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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.

Competing Interests: The authors declare no competing interest.

Titel:	AI-based spectroscopic monitoring of real-time interactions between SARS-CoV-2 and human ACE2.
Autor/in / Beteiligte Person:	Ye, S ; Zhang, G ; Jiang, J
Link:	Full Text Finder (Volltext)
Zeitschrift:	Proceedings of the National Academy of Sciences of the United States of America, Jg. 118 (2021-06-29), Heft 26
Veröffentlichung:	Washington, DC : National Academy of Sciences, 2021
Medientyp:	academicJournal
ISSN:	1091-6490 (electronic)
DOI:	10.1073/pnas.2025879118
Schlagwort:	Angiotensin-Converting Enzyme 2 chemistry Humans Kinetics Protein Binding Protein Structure, Secondary Spectrophotometry, Infrared Spike Glycoprotein, Coronavirus chemistry Angiotensin-Converting Enzyme 2 metabolism Machine Learning SARS-CoV-2 metabolism Spike Glycoprotein, Coronavirus metabolism
Sonstiges:	Nachgewiesen in: MEDLINE Sprachen: English Publication Type: Journal Article; Research Support, Non-U.S. Gov't Language: English [Proc Natl Acad Sci U S A] 2021 Jun 29; Vol. 118 (26). MeSH Terms: Machine Learning* ; Angiotensin-Converting Enzyme 2 / metabolism ; SARS-CoV-2 / metabolism ; Spike Glycoprotein, Coronavirus / *metabolism ; Angiotensin-Converting Enzyme 2 / chemistry ; Humans ; Kinetics ; Protein Binding ; Protein Structure, Secondary ; Spectrophotometry, Infrared ; Spike Glycoprotein, Coronavirus / chemistry References: Lancet. 2020 Feb 22;395(10224):565-574. (PMID: 32007145) ; J Phys Chem B. 2007 Sep 20;111(37):11032-46. (PMID: 17725341) ; Cell. 2020 Apr 16;181(2):281-292.e6. (PMID: 32155444) ; Proc Natl Acad Sci U S A. 1972 Oct;69(10):2788-92. (PMID: 4507602) ; Nat Chem. 2017 Jan;9(1):39-44. (PMID: 27995915) ; Intensive Care Med. 2020 Apr;46(4):586-590. (PMID: 32125455) ; Nature. 2020 May;581(7807):221-224. (PMID: 32225175) ; J Comput Chem. 2017 Jun 15;38(16):1362-1375. (PMID: 27868210) ; Science. 2020 Mar 27;367(6485):1444-1448. (PMID: 32132184) ; Cell Mol Immunol. 2020 May;17(5):536-538. (PMID: 32132669) ; Nature. 2018 Jul;559(7715):547-555. (PMID: 30046072) ; Nature. 2020 May;581(7807):215-220. (PMID: 32225176) ; In Vivo. 2016 09-10;30(5):599-604. (PMID: 27566078) ; J Comput Chem. 2005 Dec;26(16):1701-18. (PMID: 16211538) ; Nature. 2020 Mar;579(7798):270-273. (PMID: 32015507) ; Science. 2020 Mar 13;367(6483):1260-1263. (PMID: 32075877) ; J Med Virol. 2020 Jun;92(6):595-601. (PMID: 32100877) ; N Engl J Med. 2020 Feb 20;382(8):727-733. (PMID: 31978945) ; J Phys Chem A. 2005 Nov 3;109(43):9747-59. (PMID: 16833288) ; Biophys J. 2012 Sep 5;103(5):1020-7. (PMID: 23009851) ; Biomolecules. 2019 Aug 12;9(8):. (PMID: 31409012) ; Proc Natl Acad Sci U S A. 2019 Jun 11;116(24):11612-11617. (PMID: 31147467) ; Biochim Biophys Acta. 2007 Sep;1767(9):1073-101. (PMID: 17692815) ; J Phys Chem B. 2006 Feb 23;110(7):3362-74. (PMID: 16494351) ; Nature. 2018 Mar 28;555(7698):604-610. (PMID: 29595767) ; Biophys J. 2015 Apr 7;108(7):1747-1757. (PMID: 25863066) ; J Phys Chem B. 2011 Apr 7;115(13):3713-24. (PMID: 21405034) ; J Chem Phys. 2006 Jul 28;125(4):44312. (PMID: 16942147) ; Proteins. 1995 Dec;23(4):566-79. (PMID: 8749853) ; J Am Chem Soc. 2020 Nov 11;142(45):19071-19077. (PMID: 33126795) ; Cell. 2020 May 14;181(4):894-904.e9. (PMID: 32275855) ; Nature. 2020 Mar;579(7798):265-269. (PMID: 32015508) ; Science. 2020 Dec 4;370(6521):. (PMID: 33060197) Contributed Indexing: Keywords: IR spectroscopy; SARS-CoV-2; neural networks; protein dynamics Substance Nomenclature: 0 (Spike Glycoprotein, Coronavirus) ; 0 (spike protein, SARS-CoV-2) ; EC 3.4.17.23 (ACE2 protein, human) ; EC 3.4.17.23 (Angiotensin-Converting Enzyme 2) Entry Date(s): Date Created: 20210629 Date Completed: 20210708 Latest Revision: 20210717 Update Code: 20240513 PubMed Central ID: PMC8256048

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AI-based spectroscopic monitoring of real-time interactions between SARS-CoV-2 and human ACE2.