AI-based spectroscopic monitoring of real-time interactions between SARS-CoV-2 and human ACE2.
Proc Natl Acad Sci U S A
; 118(26)2021 06 29.
Article
in English
| MEDLINE | ID: covidwho-1284759
ABSTRACT
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.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Spike Glycoprotein, Coronavirus
/
Machine Learning
/
Angiotensin-Converting Enzyme 2
/
SARS-CoV-2
Topics:
Vaccines
Limits:
Humans
Language:
English
Year:
2021
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS