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10.1093/bib/bbaa155 http://scihub22266oqcxt.onion/10.1093/bib/bbaa155 32715315!7454273!32715315     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32715315&cmd=llinks): Failed to open stream: HTTP request failed! 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Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research |pdf=|usr=}}{{32715315}} gab.com Text Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research JO: Brief Bioinform http://www.kidney.de/pget.php?&tw=1&pmid=32715315 #FOAvip Given the scale and rapid spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent need for medicines that can help before vaccines are available. In this study, we present a viral-associated disease-specific chemogenomics knowledgebase (Virus-CKB) and apply our computational systems pharmacology-target mapping to rapidly predict the FDA-approved drugs which can quickly progress into clinical trials to meet the urgent demand of the COVID-19 outbreak. Virus-CKB reuses the underlying platform of our DAKB-GPCRs but adds new features like multiple-compound support, multi-cavity protein support and customizable symbol display. Our one-stop computing platform describes the chemical molecules, genes and proteins involved in viral-associated diseases regulation. To date, Virus-CKB archived 65 antiviral drugs in the market, 107 viral-related targets with 189 available 3D crystal or cryo-EM structures and 2698 chemical agents reported for these target proteins. Moreover, Virus-CKB is implemented with web applications for the prediction of the relevant protein targets and analysis and visualization of the outputs, including HTDocking, TargetHunter, BBB predictor, NGL Viewer, Spider Plot, etc. The Virus-CKB server is accessible at https://www.cbligand.org/g/virus-ckb. Twit Text FOAVip Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research ????Brief Bioinform http://www.kidney.de/pget.php?&tw=1&pmid=32715315 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32715315 #FOAvip English Wikipedia <ref>{{Cite pmid|32715315}}</ref> Virus-CKB: an integrated bioinformatics platform and analysis resource for COVID-19 research #MMPMID32715315 Feng Z; Chen M; Liang T; Shen M; Chen H; Xie XQ Brief Bioinform 2021[Mar]; 22 (2): 882-895 PMID32715315show ga Given the scale and rapid spread of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent need for medicines that can help before vaccines are available. In this study, we present a viral-associated disease-specific chemogenomics knowledgebase (Virus-CKB) and apply our computational systems pharmacology-target mapping to rapidly predict the FDA-approved drugs which can quickly progress into clinical trials to meet the urgent demand of the COVID-19 outbreak. Virus-CKB reuses the underlying platform of our DAKB-GPCRs but adds new features like multiple-compound support, multi-cavity protein support and customizable symbol display. Our one-stop computing platform describes the chemical molecules, genes and proteins involved in viral-associated diseases regulation. To date, Virus-CKB archived 65 antiviral drugs in the market, 107 viral-related targets with 189 available 3D crystal or cryo-EM structures and 2698 chemical agents reported for these target proteins. Moreover, Virus-CKB is implemented with web applications for the prediction of the relevant protein targets and analysis and visualization of the outputs, including HTDocking, TargetHunter, BBB predictor, NGL Viewer, Spider Plot, etc. The Virus-CKB server is accessible at https://www.cbligand.org/g/virus-ckb. |*Computational Biology[MESH] |Antiviral Agents/pharmacology[MESH] |COVID-19/*pathology/virology[MESH] |Drug Repositioning[MESH] |Humans[MESH] |Molecular Docking Simulation[MESH]Virus-CKB: an integrated bioinformatics platform and analysis resource(epmc).pdf DeepDyve Pubget Overpricing