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10.1016/j.isci.2022.104311 http://scihub22266oqcxt.onion/10.1016/j.isci.2022.104311 35502318!9044693!35502318     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       iScience 2022 ; 25 (5): 104311 Nephropedia Template TP {{tp|p=35502318|t=2022. Synthetic lethality-based prediction of anti-SARS-CoV-2 targets |pdf=|usr=}}{{35502318}} gab.com Text Synthetic lethality-based prediction of anti-SARS-CoV-2 targets JO: iScience http://www.kidney.de/pget.php?&tw=1&pmid=35502318 #FOAvip Novel strategies are needed to identify drug targets and treatments for the COVID-19 pandemic. The altered gene expression of virus-infected host cells provides an opportunity to specifically inhibit viral propagation via targeting the synthetic lethal and synthetic dosage lethal (SL/SDL) partners of such altered host genes. Pursuing this disparate antiviral strategy, here we comprehensively analyzed multiple in vitro and in vivo bulk and single-cell RNA-sequencing datasets of SARS-CoV-2 infection to predict clinically relevant candidate antiviral targets that are SL/SDL with altered host genes. The predicted SL/SDL-based targets are highly enriched for infected cell inhibiting genes reported in four SARS-CoV-2 CRISPR-Cas9 genome-wide genetic screens. We further selected a focused subset of 26 genes that we experimentally tested in a targeted siRNA screen using human Caco-2 cells. Notably, as predicted, knocking down these targets reduced viral replication and cell viability only under the infected condition without harming noninfected healthy cells. Twit Text FOAVip Synthetic lethality-based prediction of anti-SARS-CoV-2 targets ????iScience http://www.kidney.de/pget.php?&tw=1&pmid=35502318 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35502318 #FOAvip English Wikipedia <ref>{{Cite pmid|35502318}}</ref> Synthetic lethality-based prediction of anti-SARS-CoV-2 targets #MMPMID35502318 Pal LR; Cheng K; Nair NU; Martin-Sancho L; Sinha S; Pu Y; Riva L; Yin X; Schischlik F; Lee JS; Chanda SK; Ruppin E iScience 2022[May]; 25 (5): 104311 PMID35502318show ga Novel strategies are needed to identify drug targets and treatments for the COVID-19 pandemic. The altered gene expression of virus-infected host cells provides an opportunity to specifically inhibit viral propagation via targeting the synthetic lethal and synthetic dosage lethal (SL/SDL) partners of such altered host genes. Pursuing this disparate antiviral strategy, here we comprehensively analyzed multiple in vitro and in vivo bulk and single-cell RNA-sequencing datasets of SARS-CoV-2 infection to predict clinically relevant candidate antiviral targets that are SL/SDL with altered host genes. The predicted SL/SDL-based targets are highly enriched for infected cell inhibiting genes reported in four SARS-CoV-2 CRISPR-Cas9 genome-wide genetic screens. We further selected a focused subset of 26 genes that we experimentally tested in a targeted siRNA screen using human Caco-2 cells. Notably, as predicted, knocking down these targets reduced viral replication and cell viability only under the infected condition without harming noninfected healthy cells. äSynthetic lethality-based prediction of anti-SARS-CoV-2 targets (epmc).pdf DeepDyve Pubget Overpricing