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DFT and MD simulation investigation of favipiravir as an emerging antiviral option against viral protease (3CL^pro) of SARS-CoV-2.

ABSTRACT: As per date, around 20 million COVID-19 cases reported from across the globe due to a tiny 125 nm sized virus: SARS-CoV-2 which has created a pandemic and left an unforgettable impact on our world. Besides vaccine, medical community is in a race to identify an effective drug, which can fight against this disease effectively. Favipiravir (F) has recently attracted too much attention as an effective repurposed drug against COVID-19. In the present study, the pertinency of F has been tested as an antiviral option against viral protease (3CL^pro) of SARS-CoV-2 with the help of density functional theory (DFT) and MD Simulation. Different electronic properties of F such as atomic charges, molecular electrostatic properties (MEP), chemical reactivity and absorption analysis have been studied by DFT. In order to understand the interaction and stability of inhibitor F against viral protease, molecular docking and MD simulation have been performed. Various output like interaction energies, number of intermolecular hydrogen bonding, binding energy etc. have established the elucidate role of F for the management of CoV-2 virus for which there is no approved therapies till now. Our findings highlighted the need to further evaluate F as a potential antiviral against SARS-CoV-2.

SUBMITTER: Yadav P

PROVIDER: S-EPMC8342190 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Favipiravir: A new and emerging antiviral option in COVID-19.

Project description:With over 16 million cases reported from across the globe, the SARS-CoV-2, a mere 125 microns in diameter, has left an indelible impact on our world. With the paucity of new drugs to combat this disease, the medical community is in a race to identify repurposed drugs that may be effective against this novel coronavirus. One of the drugs which has recently garnered much attention, especially in India, is an anti-viral drug originally designed for influenza, called favipiravir. In this article, we have tried to provide a comprehensive, evidence-based review of this drug in the context of the present pandemic to elucidate its role in the management of COVID-19.

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Viral 3CLpro as a Target for Antiviral Intervention Using Milk-Derived Bioactive Peptides.

Project description:Viruses of the picornavirus-like supercluster mainly achieve cleavage of polyproteins into mature proteins through viral 3-chymotrypsin proteases (3Cpro) or 3-chymotrypsin-like proteases (3CLpro). Due to the essential role in processing viral polyproteins, 3Cpro/3CLpro is a drug target for treating viral infections. The 3CLpro is considered the main protease (Mpro) of coronaviruses. In the current study, the SARS-CoV-2 Mpro inhibitory activity of di- and tri-peptides (DTPs) resulted from the proteolysis of bovine milk proteins was evaluated. A set of 326 DTPs were obtained from virtual digestion of bovine milk major proteins. The resulted DTPs were screened using molecular docking. Twenty peptides (P1-P20) showed the best binding energies (ΔG b < - 7.0 kcal/mol). Among these 20 peptides, the top five ligands, namely P1 (RVY), P3 (QSW), P17 (DAY), P18 (QSA), and P20 (RNA), based on the highest binding affinity and the highest number of interactions with residues in the active site of Mpro were selected for further characterization by ADME/Tox analyses. For further validation of our results, molecular dynamics simulation was carried out for P3 as one of the most favorable candidates for up to 100 ns. In comparison to N3, a peptidomimetic control inhibitor, high stability was observed as supported by the calculated binding energy of the Mpro-P3 complex (- 59.48 ± 4.87 kcal/mol). Strong interactions between P3 and the Mpro active site, including four major hydrogen bonds to HIS41, ASN142, GLU166, GLN189 residues, and many hydrophobic interactions from which the interaction with CYS145 as a catalytic residue is worth mentioning. Conclusively, milk-derived bioactive peptides, especially the top five selected peptides P1, P3, P17, P18, and P20, show promise as an antiviral lead compound.Supplementary informationThe online version contains supplementary material available at 10.1007/s10989-021-10284-y.

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Potential inhibitors of SARS-CoV-2 (COVID 19) proteases PLpro and Mpro/ 3CLpro: molecular docking and simulation studies of three pertinent medicinal plant natural components.

Project description:The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) - coronavirus disease 2019 (COVID-19) has raised a severe global public health issue and creates a pandemic situation. The present work aims to study the molecular -docking and dynamic of three pertinent medicinal plants i.e. Eurycoma harmandiana, Sophora flavescens and Andrographis paniculata phyto-compounds against SARS-COV-2 papain-like protease (PLpro) and main protease (Mpro)/3-chymotrypsin-like protease (3CLpro). The interaction of protein targets and ligands was performed through AutoDock-Vina visualized using PyMOL and BIOVIA-Discovery Studio 2020. Molecular docking with canthin-6-one 9-O-beta-glucopyranoside showed highest binding affinity and less binding energy with both PLpro and Mpro/3CLpro proteases and was subjected to molecular dynamic (MD) simulations for a period of 100ns. Stability of the protein-ligand complexes was evaluated by different analyses. The binding free energy calculated using MM-PBSA and the results showed that the molecule must have stable interactions with the protein binding site. ADMET analysis of the compounds suggested that it is having drug-like properties like high gastrointestinal (GI) absorption, no blood-brain barrier permeability and high lipophilicity. The outcome revealed that canthin-6-one 9-O-beta-glucopyranoside can be used as a potential natural drug against COVID-19 protease.

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Identification of Phytochemicals from Arabian Peninsula Medicinal Plants as Strong Binders to SARS-CoV-2 Proteases (3CLPro and PLPro) by Molecular Docking and Dynamic Simulation Studies.

Project description:We provide promising computational (in silico) data on phytochemicals (compounds 1-10) from Arabian Peninsula medicinal plants as strong binders, targeting 3-chymotrypsin-like protease (3CLPro) and papain-like proteases (PLPro) of SARS-CoV-2. Compounds 1-10 followed the Lipinski rules of five (RO5) and ADMET analysis, exhibiting drug-like characters. Non-covalent (reversible) docking of compounds 1-10 demonstrated their binding with the catalytic dyad (CYS145 and HIS41) of 3CLPro and catalytic triad (CYS111, HIS272, and ASP286) of PLPro. Moreover, the implementation of the covalent (irreversible) docking protocol revealed that only compounds 7, 8, and 9 possess covalent warheads, which allowed the formation of the covalent bond with the catalytic dyad (CYS145) in 3CLPro and the catalytic triad (CYS111) in PLPro. Root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), and radius of gyration (Rg) analysis from molecular dynamic (MD) simulations revealed that complexation between ligands (compounds 7, 8, and 9) and 3CLPro and PLPro was stable, and there was less deviation of ligands. Overall, the in silico data on the inherent properties of the above phytochemicals unravel the fact that they can act as reversible inhibitors for 3CLPro and PLPro. Moreover, compounds 7, 8, and 9 also showed their novel properties to inhibit dual targets by irreversible inhibition, indicating their effectiveness for possibly developing future drugs against SARS-CoV-2. Nonetheless, to confirm the theoretical findings here, the effectiveness of the above compounds as inhibitors of 3CLPro and PLPro warrants future investigations using suitable in vitro and in vivo tests.

| S-EPMC10934083 | biostudies-literature

Virtual high throughput screening: Potential Inhibitors for SARS-CoV-2 PLPRO and 3CLPRO Proteases.

Project description:The pandemic, COVID-19, has spread worldwide and affected millions of people. There is an urgent need, therefore, to find a proper treatment for the novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative agent. This paper focuses on identifying inhibitors that target SARS-CoV-2 proteases, PLPRO and 3CLPRO, which control the duplication and manages the life cycle of SARS-CoV-2. We have carried out detailed in silico Virtual high-throughput screening using Food and Drug Administration (FDA) approved drugs from the Zinc database, COVID-19 clinical trial compounds from Pubchem database, Natural compounds from Natural Product Activity and Species Source (NPASS) database and Maybridge database against PLPRO and 3CLPRO proteases. After thoroughly analyzing the screening results, we found five compounds, Bemcentinib, Pacritinib, Ergotamine, MFCD00832476, and MFCD02180753 inhibit PLPRO and six compounds, Bemcentinib, Clofazimine, Abivertinib, Dasabuvir, MFCD00832476, Leuconicine F inhibit the 3CLPRO. These compounds are stable within the protease proteins' active sites at 20ns MD simulation. The stability is revealed by hydrogen bond formations, hydrophobic interactions, and salt bridge interactions. Our study results also reveal that the selected five compounds against PLPRO and the six compounds against 3CLPRO bind to their active sites with good binding free energy. These compounds that inhibit the activity of PLPRO and 3CLPRO may, therefore, be used for treating COVID-19 infection.

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SARS-CoV-2 main protease (3CLpro) interaction with acyclovir antiviral drug/methyl-β-cyclodextrin complex: Physiochemical characterization and molecular docking.

Project description:During the current outbreak of the novel coronavirus disease 2019 (COVID-19), researchers have examined several antiviral drugs with the potential to inhibit the proliferation of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The antiviral drug acyclovir (AVR), which is used to treat COVID-19, in complex with methyl-β-cyclodextrin (Mβ-CD) was examined in the solution and solid phases. UV-visible and fluorescence spectroscopic analyses confirmed that the guest (AVR) was included inside the host (Mβ-CD) cavity. A solid inclusion complex of AVR was prepared by co-precipitation, physical mixing, kneading, and bath sonication methods at a 1:1 ratio of Mβ-CD:AVR. The prepared Mβ-CD:AVR inclusion complex was characterized using Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and scanning electron microscopy (SEM) analysis. Phase solubility studies indicated the Mβ-CD:AVR inclusion complex exhibited a higher stability constant and linear enhancement in AVR solubility with increasing Mβ-CD concentrations. In silico analysis of the Mβ-CD/AVR inclusion complex confirmed that AVR drugs show potential as inhibitors of SARS-CoV-2 3C-like protease (3CLpro) receptors. Results obtained using the PatchDock and FireDock servers indicated that the most favorable docking ligand was Mβ-CD:AVR, which interacted with SARS-CoV-2 (3CLPro) protease inhibitors with high geometric shape complementarity scores (2522 and 5872) and atomic contact energy (-313.77 and -214.70 kcal mol-1). Our results suggest that the Mβ-CD/AVR inclusion complex inhibits the main protease of SARS-CoV-2, although further wet-lab experiments are needed to verify these findings.

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Pharmacoinformatics and molecular dynamics simulation studies reveal potential covalent and FDA-approved inhibitors of SARS-CoV-2 main protease 3CLpro.

Project description:The SARS-CoV-2 was confirmed to cause the global pandemic of coronavirus disease 2019 (COVID-19). The 3-chymotrypsin-like protease (3CLpro), an essential enzyme for viral replication, is a valid target to combat SARS-CoV and MERS-CoV. In this work, we present a structure-based study to identify potential covalent inhibitors containing a variety of chemical warheads. The targeted Asinex Focused Covalent (AFCL) library was screened based on different reaction types and potential covalent inhibitors were identified. In addition, we screened FDA-approved protease inhibitors to find candidates to be repurposed against SARS-CoV-2 3CLpro. A number of compounds with significant covalent docking scores were identified. These compounds were able to establish a covalent bond (C-S) with the reactive thiol group of Cys145 and to form favorable interactions with residues lining the substrate-binding site. Moreover, paritaprevir and simeprevir from FDA-approved protease inhibitors were identified as potential inhibitors of SARS-CoV-2 3CLpro. The mechanism and dynamic stability of binding between the identified compounds and SARS-CoV-2 3CLpro were characterized by molecular dynamics (MD) simulations. The identified compounds are potential inhibitors worthy of further development as COVID-19 drugs. Importantly, the identified FDA-approved anti-hepatitis-C virus (HCV) drugs paritaprevir and simeprevir could be ready for clinical trials to treat infected patients and help curb COVID-19. Communicated by Ramaswamy H. Sarma.

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"Identification of Nafamostat and VR23 as COVID-19 drug candidates by targeting 3CLpro and PLpro."

Project description:The sudden increase in the COVID-19 epidemic affected by novel coronavirus 2019 has jeopardized public health worldwide. Hence the necessities of a drug or therapeutic agent that heal SARS-CoV-2 infections are essential requirements. The viral genome encodes a large Polyprotein, further processed by the main protease/ 3C-like protease (3CLpro) and papain-like proteases (PLpro) into 16 nonstructural proteins to form a viral replication complex. These essential functions of 3CLpro and PLpro in virus duplication make these proteases a promising target for discovering potential therapeutic candidates and possible treatment for SARS-CoV-2 infection. This study aimed to screen a unique set of protease inhibitors library against 3CLpro and PLpro of the SARS-CoV-2. A molecular docking study was performed using PyRx to reveal the binding affinity of the selected ligands and molecular dynamic simulations were executed to assess the three-dimensional stability of protein-ligand complexes. The pharmacodynamics parameters of the inhibitors were predicted using admetSAR. The top two ligands (Nafamostat and VR23) based on docking scores were selected for further studies. Selected ligands showed excellent pharmacokinetic properties with proper absorption, bioavailability and minimal toxicity. Due to the emerging and efficiency of remdesivir and dexamethasone in healing COVID-19 patients, ADMET properties of the selected ligands were thus compared with it. MD Simulation studies up to 100 ns revealed the ligands' stability at the target proteins' binding site residues. Therefore, Nafamostat and VR23 may provide potential treatment options against SARS-CoV-2 infections by potentially inhibiting virus duplication though more research is warranted.

| S-EPMC7884051 | biostudies-literature

A Patent Review on SARS Coronavirus Main Protease (3CLpro ) Inhibitors.

Project description:The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is an unprecedented global health emergency causing more than 4.2 million fatalities as of 30 July 2021. Only three antiviral therapies have been approved or granted emergency use authorization by the FDA. The SARS-CoV-2 3CL protease (3CLpro ) is deemed an attractive drug target as it plays an essential role in viral polyprotein processing and pathogenesis, although no inhibitors have been approved. This patent review discusses SARS coronavirus 3CLpro inhibitors that have been filed up to 30 July 2021, giving an overview on the types of inhibitors that have generated commercial interest, especially amongst drug companies. Insights into the common structural motifs required for active site binding is also discussed.

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Machine learning prediction of 3CLpro SARS-CoV-2 docking scores.

Project description:Molecular docking results of two training sets containing 866 and 8,696 compounds were used to train three different machine learning (ML) approaches. Neural network approaches according to Keras and TensorFlow libraries and the gradient boosted decision trees approach of XGBoost were used with DScribe's Smooth Overlap of Atomic Positions molecular descriptors. In addition, neural networks using the SchNetPack library and descriptors were used. The ML performance was tested on three different sets, including compounds for future organic synthesis. The final evaluation of the ML predicted docking scores was based on the ZINC in vivo set, from which 1,200 compounds were randomly selected with respect to their size. The results obtained showed a consistent ML prediction capability of docking scores, and even though compounds with more than 60 atoms were found slightly overestimated they remain valid for a subsequent evaluation of their drug repurposing suitability.

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