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10.1021/acs.jpclett.1c01494 http://scihub22266oqcxt.onion/10.1021/acs.jpclett.1c01494 34086459!ä!34086459 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Phys+Chem+Lett 2021 ; 12 (23): 5494-5502 Nephropedia Template TP {{tp|p=34086459|t=2021. Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2 |pdf=|usr=}}{{34086459}} gab.com Text Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2 JO: J Phys Chem Lett http://www.kidney.de/pget.php?&tw=1&pmid=34086459 #FOAvip SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Herein, we have used molecular dynamics (MD) simulations, machine learning (ML), and free-energy perturbation (FEP) calculations to elucidate the differences in binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD-ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N. Twit Text FOAVip Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2 ????J Phys Chem Lett http://www.kidney.de/pget.php?&tw=1&pmid=34086459 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34086459 #FOAvip English Wikipedia <ref>{{Cite pmid|34086459}}</ref> Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2 #MMPMID34086459 Pavlova A; Zhang Z; Acharya A; Lynch DL; Pang YT; Mou Z; Parks JM; Chipot C; Gumbart JC J Phys Chem Lett 2021[Jun]; 12 (23): 5494-5502 PMID34086459show ga SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Herein, we have used molecular dynamics (MD) simulations, machine learning (ML), and free-energy perturbation (FEP) calculations to elucidate the differences in binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD-ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N. |*Machine Learning[MESH] |Angiotensin-Converting Enzyme 2/*chemistry/*metabolism[MESH] |Binding Sites[MESH] |Humans[MESH] |Models, Molecular[MESH] |Molecular Dynamics Simulation[MESH]Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spik(epmc).pdf DeepDyve Pubget Overpricing