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10.1073/pnas.2025879118 http://scihub22266oqcxt.onion/10.1073/pnas.2025879118 34185681!8256048!34185681     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Proc+Natl+Acad+Sci+U+S+A 2021 ; 118 (26): ä Nephropedia Template TP {{tp|p=34185681|t=2021. AI-based spectroscopic monitoring of real-time interactions between SARS-CoV-2 and human ACE2 |pdf=|usr=}}{{34185681}} gab.com Text AI-based spectroscopic monitoring of real-time interactions between SARS-CoV-2 and human ACE2 JO: Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=34185681 #FOAvip The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), invades a human cell via human angiotensin-converting enzyme 2 (hACE2) as the entry, causing the severe coronavirus disease (COVID-19). The interactions between hACE2 and the spike glycoprotein (S protein) of SARS-CoV-2 hold the key to understanding the molecular mechanism to develop treatment and vaccines, yet the dynamic nature of these interactions in fluctuating surroundings is very challenging to probe by those structure determination techniques requiring the structures of samples to be fixed. Here we demonstrate, by a proof-of-concept simulation of infrared (IR) spectra of S protein and hACE2, that time-resolved spectroscopy may monitor the real-time structural information of the protein-protein complexes of interest, with the help of machine learning. Our machine learning protocol is able to identify fine changes in IR spectra associated with variation of the secondary structures of S protein of the coronavirus. Further, it is three to four orders of magnitude faster than conventional quantum chemistry calculations. We expect our machine learning protocol would accelerate the development of real-time spectroscopy study of protein dynamics. Twit Text FOAVip AI-based spectroscopic monitoring of real-time interactions between SARS-CoV-2 and human ACE2 ????Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=34185681 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34185681 #FOAvip English Wikipedia <ref>{{Cite pmid|34185681}}</ref> AI-based spectroscopic monitoring of real-time interactions between SARS-CoV-2 and human ACE2 #MMPMID34185681 Ye S; Zhang G; Jiang J Proc Natl Acad Sci U S A 2021[Jun]; 118 (26): ä PMID34185681show ga The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), invades a human cell via human angiotensin-converting enzyme 2 (hACE2) as the entry, causing the severe coronavirus disease (COVID-19). The interactions between hACE2 and the spike glycoprotein (S protein) of SARS-CoV-2 hold the key to understanding the molecular mechanism to develop treatment and vaccines, yet the dynamic nature of these interactions in fluctuating surroundings is very challenging to probe by those structure determination techniques requiring the structures of samples to be fixed. Here we demonstrate, by a proof-of-concept simulation of infrared (IR) spectra of S protein and hACE2, that time-resolved spectroscopy may monitor the real-time structural information of the protein-protein complexes of interest, with the help of machine learning. Our machine learning protocol is able to identify fine changes in IR spectra associated with variation of the secondary structures of S protein of the coronavirus. Further, it is three to four orders of magnitude faster than conventional quantum chemistry calculations. We expect our machine learning protocol would accelerate the development of real-time spectroscopy study of protein dynamics. |*Machine Learning[MESH] |Angiotensin-Converting Enzyme 2/chemistry/*metabolism[MESH] |Humans[MESH] |Kinetics[MESH] |Protein Binding[MESH] |Protein Structure, Secondary[MESH] |SARS-CoV-2/*metabolism[MESH] |Spectrophotometry, Infrared[MESH]AI-based spectroscopic monitoring of real-time interactions between SA(epmc).pdf DeepDyve Pubget Overpricing