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10.3390/molecules26041100 http://scihub22266oqcxt.onion/10.3390/molecules26041100 33669720!7923184!33669720     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       Molecules 2021 ; 26 (4): ä Nephropedia Template TP {{tp|p=33669720|t=2021. In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2 |pdf=|usr=}}{{33669720}} gab.com Text In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2 JO: Molecules http://www.kidney.de/pget.php?&tw=1&pmid=33669720 #FOAvip Coronavirus desease 2019 (COVID-19) is responsible for more than 1.80 M deaths worldwide. A Quantitative Structure-Activity Relationships (QSAR) model is developed based on experimental pIC(50) values reported for a structurally diverse dataset. A robust model with only five descriptors is found, with values of R(2) = 0.897, Q(2)(LOO) = 0.854, and Q(2)(ext) = 0.876 and complying with all the parameters established in the validation Tropsha's test. The analysis of the applicability domain (AD) reveals coverage of about 90% for the external test set. Docking and molecular dynamic analysis are performed on the three most relevant biological targets for SARS-CoV-2: main protease, papain-like protease, and RNA-dependent RNA polymerase. A screening of the DrugBank database is executed, predicting the pIC(50) value of 6664 drugs, which are IN the AD of the model (coverage = 79%). Fifty-seven possible potent anti-COVID-19 candidates with pIC(50) values > 6.6 are identified, and based on a pharmacophore modelling analysis, four compounds of this set can be suggested as potent candidates to be potential inhibitors of SARS-CoV-2. Finally, the biological activity of the compounds was related to the frontier molecular orbitals shapes. Twit Text FOAVip In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2 ????Molecules http://www.kidney.de/pget.php?&tw=1&pmid=33669720 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33669720 #FOAvip English Wikipedia <ref>{{Cite pmid|33669720}}</ref> In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2 #MMPMID33669720 Cuesta SA; Mora JR; Marquez EA Molecules 2021[Feb]; 26 (4): ä PMID33669720show ga Coronavirus desease 2019 (COVID-19) is responsible for more than 1.80 M deaths worldwide. A Quantitative Structure-Activity Relationships (QSAR) model is developed based on experimental pIC(50) values reported for a structurally diverse dataset. A robust model with only five descriptors is found, with values of R(2) = 0.897, Q(2)(LOO) = 0.854, and Q(2)(ext) = 0.876 and complying with all the parameters established in the validation Tropsha's test. The analysis of the applicability domain (AD) reveals coverage of about 90% for the external test set. Docking and molecular dynamic analysis are performed on the three most relevant biological targets for SARS-CoV-2: main protease, papain-like protease, and RNA-dependent RNA polymerase. A screening of the DrugBank database is executed, predicting the pIC(50) value of 6664 drugs, which are IN the AD of the model (coverage = 79%). Fifty-seven possible potent anti-COVID-19 candidates with pIC(50) values > 6.6 are identified, and based on a pharmacophore modelling analysis, four compounds of this set can be suggested as potent candidates to be potential inhibitors of SARS-CoV-2. Finally, the biological activity of the compounds was related to the frontier molecular orbitals shapes. |*Coronavirus 3C Proteases/antagonists & inhibitors/chemistry[MESH] |*Databases, Chemical[MESH] |*Molecular Docking Simulation[MESH] |*Molecular Dynamics Simulation[MESH] |*RNA-Dependent RNA Polymerase/antagonists & inhibitors/chemistry[MESH] |Antiviral Agents/*chemistry/therapeutic use[MESH] |COVID-19 Drug Treatment[MESH] |COVID-19/*enzymology[MESH] |Cysteine Proteinase Inhibitors/*chemistry/therapeutic use[MESH] |Drug Evaluation, Preclinical[MESH] |Quantitative Structure-Activity Relationship[MESH]In Silico Screening of the DrugBank Database to Search for Possible Dr(epmc).pdf DeepDyve Pubget Overpricing