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10.1038/s41598-021-88427-w http://scihub22266oqcxt.onion/10.1038/s41598-021-88427-w 33931664!8087682!33931664     free     free     free 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       Sci+Rep 2021 ; 11 (1): 9378 Nephropedia Template TP {{tp|p=33931664|t=2021. A SARS-CoV-2 (COVID-19) biological network to find targets for drug repurposing |pdf=|usr=}}{{33931664}} gab.com Text A SARS-CoV-2 (COVID-19) biological network to find targets for drug repurposing JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=33931664 #FOAvip The Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus needs a fast recognition of effective drugs to save lives. In the COVID-19 situation, finding targets for drug repurposing can be an effective way to present new fast treatments. We have designed a two-step solution to address this approach. In the first step, we identify essential proteins from virus targets or their associated modules in human cells as possible drug target candidates. For this purpose, we apply two different algorithms to detect some candidate sets of proteins with a minimum size that drive a significant disruption in the COVID-19 related biological networks. We evaluate the resulted candidate proteins sets with three groups of drugs namely Covid-Drug, Clinical-Drug, and All-Drug. The obtained candidate proteins sets approve 16 drugs out of 18 in the Covid-Drug, 273 drugs out of 328 in the Clinical-Drug, and a large number of drugs in the All-Drug. In the second step, we study COVID-19 associated proteins sets and recognize proteins that are essential to disease pathology. This analysis is performed using DAVID to show and compare essential proteins that are contributed between the COVID-19 comorbidities. Our results for shared proteins show significant enrichment for cardiovascular-related, hypertension, diabetes type 2, kidney-related and lung-related diseases. Twit Text FOAVip A SARS-CoV-2 (COVID-19) biological network to find targets for drug repurposing ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=33931664 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33931664 #FOAvip English Wikipedia <ref>{{Cite pmid|33931664}}</ref> A SARS-CoV-2 (COVID-19) biological network to find targets for drug repurposing #MMPMID33931664 Habibi M; Taheri G; Aghdam R Sci Rep 2021[Apr]; 11 (1): 9378 PMID33931664show ga The Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus needs a fast recognition of effective drugs to save lives. In the COVID-19 situation, finding targets for drug repurposing can be an effective way to present new fast treatments. We have designed a two-step solution to address this approach. In the first step, we identify essential proteins from virus targets or their associated modules in human cells as possible drug target candidates. For this purpose, we apply two different algorithms to detect some candidate sets of proteins with a minimum size that drive a significant disruption in the COVID-19 related biological networks. We evaluate the resulted candidate proteins sets with three groups of drugs namely Covid-Drug, Clinical-Drug, and All-Drug. The obtained candidate proteins sets approve 16 drugs out of 18 in the Covid-Drug, 273 drugs out of 328 in the Clinical-Drug, and a large number of drugs in the All-Drug. In the second step, we study COVID-19 associated proteins sets and recognize proteins that are essential to disease pathology. This analysis is performed using DAVID to show and compare essential proteins that are contributed between the COVID-19 comorbidities. Our results for shared proteins show significant enrichment for cardiovascular-related, hypertension, diabetes type 2, kidney-related and lung-related diseases. |*COVID-19 Drug Treatment[MESH] |*Drug Repositioning[MESH] |*Protein Interaction Maps[MESH] |Antiviral Agents/therapeutic use[MESH] |COVID-19/metabolism[MESH] |Drug Delivery Systems[MESH] |Host-Pathogen Interactions[MESH] |Humans[MESH] |SARS-CoV-2/drug effects/physiology[MESH]A SARS-CoV-2 (COVID-19) biological network to find targets for drug re(epmc).pdf DeepDyve Pubget Overpricing