Selected article for: "analysis network and target prediction"

Author: Maurya, Vimal K.; Kumar, Swatantra; Bhatt, Madan L. B.; Saxena, Shailendra K.
Title: Antiviral activity of traditional medicinal plants from Ayurveda against SARS-CoV-2 infection
  • Cord-id: w2xfdwea
  • Document date: 2020_10_19
  • ID: w2xfdwea
    Snippet: SARS-CoV-2 is the etiological agent of COVID-19 and responsible for more than 6 million cases globally, for which no vaccine or antiviral is available. Therefore, this study was planned to investigate the antiviral role of the active constituents against spike glycoprotein of SARS-CoV-2 as well as its host ACE2 receptor. Structure-based drug design approach has been used to elucidate the antiviral activity of active constituents present in traditional medicinal plants from Ayurveda. Further, par
    Document: SARS-CoV-2 is the etiological agent of COVID-19 and responsible for more than 6 million cases globally, for which no vaccine or antiviral is available. Therefore, this study was planned to investigate the antiviral role of the active constituents against spike glycoprotein of SARS-CoV-2 as well as its host ACE2 receptor. Structure-based drug design approach has been used to elucidate the antiviral activity of active constituents present in traditional medicinal plants from Ayurveda. Further, parameters like drug-likeness, pharmacokinetics, and toxicity were determined to ensure the safety and efficacy of active constituents. Gene network analysis was performed to investigate the pathways altered during COVID-19. The prediction of drug–target interactions was performed to discover novel targets for active constituents. The results suggested that amarogentin, eufoliatorin, α-amyrin, caesalpinins, kutkin, β-sitosterol, and belladonnine are the top-ranked molecules have the highest affinity towards both the spike glycoprotein and ACE2. Most active constituents have passed the criteria of drug-likeness and demonstrated good pharmacokinetic profile with minimum predicted toxicity level. Gene network analysis confirmed that G-protein coupled receptor, protein kinase B signaling, protein secretion, peptidyl-serine phosphorylation, nuclear transport, apoptotic pathway, tumor necrosis factor, regulation of angiotensin level, positive regulation of ion transport, and membrane protein proteolysis were altered during COVID-19. The target prediction analysis revealed that most active constituents target the same pathways which are found to be altered during COVID-19. Collectively, our data encourages the use of active constituents as a potential therapy for COVID-19. However, further studies are ongoing to confirm its efficacy against disease.

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