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10.1080/07391102.2020.1806930 http://scihub22266oqcxt.onion/10.1080/07391102.2020.1806930 32795148!7484579!32795148     free     free     free Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 229.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 263.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 296.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 296.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 296.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 296.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Biomol+Struct+Dyn 2021 ; 39 (17): 6810-6827 Nephropedia Template TP {{tp|p=32795148|t=2021. Protein reliability analysis and virtual screening of natural inhibitors for SARS-CoV-2 main protease (M(pro)) through docking, molecular mechanic & dynamic, and ADMET profiling |pdf=|usr=}}{{32795148}} gab.com Text Protein reliability analysis and virtual screening of natural inhibitors for SARS-CoV-2 main protease (M(pro)) through docking, molecular mechanic & dynamic, and ADMET profiling JO: J Biomol Struct Dyn http://www.kidney.de/pget.php?&tw=1&pmid=32795148 #FOAvip Due to an outbreak of COVID-19, the number of research papers devoted to in-silico drug discovery of potential antiviral drugs is increasing every day exponentially. Still, there is no specific drug to prevent or treat this novel coronavirus (SARS-CoV-2) disease. Thus, the screening for a potential remedy presents a global challenge for scientists. Up to date over a hundred crystallographic structures of SARS-CoV-2 M(pro) have been deposited to Protein Data Bank. With many known proteins, the demand for a reliable target has become higher than ever, so as the choice of an efficient computational methods. Therefore, in this study comparative methods have been used for receptor-based virtual screening, targeting 9 selected structures of viral M(pro). Reliability analyses followed by re-docking of the specific co-crystallized ligand provided the best reproductivity for structures with PDB ID 6LU7, 6Y2G and 6Y2F. The influence of crystallographic water on an outcome of a virtual screening against selected targets was also investigated. Once the most reliable targets were selected, the library of easy purchasable natural compounds were retrieved from the MolPort database (10,305 compounds) and docked against the selected M(pro) proteins. To ensure the efficiency of the selected compounds, binding energies for top-15 hit ligands were calculated using Molecular Mechanics as well as their absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties were predicted. Based on predicted binding energies and toxicities, top-5 compounds were selected and subjected to Molecular Dynamics simulation and found to be stable in complex to act as possible inhibitors for SARS-CoV-2. Communicated by Ramaswamy H. Sarma. Twit Text FOAVip Protein reliability analysis and virtual screening of natural inhibitors for SARS-CoV-2 main protease (M(pro)) through docking, molecular mechanic & dynamic, and ADMET profiling ????J Biomol Struct Dyn http://www.kidney.de/pget.php?&tw=1&pmid=32795148 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32795148 #FOAvip English Wikipedia <ref>{{Cite pmid|32795148}}</ref> Protein reliability analysis and virtual screening of natural inhibitors for SARS-CoV-2 main protease (M(pro)) through docking, molecular mechanic & dynamic, and ADMET profiling #MMPMID32795148 Kapusta K; Kar S; Collins JT; Franklin LM; Kolodziejczyk W; Leszczynski J; Hill GA J Biomol Struct Dyn 2021[Oct]; 39 (17): 6810-6827 PMID32795148show ga Due to an outbreak of COVID-19, the number of research papers devoted to in-silico drug discovery of potential antiviral drugs is increasing every day exponentially. Still, there is no specific drug to prevent or treat this novel coronavirus (SARS-CoV-2) disease. Thus, the screening for a potential remedy presents a global challenge for scientists. Up to date over a hundred crystallographic structures of SARS-CoV-2 M(pro) have been deposited to Protein Data Bank. With many known proteins, the demand for a reliable target has become higher than ever, so as the choice of an efficient computational methods. Therefore, in this study comparative methods have been used for receptor-based virtual screening, targeting 9 selected structures of viral M(pro). Reliability analyses followed by re-docking of the specific co-crystallized ligand provided the best reproductivity for structures with PDB ID 6LU7, 6Y2G and 6Y2F. The influence of crystallographic water on an outcome of a virtual screening against selected targets was also investigated. Once the most reliable targets were selected, the library of easy purchasable natural compounds were retrieved from the MolPort database (10,305 compounds) and docked against the selected M(pro) proteins. To ensure the efficiency of the selected compounds, binding energies for top-15 hit ligands were calculated using Molecular Mechanics as well as their absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties were predicted. Based on predicted binding energies and toxicities, top-5 compounds were selected and subjected to Molecular Dynamics simulation and found to be stable in complex to act as possible inhibitors for SARS-CoV-2. Communicated by Ramaswamy H. Sarma. |*COVID-19[MESH] |*Molecular Dynamics Simulation[MESH] |Humans[MESH] |Molecular Docking Simulation[MESH] |Peptide Hydrolases[MESH] |Protease Inhibitors/pharmacology[MESH] |Reproducibility of Results[MESH]Protein reliability analysis and virtual screening of natural inhibito(epmc).pdf DeepDyve Pubget Overpricing