Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.15252/msb.202110260 http://scihub22266oqcxt.onion/10.15252/msb.202110260 34709707!8552660!34709707     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Mol+Syst+Biol 2021 ; 17 (11): e10260 Nephropedia Template TP {{tp|p=34709707|t=2021. Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets |pdf=|usr=}}{{34709707}} gab.com Text Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets JO: Mol Syst Biol http://www.kidney.de/pget.php?&tw=1&pmid=34709707 #FOAvip Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism targeting as a promising antiviral strategy. Twit Text FOAVip Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets ????Mol Syst Biol http://www.kidney.de/pget.php?&tw=1&pmid=34709707 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34709707 #FOAvip English Wikipedia <ref>{{Cite pmid|34709707}}</ref> Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets #MMPMID34709707 Cheng K; Martin-Sancho L; Pal LR; Pu Y; Riva L; Yin X; Sinha S; Nair NU; Chanda SK; Ruppin E Mol Syst Biol 2021[Nov]; 17 (11): e10260 PMID34709707show ga Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism targeting as a promising antiviral strategy. |*Pandemics[MESH] |Adenosine Monophosphate/*analogs & derivatives/therapeutic use[MESH] |Alanine/*analogs & derivatives/therapeutic use[MESH] |Animals[MESH] |Antiviral Agents/*therapeutic use[MESH] |COVID-19 Drug Treatment[MESH] |COVID-19/*metabolism/virology[MESH] |Caco-2 Cells[MESH] |Chlorocebus aethiops[MESH] |Datasets as Topic[MESH] |Drug Development[MESH] |Drug Repositioning[MESH] |Host-Pathogen Interactions[MESH] |Humans[MESH] |Metabolic Networks and Pathways/*genetics[MESH] |RNA, Small Interfering[MESH] |SARS-CoV-2/*physiology[MESH] |Sequence Analysis, RNA[MESH]Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic c(epmc).pdf DeepDyve Pubget Overpricing