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10.1042/BSR20202616 http://scihub22266oqcxt.onion/10.1042/BSR20202616 33624754!7982772!33624754     free     free     free Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 259.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 259.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 259.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 259.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 259.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biosci+Rep 2021 ; 41 (3): ä Nephropedia Template TP {{tp|p=33624754|t=2021. Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates |pdf=|usr=}}{{33624754}} gab.com Text Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates JO: Biosci Rep http://www.kidney.de/pget.php?&tw=1&pmid=33624754 #FOAvip Since the emergence of the new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) at the end of December 2019 in China, and with the urge of the coronavirus disease 2019 (COVID-19) pandemic, there have been huge efforts of many research teams and governmental institutions worldwide to mitigate the current scenario. Reaching more than 1,377,000 deaths in the world and still with a growing number of infections, SARS-CoV-2 remains a critical issue for global health and economic systems, with an urgency for available therapeutic options. In this scenario, as drug repurposing and discovery remains a challenge, computer-aided drug design (CADD) approaches, including machine learning (ML) techniques, can be useful tools to the design and discovery of novel potential antiviral inhibitors against SARS-CoV-2. In this work, we describe and review the current knowledge on this virus and the pandemic, the latest strategies and computational approaches applied to search for treatment options, as well as the challenges to overcome COVID-19. Twit Text FOAVip Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates ????Biosci Rep http://www.kidney.de/pget.php?&tw=1&pmid=33624754 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33624754 #FOAvip English Wikipedia <ref>{{Cite pmid|33624754}}</ref> Knowing and combating the enemy: a brief review on SARS-CoV-2 and computational approaches applied to the discovery of drug candidates #MMPMID33624754 Serafim MSM; Gertrudes JC; Costa DMA; Oliveira PR; Maltarollo VG; Honorio KM Biosci Rep 2021[Mar]; 41 (3): ä PMID33624754show ga Since the emergence of the new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) at the end of December 2019 in China, and with the urge of the coronavirus disease 2019 (COVID-19) pandemic, there have been huge efforts of many research teams and governmental institutions worldwide to mitigate the current scenario. Reaching more than 1,377,000 deaths in the world and still with a growing number of infections, SARS-CoV-2 remains a critical issue for global health and economic systems, with an urgency for available therapeutic options. In this scenario, as drug repurposing and discovery remains a challenge, computer-aided drug design (CADD) approaches, including machine learning (ML) techniques, can be useful tools to the design and discovery of novel potential antiviral inhibitors against SARS-CoV-2. In this work, we describe and review the current knowledge on this virus and the pandemic, the latest strategies and computational approaches applied to search for treatment options, as well as the challenges to overcome COVID-19. |*COVID-19 Drug Treatment[MESH] |*Drug Design[MESH] |Antiviral Agents/chemistry/*pharmacology[MESH] |Artificial Intelligence[MESH] |COVID-19/metabolism[MESH] |Drug Discovery/*methods[MESH] |Drug Repositioning[MESH] |Humans[MESH] |Molecular Docking Simulation[MESH]Knowing and combating the enemy: a brief review on SARS-CoV-2 and comp(epmc).pdf DeepDyve Pubget Overpricing