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10.1073/pnas.2010470117 http://scihub22266oqcxt.onion/10.1073/pnas.2010470117 33051297!7959488!33051297     free     free     free Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 269.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 269.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 269.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 269.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Proc+Natl+Acad+Sci+U+S+A 2020 ; 117 (44): 27381-27387 Nephropedia Template TP {{tp|p=33051297|t=2020. Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs |pdf=|usr=}}{{33051297}} gab.com Text Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs JO: Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=33051297 #FOAvip The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global crisis. There is no therapeutic treatment specific for COVID-19. It is highly desirable to identify potential antiviral agents against SARS-CoV-2 from existing drugs available for other diseases and thus repurpose them for treatment of COVID-19. In general, a drug repurposing effort for treatment of a new disease, such as COVID-19, usually starts from a virtual screening of existing drugs, followed by experimental validation, but the actual hit rate is generally rather low with traditional computational methods. Here we report a virtual screening approach with accelerated free energy perturbation-based absolute binding free energy (FEP-ABFE) predictions and its use in identifying drugs targeting SARS-CoV-2 main protease (M(pro)). The accurate FEP-ABFE predictions were based on the use of a restraint energy distribution (RED) function, making the practical FEP-ABFE-based virtual screening of the existing drug library possible. As a result, out of 25 drugs predicted, 15 were confirmed as potent inhibitors of SARS-CoV-2 M(pro) The most potent one is dipyridamole (inhibitory constant K(i) = 0.04 microM) which has shown promising therapeutic effects in subsequently conducted clinical studies for treatment of patients with COVID-19. Additionally, hydroxychloroquine (K(i) = 0.36 microM) and chloroquine (K(i) = 0.56 microM) were also found to potently inhibit SARS-CoV-2 M(pro) We anticipate that the FEP-ABFE prediction-based virtual screening approach will be useful in many other drug repurposing or discovery efforts. Twit Text FOAVip Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs ????Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=33051297 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33051297 #FOAvip English Wikipedia <ref>{{Cite pmid|33051297}}</ref> Identify potent SARS-CoV-2 main protease inhibitors via accelerated free energy perturbation-based virtual screening of existing drugs #MMPMID33051297 Li Z; Li X; Huang YY; Wu Y; Liu R; Zhou L; Lin Y; Wu D; Zhang L; Liu H; Xu X; Yu K; Zhang Y; Cui J; Zhan CG; Wang X; Luo HB Proc Natl Acad Sci U S A 2020[Nov]; 117 (44): 27381-27387 PMID33051297show ga The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global crisis. There is no therapeutic treatment specific for COVID-19. It is highly desirable to identify potential antiviral agents against SARS-CoV-2 from existing drugs available for other diseases and thus repurpose them for treatment of COVID-19. In general, a drug repurposing effort for treatment of a new disease, such as COVID-19, usually starts from a virtual screening of existing drugs, followed by experimental validation, but the actual hit rate is generally rather low with traditional computational methods. Here we report a virtual screening approach with accelerated free energy perturbation-based absolute binding free energy (FEP-ABFE) predictions and its use in identifying drugs targeting SARS-CoV-2 main protease (M(pro)). The accurate FEP-ABFE predictions were based on the use of a restraint energy distribution (RED) function, making the practical FEP-ABFE-based virtual screening of the existing drug library possible. As a result, out of 25 drugs predicted, 15 were confirmed as potent inhibitors of SARS-CoV-2 M(pro) The most potent one is dipyridamole (inhibitory constant K(i) = 0.04 microM) which has shown promising therapeutic effects in subsequently conducted clinical studies for treatment of patients with COVID-19. Additionally, hydroxychloroquine (K(i) = 0.36 microM) and chloroquine (K(i) = 0.56 microM) were also found to potently inhibit SARS-CoV-2 M(pro) We anticipate that the FEP-ABFE prediction-based virtual screening approach will be useful in many other drug repurposing or discovery efforts. |*Drug Repositioning[MESH] |Antiviral Agents/*pharmacology[MESH] |Betacoronavirus/*drug effects[MESH] |COVID-19[MESH] |Chloroquine/pharmacology[MESH] |Coronavirus 3C Proteases[MESH] |Coronavirus Infections/drug therapy[MESH] |Cysteine Endopeptidases[MESH] |Dipyridamole/pharmacology[MESH] |Humans[MESH] |Hydroxychloroquine/pharmacology[MESH] |Molecular Docking Simulation[MESH] |Molecular Structure[MESH] |Pandemics[MESH] |Pneumonia, Viral/drug therapy[MESH] |Protease Inhibitors/*pharmacology[MESH] |SARS-CoV-2[MESH]Identify potent SARS-CoV-2 main protease inhibitors via accelerated fr(epmc).pdf DeepDyve Pubget Overpricing