In silico prediction of natural compounds as potential multi-target inhibitors of structural proteins of SARS-CoV-2.
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ABSTRACT:
SUBMITTER: Rani J
PROVIDER: S-EPMC8425474 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Coronavirus disease 2019 (COVID-19), resulting from infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can cause severe and fatal pneumonia along with other life-threatening complications. The COVID-19 pandemic has taken a heavy toll on the healthcare system globally and has hit the economy hard in all affected countries. As a result, there is an unmet medical need for both the prevention and treatment of COVID-19 infection. Several herbal remedies have claimed to show promising clinical results, but the mechanisms of action are not clear. We set out to identify the anti-viral natural products of these herbal remedies that presumably inhibit the life cycle of SARS-CoV-2. Particularly we chose four key SARS-CoV-2 viral enzymes as targets: Papain-like protease, Main protease, RNA dependent RNA polymerase, and 2'-O-ribose methyltransferase, which were subjected to an unbiased in silico screening against a small molecule library of 33,765 compounds originating from herbs and medicinal plants. The small molecules were then ranked based on their free energy of fitting into the "druggable" pockets on the surface of each target protein. We have analyzed the best "fit" molecules and annotated them according to their plant sources and pharmacokinetic properties. Here we present a list of potential anti-viral ingredients of herbal remedies targeting SARS-CoV-2 and explore the potential mechanisms of action of these compounds as a framework for further development of chemoprophylaxis agents against COVID-19.
| S-EPMC8310681 | biostudies-literature
Project description:The novel Coronavirus disease 2019 (COVID-19) is potentially fatal and caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Due to the unavailability of any proven treatment or vaccination, the outbreak of COVID-19 is wreaking havoc worldwide. Hence, there is an urgent need for therapeutics targeting SARS-CoV-2. Since, botanicals are an important resource for several efficacious antiviral agents, natural compounds gaining significant attention for COVID-19 treatment. In the present study, methyltranferase (MTase) of the SARS-CoV-2 is targeted using computational approach. The compounds were identified using molecular docking, virtual screening and molecular dynamics simulation studies. The binding mechanism of each compound was analyzed considering the stability and energetic parameter using in silico methods. We have found four natural antiviral compounds Amentoflavone, Baicalin, Daidzin and Luteoloside as strong inhibitors of methyltranferase of SARS-CoV-2. ADMET prediction and target analysis of the selected compounds showed favorable results. MD simulation was performed for four top-scored molecules to analyze the stability, binding mechanism and energy requirements. MD simulation studies indicated energetically favorable complex formation between MTase and the selected antiviral compounds. Furthermore, the structural effects on these substitutions were analyzed using the principles of each trajectories, which validated the interaction studies. Our analysis suggests that there is a very high probability that these compounds may have a good potential to inhibit Methyltransferase (MTase) of SARS-CoV-2 and to be used in the treatment of COVID-19. Further studies on these natural compounds may offer a quick therapeutic choice to treat COVID-19. Communicated by Ramaswamy H. Sarma.
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Project description:As an extension of our research against COVID-19, a multiphase in silico approach was applied in the selection of the three most common inhibitors (Glycyrrhizoflavone (76), Arctigenin (94), and Thiangazole (298)) against papain-like protease, PLpro (PDB ID: 4OW0), among 310 metabolites of natural origin. All compounds of the exam set were reported as antivirals. The structural similarity between the examined compound set and S88, the co-crystallized ligand of PLpro, was examined through structural similarity and fingerprint studies. The two experiments pointed to Brevicollin (28), Cryptopleurine (41), Columbamine (46), Palmatine (47), Glycyrrhizoflavone (76), Licochalcone A (87), Arctigenin (94), Termilignan (98), Anolignan B (99), 4,5-dihydroxy-6″-deoxybromotopsentin (192), Dercitin (193), Tryptanthrin (200), 6-Cyano-5-methoxy-12-methylindolo [2, 3A] carbazole (211), Thiangazole (298), and Phenoxan (300). The binding ability against PLpro was screened through molecular docking, disclosing the favorable binding modes of six metabolites. ADMET studies expected molecules 28, 76, 94, 200, and 298 as the most favorable metabolites. Then, molecules 76, 94, and 298 were chosen through in silico toxicity studies. Finally, DFT studies were carried out on glycyrrhizoflavone (76) and indicated a high level of similarity in the molecular orbital analysis. The obtained data can be used in further in vitro and in vivo studies to examine and confirm the inhibitory effect of the filtered metabolites against PLpro and SARS-CoV-2.
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Project description:In continuation of our previous effort, different in silico selection methods were applied to 310 naturally isolated metabolites that exhibited antiviral potentialities before. The applied selection methods aimed to pick the most relevant inhibitor of SARS-CoV-2 nsp10. At first, a structural similarity study against the co-crystallized ligand, S-Adenosyl Methionine (SAM), of SARS-CoV-2 nonstructural protein (nsp10) (PDB ID: 6W4H) was carried out. The similarity analysis culled 30 candidates. Secondly, a fingerprint study against SAM preferred compounds 44, 48, 85, 102, 105, 182, 220, 221, 282, 284, 285, 301, and 302. The docking studies picked 48, 182, 220, 221, and 284. While the ADMET analysis expected the likeness of the five candidates to be drugs, the toxicity study preferred compounds 48 and 182. Finally, a density-functional theory (DFT) study suggested vidarabine (182) to be the most relevant SARS-Cov-2 nsp10 inhibitor.
| S-EPMC8539059 | biostudies-literature
Project description:Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), an infectious disease that spreads rapidly in humans. In March 2020, the World Health Organization (WHO) declared a COVID-19 pandemic. Identifying a multi-target-directed ligand approach would open up new opportunities for drug discovery to combat COVID-19. The aim of this work was to perform a virtual screening of an exclusive chemical library of about 1700 molecules containing both pharmacologically active compounds and synthetic intermediates to propose potential protein inhibitors for use against SARS-CoV-2. In silico analysis showed that our compounds triggered an interaction network with key residues of the SARS-CoV-2 spike protein (S-protein), blocking trimer formation and interaction with the human receptor hACE2, as well as with the main 3C-like protease (3CLpro), inhibiting their biological function. Our data may represent a step forward in the search for potential new chemotherapeutic agents for the treatment of COVID-19.
| S-EPMC8945274 | biostudies-literature
Project description:The inhibitors of two isoforms of mitogen-activated protein kinase-interacting kinases (i.e., MNK-1 and MNK-2) are implicated in the treatment of a number of diseases including cancer. This work reports, for the first time, a multi-target (or multi-tasking) in silico modeling approach (mt-QSAR) for probing the inhibitory potential of these isoforms against MNKs. Linear and non-linear mt-QSAR classification models were set up from a large dataset of 1892 chemicals tested under a variety of assay conditions, based on the Box-Jenkins moving average approach, along with a range of feature selection algorithms and machine learning tools, out of which the most predictive one (>90% overall accuracy) was used for mechanistic interpretation of the likely inhibition of MNK-1 and MNK-2. Considering that the latter model is suitable for virtual screening of chemical libraries-i.e., commercial, non-commercial and in-house sets, it was made publicly accessible as a ready-to-use FLASK-based application. Additionally, this work employed a focused kinase library for virtual screening using an mt-QSAR model. The virtual hits identified in this process were further filtered by using a similarity search, in silico prediction of drug-likeness, and ADME profiles as well as synthetic accessibility tools. Finally, molecular dynamic simulations were carried out to identify and select the most promising virtual hits. The information gathered from this work can supply important guidelines for the discovery of novel MNK-1/2 inhibitors as potential therapeutic agents.
| S-EPMC8615736 | biostudies-literature
Project description:COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. It has six open reading frames (orf1ab, orf3a, orf6, orf7a, orf8, and orf10), a spike protein, a membrane protein, an envelope small membrane protein, and a nucleocapsid protein, out of which, orf1ab is the largest ORF coding different important non-structural proteins. In this study, an effort was made to evaluate the susceptibility of different animals against SARS-CoV-2 by analyzing the interactions of Spike and ACE2 proteins of the animals and propose a list of potential natural compounds binding to orf1ab of SARS-CoV-2. Here, we analyzed structural interactions between spike proteins of SARS-CoV-2 and the ACE2 receptor of 16 different hosts. A simulation for 50 ns was performed on these complexes. Based on post-simulation analysis, Chelonia mydas was found to have a more stable complex, while Bubalus bubalis, Aquila chrysaetos chrysaetos, Crocodylus porosus, and Loxodonta africana were found to have the least stable complexes with more fluctuations than all other organisms. Apart from that, we performed domain assignment of orf1ab of SARS-CoV-2 and identified 14 distinct domains. Out of these, Domain 3 (DNA/RNA polymerases) was selected as a target, as it showed no similarities with host proteomes and was validated in silico. Then, the top 10 molecules were selected from the virtual screening of ∼1.8 lakh molecules from the ZINC database, based on binding energy, and validated for ADME and toxicological properties. Three molecules were selected and analyzed further. The structural analysis showed that these molecules were residing within the pocket of the receptor. Finally, a simulation for 200 ns was performed on complexes with three selected molecules. Based on post-simulation analysis (RMSD, RMSF, Rg, SASA, and energies), the molecule ZINC000103666966 was found as the most suitable inhibitory compound against Domain 3. As this is an in silico prediction, further experimental studies could unravel the potential of the proposed molecule against SARS-CoV-2.
| S-EPMC9468858 | biostudies-literature
Project description:The current pandemic, caused by SARS-CoV-2 virus, is a severe challenge for human health and the world economy. There is an urgent need for development of drugs that can manage this pandemic, as it has already infected 19 million people and led to the death of around 711,277 people worldwide. At this time, in-silico studies are providing lots of preliminary data about potential drugs, which can be a great help in further in-vitro and in-vivo studies. Here, we have selected three polyphenolic compounds, mangiferin, glucogallin, and phlorizin. These compounds are isolated from different natural sources but share structural similarities and have been reported for their antiviral activity. The objective of this study is to analyze and predict the anti-protease activity of these compounds on SARS-CoV-2main protease (Mpro) and TMPRSS2 protein. Both the viral protein and the host protein play an important role in the viral life cycle, such as post-translational modification and viral spike protein priming. This study has been performed by molecular docking of the compounds using PyRx with AutoDock Vina on the two aforementioned targets chosen for this study, i.e., SARS-CoV-2 Mpro and TMPRSS2. The compounds showed good binding affinity and are further analyzed by (Molecular dynamic) MD and Molecular Mechanics Poisson-Boltzmann Surface Area MM-PBSA study. The MD-simulation study has predicted that these natural compounds will have a great impact on the stabilization of the binding cavity of the Mpro of SARS-CoV-2. The predicted pharmacokinetic parameters also show that these compounds are expected to have good solubility and absorption properties. Further predictions for these compounds also showed no involvement in drug-drug interaction and no toxicity.
| S-EPMC7587198 | biostudies-literature
Project description:Since the advent of Covid-19, several natural products have been investigated regarding their in silico interactions with SARS-CoV-2 proteases - 3CLpro and PLpro, two of the most important pharmacological targets for antiviral development. Phenylethanoid glycosides (PG) are a class of natural products present in important medicinal plants and a drug containing this group of active ingredients has been successfully used in the treatment of Covid-19 in China. Thus, a dataset with 567 derivatives of this class was built from reviews published between 1994 and 2020, and their interaction against both SARS-CoV-2 proteases was investigated. The virtual screening was performed by filtering the PGs through the evaluation of scores based on the AutoDock Vina, GOLD/ChemPLP, and GOLD/GoldScore evaluation functions. The bRO5 pharmacokinetic parameters of the PGs ranked in the previous step were analyzed and their interaction with key amino acid residues of the 3CLpro and PLpro enzymes was evaluated. Ninety-eight compounds were identified by computational approaches against PLpro and 80 PGs against 3CLpro. Of these, four interacted with key catalytic residues of PLpro, which is an indicative of inhibitory activity, and three compounds interacted with catalytic key residues of 3CLpro. Of these, five PGs occur in plants of the Traditional Chinese Medicine (TCM), while two are components of plants/formulations currently used in the Covid-19 protocols in China. The data presented here show the potential of PGs as selective inhibitors of SARS-CoV-2 3CLpro and PLpro.
| S-EPMC9920770 | biostudies-literature
Project description:The present-day world is severely suffering from the recently emerged SARS-CoV-2. The lack of prescribed drugs for the deadly virus has stressed the likely need to identify novel inhibitors to alleviate and stop the pandemic. In the present high throughput virtual screening study, we used in silico techniques like receptor-ligand docking, Molecular dynamic (MD), and ADME properties to screen natural compounds. It has been documented that many natural compounds display antiviral activities, including anti-SARS-CoV effect. The present study deals with compounds of Natural Product Activity and Species Source (NPASS) database with known biological activity that probably impedes the activity of six essential enzymes of the virus. Promising drug-like compounds were identified, demonstrating better docking score and binding energy for each druggable targets. After an extensive screening analysis, three novel multi-target natural compounds were predicted to subdue the activity of three/more major drug targets simultaneously. Concerning the utility of natural compounds in the formulation of many therapies, we propose these compounds as excellent lead candidates for the development of therapeutic drugs against SARS-CoV-2.
| S-EPMC7250083 | biostudies-literature