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10.2174/1386207323666200914094712 http://scihub22266oqcxt.onion/10.2174/1386207323666200914094712 32928086!ä!32928086 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Comb+Chem+High+Throughput+Screen 2021 ; 24 (8): 1281-1299 Nephropedia Template TP {{tp|p=32928086|t=2021. In Silico Modeling of Small Molecule Carboxamides as Inhibitors of SARS-CoV 3CL Protease: An Approach Towards Combating COVID-19 |pdf=|usr=}}{{32928086}} gab.com Text In Silico Modeling of Small Molecule Carboxamides as Inhibitors of SARS-CoV 3CL Protease: An Approach Towards Combating COVID-19 JO: Comb Chem High Throughput Screen http://www.kidney.de/pget.php?&tw=1&pmid=32928086 #FOAvip BACKGROUND: The quantitative structure-activity relationship (QSAR) approach is most widely used for the prediction of biological activity of potential medicinal compounds. A QSAR model is developed by correlating the information obtained from chemical structures (numerical descriptors/ independent variables) with the experimental response values (the dependent variable). METHODS: In the current study, we have developed a QSAR model to predict the inhibitory activity of small molecule carboxamides against severe acute respiratory syndrome coronavirus (SARS-- CoV) 3CLpro enzyme. Due to the structural similarity of this enzyme with SARS-CoV-2, the causative organism of the recent pandemic, the former may be used for the development of therapies against coronavirus disease 19 (COVID-19). RESULTS: The final multiple linear regression (MLR) model was based on four two-dimensional descriptors with definite physicochemical meaning. The model was strictly validated using different internal and external quality metrics. The model showed significant statistical quality in terms of determination coefficient (R2=0.748, adjusted R2 or R2 (adj) = 0.700), cross-validated leave-one-out Q2 (Q2=0.628) and external predicted variance R2 (pred) = 0.723. The final validated model was used for the prediction of external set compounds as well as to virtually design a new library of small molecules. We have also performed a docking analysis of the most active and least active compounds present in the dataset for comparative analysis and to explain the features obtained from the 2D-QSAR model. CONCLUSION: The derived model may be useful to predict the inhibitory activity of small molecules within the applicability domain of the model only based on the chemical structure information prior to their synthesis and testing. Twit Text FOAVip In Silico Modeling of Small Molecule Carboxamides as Inhibitors of SARS-CoV 3CL Protease: An Approach Towards Combating COVID-19 ????Comb Chem High Throughput Screen http://www.kidney.de/pget.php?&tw=1&pmid=32928086 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32928086 #FOAvip English Wikipedia <ref>{{Cite pmid|32928086}}</ref> In Silico Modeling of Small Molecule Carboxamides as Inhibitors of SARS-CoV 3CL Protease: An Approach Towards Combating COVID-19 #MMPMID32928086 Khan PM; Kumar V; Roy K Comb Chem High Throughput Screen 2021[]; 24 (8): 1281-1299 PMID32928086show ga BACKGROUND: The quantitative structure-activity relationship (QSAR) approach is most widely used for the prediction of biological activity of potential medicinal compounds. A QSAR model is developed by correlating the information obtained from chemical structures (numerical descriptors/ independent variables) with the experimental response values (the dependent variable). METHODS: In the current study, we have developed a QSAR model to predict the inhibitory activity of small molecule carboxamides against severe acute respiratory syndrome coronavirus (SARS-- CoV) 3CLpro enzyme. Due to the structural similarity of this enzyme with SARS-CoV-2, the causative organism of the recent pandemic, the former may be used for the development of therapies against coronavirus disease 19 (COVID-19). RESULTS: The final multiple linear regression (MLR) model was based on four two-dimensional descriptors with definite physicochemical meaning. The model was strictly validated using different internal and external quality metrics. The model showed significant statistical quality in terms of determination coefficient (R2=0.748, adjusted R2 or R2 (adj) = 0.700), cross-validated leave-one-out Q2 (Q2=0.628) and external predicted variance R2 (pred) = 0.723. The final validated model was used for the prediction of external set compounds as well as to virtually design a new library of small molecules. We have also performed a docking analysis of the most active and least active compounds present in the dataset for comparative analysis and to explain the features obtained from the 2D-QSAR model. CONCLUSION: The derived model may be useful to predict the inhibitory activity of small molecules within the applicability domain of the model only based on the chemical structure information prior to their synthesis and testing. |*COVID-19[MESH] |Computer Simulation[MESH] |Humans[MESH] |Molecular Docking Simulation[MESH] |Peptide Hydrolases[MESH] |Protease Inhibitors/pharmacology[MESH] |Quantitative Structure-Activity Relationship[MESH]In Silico Modeling of Small Molecule Carboxamides as Inhibitors of SAR(epmc).pdf DeepDyve Pubget Overpricing