate Amentoflavone. ADMET properties were found to be in feasible range for putative drug candidates. Conclusion:: Computational analysis was successfully deployed in searching pharmacoactive phytochemicals Like Amentoflavone, Somniferine-A, and Stigmasterol that can bring control over COVID-19 expansion. This new methodology was found to be efficient, as reduces monetary expenditures and time consumption, aftermath molecular wet-lab validations will provide better approval for finalizing our selected drug model for controlling COVID-19 pandemic.

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