Potential anti-COVID-19 activity of Egyptian propolis using computational modeling
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ABSTRACT:
SUBMITTER: H Elwakil B
PROVIDER: S-EPMC7849826 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature
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Project description:Bioactive plant-derived molecules have emerged as therapeutic alternatives in the fight against the COVID-19 pandemic. In this investigation, principal bioactive compounds of the herbal infusion "horchata" from Ecuador were studied as potential novel inhibitors of the SARS-CoV-2 virus. The chemical composition of horchata was determined through a HPLC-DAD/ESI-MSn and GC-MS analysis while the inhibitory potential of the compounds on SARS-CoV-2 was determined by a computational prediction using various strategies, such as molecular docking and molecular dynamics simulations. Up to 51 different compounds were identified. The computational analysis of predicted targets reveals the compounds' possible anti-inflammatory (no steroidal) and antioxidant effects. Three compounds were identified as candidates for Mpro inhibition: benzoic acid, 2-(ethylthio)-ethyl ester, l-Leucine-N-isobutoxycarbonyl-N-methyl-heptyl and isorhamnetin and for PLpro: isorhamnetin-3-O-(6-Orhamnosyl-galactoside), dihydroxy-methoxyflavanone and dihydroxyphenyl)-5-hydroxy-4-oxochromen-7-yl]oxy-3,4,5-trihydroxyoxane-2-carboxylic acid. Our results suggest the potential of Ecuadorian horchata infusion as a starting scaffold for the development of new inhibitors of the SARS-CoV-2 Mpro and PLpro enzymes.
| S-EPMC8314115 | biostudies-literature
Project description:Propolis, a resinous material produced by honey bees from plant exudates, has long been used in traditional herbal medicine and is widely consumed as a health aid and immune system booster. The COVID-19 pandemic has renewed interest in propolis products worldwide; fortunately, various aspects of the SARS-CoV-2 infection mechanism are potential targets for propolis compounds. SARS-CoV-2 entry into host cells is characterized by viral spike protein interaction with cellular angiotensin-converting enzyme 2 (ACE2) and serine protease TMPRSS2. This mechanism involves PAK1 overexpression, which is a kinase that mediates coronavirus-induced lung inflammation, fibrosis, and immune system suppression. Propolis components have inhibitory effects on the ACE2, TMPRSS2 and PAK1 signaling pathways; in addition, antiviral activity has been proven in vitro and in vivo. In pre-clinical studies, propolis promoted immunoregulation of pro-inflammatory cytokines, including reduction in IL-6, IL-1 beta and TNF-?. This immunoregulation involves monocytes and macrophages, as well as Jak2/STAT3, NF-kB, and inflammasome pathways, reducing the risk of cytokine storm syndrome, a major mortality factor in advanced COVID-19 disease. Propolis has also shown promise as an aid in the treatment of various of the comorbidities that are particularly dangerous in COVID-19 patients, including respiratory diseases, hypertension, diabetes, and cancer. Standardized propolis products with consistent bioactive properties are now available. Given the current emergency caused by the COVID-19 pandemic and limited therapeutic options, propolis is presented as a promising and relevant therapeutic option that is safe, easy to administrate orally and is readily available as a natural supplement and functional food.
| S-EPMC7430291 | biostudies-literature
Project description:The COVID-19 pandemic has spread globally. Only three cases in Bangladesh were reported on March 8, 2020. Here, we aim to predict the epidemic progression for 1 year under different scenarios in Bangladesh. We extracted the number of daily confirmed cases from March 8 to July 20, 2020. We considered the suspected-infected-removed (SIR) model and performed a maximum likelihood-based grid search to determine the removal rate (ɣ). The transmission was modeled as a stochastic random walk process, and sequential Monte Carlo simulation was run 100 times with bootstrap fits to infer the transmission rate (β) and R t. According to the simulation, the (real) peak daily incidence of 3,600 would be followed by a steady decline, reaching below 1,000 in late January 2021. Thus, the model predicted that there would still be more than 300 cases/day even after a year. However, with proper interventions, a much steeper decline would be achieved following the peak. If we apply a combined (0.8β, 1.2ɣ) intervention, there would be less than 100 cases by mid-October, only around five odd cases at the beginning of the year 2021, and zero cases in early March 2021. The predicted total number of deaths (in status quo) after 1 year would be 8,533 which would reduce to 3,577 if combined (0.8β, 1.2ɣ) intervention is applied. We have also predicted the ideal number of tests that Bangladesh should perform and based on that redid the whole simulation. The outcome, though worse, would be manageable with interventions according to the simulation.
| S-EPMC7790066 | biostudies-literature
Project description:The ongoing pandemic of a novel coronavirus (SARS-CoV-2) leads to international concern; thus, emergency interventions need to be taken. Due to the time-consuming experimental methods for proposing useful treatments, computational approaches facilitate investigating thousands of alternatives simultaneously and narrow down the cases for experimental validation. Herein, we conducted four independent analyses for RNA interference (RNAi)-based therapy with computational and bioinformatic methods. The aim is to target the evolutionarily conserved regions in the SARS-CoV-2 genome in order to down-regulate or silence its RNA. miRNAs are denoted to play an important role in the resistance of some species to viral infections. A comprehensive analysis of the miRNAs available in the body of humans, as well as the miRNAs in bats and many other species, were done to find efficient candidates with low side effects in the human body. Moreover, the evolutionarily conserved regions in the SARS-CoV-2 genome were considered for designing novel significant siRNA that are target-specific. A small set of miRNAs and five siRNAs were suggested as the possible efficient candidates with a high affinity to the SARS-CoV-2 genome and low side effects. The suggested candidates are promising therapeutics for the experimental evaluations and may speed up the procedure of treatment design. Materials and implementations are available at: https://github.com/nrohani/SARS-CoV-2.
| S-EPMC7919535 | biostudies-literature
Project description:Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has become a global health emergency. Although new vaccines have been generated and being implicated, discovery and application of novel preventive and control measures are warranted. We aimed to identify compounds that may possess the potential to either block the entry of virus to host cells or attenuate its replication upon infection. Using host cell surface receptor expression (angiotensin-converting enzyme 2 (ACE2) and Transmembrane protease serine 2 (TMPRSS2)) analysis as an assay, we earlier screened several synthetic and natural compounds and identified candidates that showed ability to down-regulate their expression. Here, we report experimental and computational analyses of two small molecules, Mortaparib and MortaparibPlus that were initially identified as dual novel inhibitors of mortalin and PARP-1, for their activity against SARS-CoV-2. In silico analyses showed that MortaparibPlus, but not Mortaparib, stably binds into the catalytic pocket of TMPRSS2. In vitro analysis of control and treated cells revealed that MortaparibPlus caused down-regulation of ACE2 and TMPRSS2; Mortaparib did not show any effect. Furthermore, computational analysis on SARS-CoV-2 main protease (Mpro) that also predicted the inhibitory activity of MortaparibPlus. However, cell-based antiviral drug screening assay showed 30-60% viral inhibition in cells treated with non-toxic doses of either MortaparibPlus or Mortaparib. The data suggest that these two closely related compounds possess multimodal anti-COVID-19 activities. Whereas MortaparibPlus works through direct interactions/effects on the host cell surface receptors (ACE2 and TMPRSS2) and the virus protein (Mpro), Mortaparib involves independent mechanisms, elucidation of which warrants further studies.
| S-EPMC8527209 | biostudies-literature
Project description:A compound that could inhibit multiple targets associated with SARS-CoV-2 infection would prove to be a drug of choice against the virus. Human receptor-ACE2, receptor binding domain (RBD) of SARS-CoV-2 S-protein, Papain-like protein of SARS-CoV-2 (PLpro), reverse transcriptase of SARS-CoV-2 (RdRp) were chosen for in silico study. A set of previously synthesized compounds (1-5) were docked into the active sites of the targets. Based on the docking score, ligand efficiency, binding free energy, and dissociation constants for a definite conformational position of the ligand, inhibitory potentials of the compounds were measured. The stability of the protein-ligand (P-L) complex was validated in silico by using molecular dynamics simulations using the YASARA suit. Moreover, the pharmacokinetic properties, FMO and NBO analysis were performed for ranking the potentiality of the compounds as drug. The geometry optimizations and electronic structures were investigated using DFT. As per the study, compound-5 has the best binding affinity against all four targets. Moreover, compounds 1, 3 and 5 are less toxic and can be considered for oral consumption.
| S-EPMC9101701 | biostudies-literature
Project description:Vaccines have made gratifying progress in preventing the 2019 coronavirus disease (COVID-19) pandemic. However, the emergence of variants, especially the latest delta variant, has brought considerable challenges to human health. Hence, the development of robust therapeutic approaches, such as anti-COVID-19 drug design, could aid in managing the pandemic more efficiently. Some drug design strategies have been successfully applied during the COVID-19 pandemic to create and validate related lead drugs. The computational drug design methods used for COVID-19 can be roughly divided into (i) structure-based approaches and (ii) artificial intelligence (AI)-based approaches. Structure-based approaches investigate different molecular fragments and functional groups through lead drugs and apply relevant tools to produce antiviral drugs. AI-based approaches usually use end-to-end learning to explore a larger biochemical space to design antiviral drugs. This review provides an overview of the two design strategies of anti-COVID-19 drugs, the advantages and disadvantages of these strategies and discussions of future developments.
| S-EPMC8690229 | biostudies-literature
Project description:IntroductionDespite all the efforts to treat COVID-19, no particular cure has been found for this virus. Since developing antiviral drugs is a time-consuming process, the most effective approach is to evaluate the approved and under investigation drugs using in silico methods. Among the different targets within the virus structure, as a vital component in the life cycle of coronaviruses, RNA-dependent RNA polymerase (RdRP) can be a critical target for antiviral drugs. The impact of the existence of RNA in the enzyme structure on the binding affinity of anti-RdRP drugs has not been investigated so far.MethodsIn this study, the potential anti-RdRP effects of a variety of drugs from two databases (Zinc database and DrugBank) were evaluated using molecular docking. For this purpose, the newly emerged model of COVID-19 (RdRP) post-translocated catalytic complex (PDB ID: 7BZF) that consists of RNA was chosen as the target.ResultsThe results indicated that idarubicin (IDR), a member of the anthracycline antibiotic family, and fenoterol (FNT), a known beta-2 adrenergic agonist drug, tightly bind to the target enzyme and could be used as potential anti-RdRP inhibitors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). These outcomes revealed that due to the ligand-protein interactions, the presence of RNA in this structure could remarkably affect the binding affinity of inhibitor compounds.ConclusionIn silico approaches, such as molecular docking, could effectively address the problem of finding appropriate treatment for COVID-19. Our results showed that IDR and FNT have a significant affinity to the RdRP of SARS-CoV-2; therefore, these drugs are remarkable inhibitors of coronaviruses.
| S-EPMC7895701 | biostudies-literature
Project description:With the gradual increase in the COVID-19 mortality rate, there is an urgent need for an effective drug/vaccine. Several drugs like Remdesivir, Azithromycin, Favirapir, Ritonavir, Darunavir, etc., are put under evaluation in more than 300 clinical trials to treat COVID-19. On the other hand, several vaccines like Pfizer-BioNTech, Moderna, Johnson & Johnson's Janssen, Sputnik V, Covishield, Covaxin, etc., also evolved from the research study. While few of them already gets approved, others show encouraging results and are still under assessment. In parallel, there are also significant developments in new drug development. But, since the approval of new molecules takes substantial time, drug repurposing studies have also gained considerable momentum. The primary agent of the disease progression of COVID-19 is SARS-CoV2/nCoV, which is believed to have ~89% genetic resemblance with SARS-CoV, a coronavirus responsible for the massive outbreak in 2003. With this hypothesis, Human-SARS-CoV protein interactions are used to develop an in-silico Human-nCoV network by identifying potential COVID-19 human spreader proteins by applying the SIS model and fuzzy thresholding by a possible COVID-19 FDA drugs target-based validation. At first, the complete list of FDA drugs is identified for the level-1 and level-2 spreader proteins in this network, followed by applying a drug consensus scoring strategy. The same consensus strategy is involved in the second analysis but on a curated overlapping set of key genes/proteins identified from COVID-19 symptoms. Validation using subsequent docking study has also been performed on COVID-19 potential drugs with the available major COVID-19 crystal structures whose PDB IDs are: 6LU7, 6M2Q, 6W9C, 6M0J, 6M71 and 6VXX. Our computational study and docking results suggest that Fostamatinib (R406 as its active promoiety) may also be considered as one of the potential candidates for further clinical trials in pursuit to counter the spread of COVID-19.
| S-EPMC8390099 | biostudies-literature
Project description:Human tuberculosis (TB), caused by Mycobacterium tuberculosis, is the leading bacterial killer disease worldwide and new anti-TB drugs are urgently needed. Natural remedies have long played an important role in medicine and continue to provide some inspiring templates for drug design. Propolis, a substance naturally-produced by bees upon collection of plant resins, is used in folk medicine for its beneficial anti-TB activity. In this study, we used a molecular docking approach to investigate the interactions between selected propolis constituents and four 'druggable' proteins involved in vital physiological functions in M. tuberculosis, namely MtPanK, MtDprE1, MtPknB and MtKasA. The docking score for ligands towards each protein was calculated to estimate the binding free energy, with the best docking score (lowest energy value) indicating the highest predicted ligand/protein affinity. Specific interactions were also explored to understand the nature of intermolecular bonds between the most active ligands and the protein binding site residues. The lignan (+)-sesamin displayed the best docking score towards MtDprE1 (-10.7?kcal/mol) while the prenylated flavonoid isonymphaeol D docked strongly with MtKasA (-9.7?kcal/mol). Both compounds showed docking scores superior to the control inhibitors and represent potentially interesting scaffolds for further in vitro biological evaluation and anti-TB drug design.
| S-EPMC6095843 | biostudies-literature