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1.
Nutrients ; 13(12)2021 Dec 16.
Article in English | MEDLINE | ID: covidwho-1580557

ABSTRACT

The excessive synthesis of interleukin-6 (IL-6) is related to cytokine storm in COVID-19 patients. Moreover, blocking IL-6 has been suggested as a treatment strategy for inflammatory diseases such as sepsis. Sepsis is a severe systemic inflammatory response syndrome with high mortality. In the present study, we investigated the anti-inflammatory and anti-septic effects and the underlying mechanisms of Dracocephalum moldavica ethanol extract (DMEE) on lipopolysaccharide (LPS)-induced inflammatory stimulation in RAW 264.7 macrophages along with septic mouse models. We found that DMEE suppressed the release of inflammatory mediators NO and PGE2 and inhibited both the mRNA and protein expression levels of iNOS and COX-2, respectively. In addition, DMEE reduced the release of proinflammatory cytokines, mainly IL-6 and IL-1ß, in RAW 264.7 cells by inhibiting the phosphorylation of JNK, ERK and p65. Furthermore, treatment with DMEE increased the survival rate and decreased the level of IL-6 in plasma in LPS-induced septic shock mice. Our findings suggest that DMEE elicits an anti-inflammatory effect in LPS-stimulated RAW 264.7 macrophages and an anti-septic effect on septic mouse model through the inhibition of the ERK/JNK/NF-κB signaling cascades and production of IL-6.


Subject(s)
Interleukin-6/metabolism , Lamiaceae/chemistry , Lipopolysaccharides/toxicity , MAP Kinase Signaling System/drug effects , Plant Extracts/pharmacology , Transcription Factor RelA/metabolism , Animals , Ethanol/chemistry , Extracellular Signal-Regulated MAP Kinases/metabolism , Inflammation/chemically induced , Inflammation/drug therapy , Inflammation/metabolism , MAP Kinase Kinase 4/metabolism , Male , Mice , Plant Extracts/chemistry , RAW 264.7 Cells
2.
J Mol Model ; 27(8): 221, 2021 Jul 08.
Article in English | MEDLINE | ID: covidwho-1300483

ABSTRACT

Natural products have served human life as medications for centuries. During the outbreak of COVID-19, a number of naturally derived compounds and extracts have been tested or used as potential remedies against COVID-19. Tetradenia riparia extract is one of the plant extracts that have been deployed and claimed to manage and control COVID-19 by some communities in Tanzania and other African countries. The active compounds isolated from T. riparia are known to possess various biological properties including antimalarial and antiviral. However, the underlying mechanism of the active compounds against SARS-CoV-2 remains unknown. Results in the present work have been interpreted from the view point of computational methods including molecular dynamics, free energy methods, and metadynamics to establish the related mechanism of action. Among the constituents of T. riparia studied, luteolin inhibited viral cell entry and was thermodynamically stable. The title compound exhibit residence time and unbinding kinetics of 68.86 ms and 0.014 /ms, respectively. The findings suggest that luteolin could be potent blocker of SARS-CoV-2 cell entry. The study shades lights towards identification of bioactive constituents from T. riparia against COVID-19, and thus bioassay can be carried out to further validate such observations.


Subject(s)
Antiviral Agents/pharmacology , COVID-19 Drug Treatment , Luteolin/pharmacology , Molecular Dynamics Simulation , Plant Extracts/pharmacology , SARS-CoV-2/drug effects , Virus Internalization/drug effects , Angiotensin-Converting Enzyme 2/metabolism , Antiviral Agents/isolation & purification , Antiviral Agents/metabolism , Binding Sites , COVID-19/virology , Host-Pathogen Interactions , Humans , Kinetics , Lamiaceae/chemistry , Luteolin/isolation & purification , Luteolin/metabolism , Plant Extracts/isolation & purification , Plant Extracts/metabolism , Protein Binding , Protein Conformation , Receptors, Virus/metabolism , SARS-CoV-2/pathogenicity , Spike Glycoprotein, Coronavirus/metabolism
3.
Curr Top Med Chem ; 20(24): 2126-2145, 2020.
Article in English | MEDLINE | ID: covidwho-648861

ABSTRACT

BACKGROUND: The emergence of a new coronavirus (CoV), named 2019-nCoV, as an outbreak originated in the city of Wuhan, China, has resulted in the death of more than 3,400 people this year alone and has caused worldwide an alarming situation, particularly following previous CoV epidemics, including the Severe Acute Respiratory Syndrome (SARS) in 2003 and the Middle East Respiratory Syndrome (MERS) in 2012. Currently, no exists for infections caused by CoVs; however, some natural products may represent potential treatment resources, such as those that contain diterpenes. OBJECTIVE: This study aimed to use computational methods to perform a virtual screening (VS) of candidate diterpenes with the potential to act as CoV inhibitors. METHODS: 1,955 diterpenes, derived from the Nepetoideae subfamily (Lamiaceae), were selected using the SistematX tool (https://sistematx.ufpb.br), which were used to make predictions. From the ChEMBL database, 3 sets of chemical structures were selected for the construction of predictive models. RESULTS: The chemical structures of molecules with known activity against SARS CoV, two of which were tested for activity against specific viral proteins and one of which was tested for activity against the virus itself, were classified according to their pIC50 values [-log IC50 (mol/l)]. CONCLUSION: In the consensus analysis approach, combining both ligand- and structure-based VSs, 19 compounds were selected as potential CoV inhibitors, including isotanshinone IIA (01), tanshinlactone (02), isocryptotanshinone (03), and tanshinketolactone (04), which did not present toxicity within the evaluated parameters.


Subject(s)
Antiviral Agents/chemistry , Antiviral Agents/pharmacology , Betacoronavirus/drug effects , Coronavirus Infections/drug therapy , Diterpenes/chemistry , Diterpenes/pharmacology , Lamiaceae/chemistry , Pneumonia, Viral/drug therapy , Antiviral Agents/pharmacokinetics , COVID-19 , Computational Biology , Diterpenes/pharmacokinetics , High-Throughput Screening Assays , Humans , Ligands , Models, Chemical , Molecular Docking Simulation , Molecular Structure , Pandemics , Predictive Value of Tests , SARS-CoV-2 , Structure-Activity Relationship
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