PMID- 35312321
OWN - NLM
STAT- MEDLINE
DCOM- 20220412
LR  - 20220511
IS  - 1549-960X (Electronic)
IS  - 1549-9596 (Print)
IS  - 1549-9596 (Linking)
VI  - 62
IP  - 7
DP  - 2022 Apr 11
TI  - Interaction Analysis of the Spike Protein of Delta and Omicron Variants of 
      SARS-CoV-2 with hACE2 and Eight Monoclonal Antibodies Using the Fragment 
      Molecular Orbital Method.
PG  - 1771-1782
LID - 10.1021/acs.jcim.2c00100 [doi]
AB  - In the past 2 years, since the emergence of severe acute respiratory syndrome 
      coronavirus 2 (SARS-CoV-2), multiple SARS-CoV-2 variants have emerged. Whenever a 
      new variant emerges, considerable time is required to analyze the binding 
      affinity of the viral surface proteins to human angiotensin-converting enzyme 2 
      (hACE2) and monoclonal antibodies. To efficiently predict the binding affinities 
      associated with hACE2 and monoclonal antibodies in a short time, herein, we 
      propose a method applying statistical analysis to simulations performed using 
      molecular and quantum mechanics. This method efficiently predicted the trend of 
      binding affinity for the binding of the spike protein of each variant of 
      SARS-CoV-2 to hACE2 and individually to eight commercial monoclonal antibodies. 
      Additionally, this method accurately predicted interaction energy changes in the 
      crystal structure for 10 of 13 mutated residues in the Omicron variant, showing a 
      significant change in the interaction energy of hACE2. S375F was found to be a 
      mutation that majorly changed the binding affinity of the spike protein to hACE2 
      and the eight monoclonal antibodies. Our proposed analysis method enables the 
      prediction of the binding affinity of new variants to hACE2 or to monoclonal 
      antibodies in a shorter time compared to that utilized by the experimental 
      method.
FAU - Hwang, Sungbo
AU  - Hwang S
AUID- ORCID: 0000-0002-1610-5259
AD  - Department of Predictive Toxicology, Korea Institute of Toxicology, Daejeon 
      34114, Republic of Korea.
FAU - Baek, Seung-Hwa
AU  - Baek SH
AD  - Department of Predictive Toxicology, Korea Institute of Toxicology, Daejeon 
      34114, Republic of Korea.
AD  - Center for Convergent Research of Emerging Virus Infection, Korea Research 
      Institute of Chemical Technology, Daejeon 34114, Republic of Korea.
FAU - Park, Daeui
AU  - Park D
AUID- ORCID: 0000-0002-9452-5849
AD  - Department of Predictive Toxicology, Korea Institute of Toxicology, Daejeon 
      34114, Republic of Korea.
AD  - Center for Convergent Research of Emerging Virus Infection, Korea Research 
      Institute of Chemical Technology, Daejeon 34114, Republic of Korea.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20220321
PL  - United States
TA  - J Chem Inf Model
JT  - Journal of chemical information and modeling
JID - 101230060
RN  - 0 (Antibodies, Monoclonal)
RN  - 0 (Spike Glycoprotein, Coronavirus)
RN  - 0 (spike protein, SARS-CoV-2)
RN  - EC 3.4.17.23 (Angiotensin-Converting Enzyme 2)
RN  - SARS-CoV-2 variants
SB  - IM
MH  - Angiotensin-Converting Enzyme 2
MH  - Antibodies, Monoclonal/metabolism
MH  - *COVID-19
MH  - Humans
MH  - Protein Binding
MH  - SARS-CoV-2/genetics
MH  - *Spike Glycoprotein, Coronavirus/metabolism
PMC - PMC8982492
COIS- The authors declare no competing financial interest.
EDAT- 2022/03/22 06:00
MHDA- 2022/04/13 06:00
PMCR- 2022/04/13
CRDT- 2022/03/21 17:16
PHST- 2022/03/22 06:00 [pubmed]
PHST- 2022/04/13 06:00 [medline]
PHST- 2022/03/21 17:16 [entrez]
PHST- 2022/04/13 00:00 [pmc-release]
AID - 10.1021/acs.jcim.2c00100 [doi]
PST - ppublish
SO  - J Chem Inf Model. 2022 Apr 11;62(7):1771-1782. doi: 10.1021/acs.jcim.2c00100. 
      Epub 2022 Mar 21.