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10.1080/07391102.2020.1776158 http://scihub22266oqcxt.onion/10.1080/07391102.2020.1776158 32544024!7309303!32544024     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Biomol+Struct+Dyn 2021 ; 39 (12): 4304-4315 Nephropedia Template TP {{tp|p=32544024|t=2021. An in silico approach for identification of novel inhibitors as potential therapeutics targeting COVID-19 main protease |pdf=|usr=}}{{32544024}} gab.com Text An in silico approach for identification of novel inhibitors as potential therapeutics targeting COVID-19 main protease JO: J Biomol Struct Dyn http://www.kidney.de/pget.php?&tw=1&pmid=32544024 #FOAvip Respiratory disease caused by a novel coronavirus, COVID-19, has been labeled a pandemic by the World Health Organization. Very little is known about the infection mechanism for this virus. More importantly, there are no drugs or vaccines that can cure or prevent a person from getting COVID-19. In this study, the binding affinity of 2692 protease inhibitor compounds that are known in the protein data bank, are calculated against the main protease of the novel coronavirus with docking and molecular dynamics (MD). Both the docking and MD methods predict the macrocyclic tissue factor-factor VIIa (PubChem ID: 118098670) inhibitor to bind strongly with the main protease with a binding affinity of -10.6 and -10.0 kcal/mol, respectively. The TF-FVIIa inhibitors are known to prevent the coagulation of blood and have antiviral activity as shown in the case of SARS coronavirus. Two more inhibitors, phenyltriazolinones (PubChem ID: 104161460) and allosteric HCV NS5B polymerase thumb pocket 2 (PubChem ID: 163632044) have shown antiviral activity and also have high affinity towards the main protease of COVID-19. Furthermore, these inhibitors interact with the catalytic dyad in the active site of the COVID-19 main protease that is especially important in viral replication. The calculated theoretical dissociation constants of the proposed COVID-19 inhibitors are found to be very similar to the experimental dissociation constant values of similar protease-inhibitor systems.Communicated by Ramaswamy H. Sarma. Twit Text FOAVip An in silico approach for identification of novel inhibitors as potential therapeutics targeting COVID-19 main protease ????J Biomol Struct Dyn http://www.kidney.de/pget.php?&tw=1&pmid=32544024 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32544024 #FOAvip English Wikipedia <ref>{{Cite pmid|32544024}}</ref> An in silico approach for identification of novel inhibitors as potential therapeutics targeting COVID-19 main protease #MMPMID32544024 Havranek B; Islam SM J Biomol Struct Dyn 2021[Aug]; 39 (12): 4304-4315 PMID32544024show ga Respiratory disease caused by a novel coronavirus, COVID-19, has been labeled a pandemic by the World Health Organization. Very little is known about the infection mechanism for this virus. More importantly, there are no drugs or vaccines that can cure or prevent a person from getting COVID-19. In this study, the binding affinity of 2692 protease inhibitor compounds that are known in the protein data bank, are calculated against the main protease of the novel coronavirus with docking and molecular dynamics (MD). Both the docking and MD methods predict the macrocyclic tissue factor-factor VIIa (PubChem ID: 118098670) inhibitor to bind strongly with the main protease with a binding affinity of -10.6 and -10.0 kcal/mol, respectively. The TF-FVIIa inhibitors are known to prevent the coagulation of blood and have antiviral activity as shown in the case of SARS coronavirus. Two more inhibitors, phenyltriazolinones (PubChem ID: 104161460) and allosteric HCV NS5B polymerase thumb pocket 2 (PubChem ID: 163632044) have shown antiviral activity and also have high affinity towards the main protease of COVID-19. Furthermore, these inhibitors interact with the catalytic dyad in the active site of the COVID-19 main protease that is especially important in viral replication. The calculated theoretical dissociation constants of the proposed COVID-19 inhibitors are found to be very similar to the experimental dissociation constant values of similar protease-inhibitor systems.Communicated by Ramaswamy H. Sarma. |*COVID-19[MESH] |Humans[MESH] |Molecular Docking Simulation[MESH] |Pandemics[MESH] |Peptide Hydrolases[MESH]An in silico approach for identification of novel inhibitors as potent(epmc).pdf DeepDyve Pubget Overpricing