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10.1021/acs.jcim.1c00159 http://scihub22266oqcxt.onion/10.1021/acs.jcim.1c00159 33829781!ä!33829781 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Chem+Inf+Model 2021 ; 61 (5): 2302-2312 Nephropedia Template TP {{tp|p=33829781|t=2021. Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV-2 Mpro |pdf=|usr=}}{{33829781}} gab.com Text Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV-2 Mpro JO: J Chem Inf Model http://www.kidney.de/pget.php?&tw=1&pmid=33829781 #FOAvip The COVID-19 pandemic has killed millions of people worldwide since its outbreak in December 2019. The pandemic is caused by the SARS-CoV-2 virus whose main protease (Mpro) is a promising drug target since it plays a key role in viral proliferation and replication. Currently, developing an effective therapy is an urgent task, which requires accurately estimating the ligand-binding free energy to SARS-CoV-2 Mpro. However, it should be noted that the accuracy of a free energy method probably depends on the protein target. A highly accurate approach for some targets may fail to produce a reasonable correlation with the experiment when a novel enzyme is considered as a drug target. Therefore, in this context, the ligand-binding affinity to SARS-CoV-2 Mpro was calculated via various approaches. The molecular docking approach was manipulated using Autodock Vina (Vina) and Autodock4 (AD4) protocols to preliminarily investigate the ligand-binding affinity and pose to SARS-CoV-2 Mpro. The binding free energy was then refined using the fast pulling of ligand (FPL), linear interaction energy (LIE), molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA), and free energy perturbation (FEP) methods. The benchmark results indicated that for docking calculations, Vina is more accurate than AD4, and for free energy methods, FEP is the most accurate method, followed by LIE, FPL, and MM-PBSA (FEP > LIE approximately FPL > MM-PBSA). Moreover, atomistic simulations revealed that the van der Waals interaction is the dominant factor. The residues Thr26, His41, Ser46, Asn142, Gly143, Cys145, His164, Glu166, and Gln189 are essential elements affecting the binding process. Our benchmark provides guidelines for further investigations using computational approaches. Twit Text FOAVip Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV-2 Mpro ????J Chem Inf Model http://www.kidney.de/pget.php?&tw=1&pmid=33829781 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33829781 #FOAvip English Wikipedia <ref>{{Cite pmid|33829781}}</ref> Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV-2 Mpro #MMPMID33829781 Ngo ST; Tam NM; Pham MQ; Nguyen TH J Chem Inf Model 2021[May]; 61 (5): 2302-2312 PMID33829781show ga The COVID-19 pandemic has killed millions of people worldwide since its outbreak in December 2019. The pandemic is caused by the SARS-CoV-2 virus whose main protease (Mpro) is a promising drug target since it plays a key role in viral proliferation and replication. Currently, developing an effective therapy is an urgent task, which requires accurately estimating the ligand-binding free energy to SARS-CoV-2 Mpro. However, it should be noted that the accuracy of a free energy method probably depends on the protein target. A highly accurate approach for some targets may fail to produce a reasonable correlation with the experiment when a novel enzyme is considered as a drug target. Therefore, in this context, the ligand-binding affinity to SARS-CoV-2 Mpro was calculated via various approaches. The molecular docking approach was manipulated using Autodock Vina (Vina) and Autodock4 (AD4) protocols to preliminarily investigate the ligand-binding affinity and pose to SARS-CoV-2 Mpro. The binding free energy was then refined using the fast pulling of ligand (FPL), linear interaction energy (LIE), molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA), and free energy perturbation (FEP) methods. The benchmark results indicated that for docking calculations, Vina is more accurate than AD4, and for free energy methods, FEP is the most accurate method, followed by LIE, FPL, and MM-PBSA (FEP > LIE approximately FPL > MM-PBSA). Moreover, atomistic simulations revealed that the van der Waals interaction is the dominant factor. The residues Thr26, His41, Ser46, Asn142, Gly143, Cys145, His164, Glu166, and Gln189 are essential elements affecting the binding process. Our benchmark provides guidelines for further investigations using computational approaches. |*COVID-19[MESH] |*Pandemics[MESH] |Benchmarking[MESH] |Humans[MESH] |Molecular Docking Simulation[MESH] |Peptide Hydrolases[MESH]Benchmark of Popular Free Energy Approaches Revealing the Inhibitors B(epmc).pdf DeepDyve Pubget Overpricing