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10.1016/j.ejphar.2020.173779 http://scihub22266oqcxt.onion/10.1016/j.ejphar.2020.173779 33275961!7706467!33275961     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\33275961.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Eur+J+Pharmacol 2021 ; 892 (ä): 173779 Nephropedia Template TP {{tp|p=33275961|t=2021. Drug designing against NSP15 of SARS-COV2 via high throughput computational screening and structural dynamics approach |pdf=|usr=}}{{33275961}} gab.com Text Drug designing against NSP15 of SARS-COV2 via high throughput computational screening and structural dynamics approach JO: Eur J Pharmacol http://www.kidney.de/pget.php?&tw=1&pmid=33275961 #FOAvip The rapid outbreak of the COVID-19 also known as SARS-CoV2 has been declared pandemic with serious global concern. As there is no effective therapeutic against COVID-19, there is an urgent need for explicit treatment against it. The focused objective of the current study is to propose promising drug candidates against the newly identified potential therapeutic target (endonuclease, NSP15) of SARS-CoV2. NSP15 is an attractive druggable target due to its critical role in SARS-CoV2 replication and virulence in addition to interference with the host immune system. Here in the present study, we integrated the high throughput computational screening and dynamic simulation approach to identify the most promising candidate lead compound against NSP15.5-fluoro-2-oxo-1H-pyrazine-3-carboxamide (favipiravir), (3R,4R, 5R)-3,4-Bis(benzyloxy)-5-((benzyloxy) methyl) dihydrofuran-2(3H)-one) remedesivir, 1,3-thiazol-5-ylmethyl N-[(2S,3S, 5S)-3-hydroxy-5-[[(2 S)-3-methyl-2-[[methyl-[(2-propan-2-yl-1,3-thiazol-4-yl)methyl]carbamoyl]amino]butanoyl]amino]-1,6-diphenylhexan-2-yl]carbamate (ritonavir), ethyl (3R,4R, 5S)-4-acetamido-5-amino-3-pentan-3-yloxycyclohexene-1-carboxylate (oseltamivir), and (2 S)-N-[(2S,4S, 5S)-5-[[2-(2,6-dimethylphenoxy)acetyl]amino]-4-hydroxy-1,6-diphenylhexan-2-yl]-3-methyl-2-(2-oxo-1,3-diazinan-1-yl)butanamide (lopinavir) were chosen as a training set to generate the pharmacophore model. A dataset of ~140,000 compounds library was screened against the designed pharmacophore model and 10 unique compounds were selected that passed successfully through geometry constraints, Lipinski Rule of 5, and ADME/Tox filters along with a strong binding affinity for NSP15 binding cavity. The best fit compound was selected for dynamic simulation to have detailed structural features critical for binding with the NSP15 protein. Given our detailed integrative computational analysis, a Small molecule (3,3-Dimethyl-N-[4-(1-piperidinylcarbonyl) phenyl] butanamide) with drug-like properties and high binding affinity with the NSP15 is proposed as a most promising potential drug against COVID-19. The current computational integrative approach may complement high-throughput screening and the shortlisted small molecule may contribute to selective targeting of NSP15 to stop the replication of SARS-CoV2. Twit Text FOAVip Drug designing against NSP15 of SARS-COV2 via high throughput computational screening and structural dynamics approach ????Eur J Pharmacol http://www.kidney.de/pget.php?&tw=1&pmid=33275961 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33275961 #FOAvip English Wikipedia <ref>{{Cite pmid|33275961}}</ref> Drug designing against NSP15 of SARS-COV2 via high throughput computational screening and structural dynamics approach #MMPMID33275961 Batool A; Bibi N; Amin F; Kamal MA Eur J Pharmacol 2021[Feb]; 892 (ä): 173779 PMID33275961show ga The rapid outbreak of the COVID-19 also known as SARS-CoV2 has been declared pandemic with serious global concern. As there is no effective therapeutic against COVID-19, there is an urgent need for explicit treatment against it. The focused objective of the current study is to propose promising drug candidates against the newly identified potential therapeutic target (endonuclease, NSP15) of SARS-CoV2. NSP15 is an attractive druggable target due to its critical role in SARS-CoV2 replication and virulence in addition to interference with the host immune system. Here in the present study, we integrated the high throughput computational screening and dynamic simulation approach to identify the most promising candidate lead compound against NSP15.5-fluoro-2-oxo-1H-pyrazine-3-carboxamide (favipiravir), (3R,4R, 5R)-3,4-Bis(benzyloxy)-5-((benzyloxy) methyl) dihydrofuran-2(3H)-one) remedesivir, 1,3-thiazol-5-ylmethyl N-[(2S,3S, 5S)-3-hydroxy-5-[[(2 S)-3-methyl-2-[[methyl-[(2-propan-2-yl-1,3-thiazol-4-yl)methyl]carbamoyl]amino]butanoyl]amino]-1,6-diphenylhexan-2-yl]carbamate (ritonavir), ethyl (3R,4R, 5S)-4-acetamido-5-amino-3-pentan-3-yloxycyclohexene-1-carboxylate (oseltamivir), and (2 S)-N-[(2S,4S, 5S)-5-[[2-(2,6-dimethylphenoxy)acetyl]amino]-4-hydroxy-1,6-diphenylhexan-2-yl]-3-methyl-2-(2-oxo-1,3-diazinan-1-yl)butanamide (lopinavir) were chosen as a training set to generate the pharmacophore model. A dataset of ~140,000 compounds library was screened against the designed pharmacophore model and 10 unique compounds were selected that passed successfully through geometry constraints, Lipinski Rule of 5, and ADME/Tox filters along with a strong binding affinity for NSP15 binding cavity. The best fit compound was selected for dynamic simulation to have detailed structural features critical for binding with the NSP15 protein. Given our detailed integrative computational analysis, a Small molecule (3,3-Dimethyl-N-[4-(1-piperidinylcarbonyl) phenyl] butanamide) with drug-like properties and high binding affinity with the NSP15 is proposed as a most promising potential drug against COVID-19. The current computational integrative approach may complement high-throughput screening and the shortlisted small molecule may contribute to selective targeting of NSP15 to stop the replication of SARS-CoV2. |*SARS-CoV-2[MESH] |Antiviral Agents/pharmacokinetics/*pharmacology/toxicity[MESH] |Benzamides/pharmacokinetics/*pharmacology[MESH] |COVID-19/*metabolism[MESH] |Drug Design[MESH] |Endoribonucleases/chemistry/*metabolism[MESH] |High-Throughput Screening Assays[MESH] |Molecular Docking Simulation[MESH] |Molecular Dynamics Simulation[MESH] |Piperidines/pharmacokinetics/*pharmacology[MESH]Drug designing against NSP15 of SARS-COV2 via high throughput computat(epmc).pdf DeepDyve Pubget Overpricing