PMID- 34518836
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20240214
DP  - 2021 Sep 9
TI  - The pH Effects on SARS-CoV and SARS-CoV-2 Spike Proteins in the Process of 
      Binding to hACE2.
LID - rs.3.rs-871118 [pii]
LID - 10.21203/rs.3.rs-871118/v1 [doi]
AB  - COVID-19 has been threatening human health since the late 2019, which has 
      significant impact on human health and economy. Understanding the SARS-CoV-2 and 
      other coronaviruses is important to develop effective treatments for COVID-19 and 
      other coronaviruses-caused diseases. In this work, we applied multi-scale 
      computational approaches to study the electrostatic features of spike (S) 
      proteins for SARS-CoV and SARS-CoV-2. From our results, we found thatSARS-CoV and 
      SARS-CoV-2 have similar charge distributions and electrostatic features when 
      binding with the human angiotensin-converting enzyme 2 (hACE2). The energy 
      pH-dependence calculation srevealed that the complex structures of hACE2 and the 
      S proteins of SARS-CoV/SARS-CoV-2 are stable at pH values ranging from 7.5 to 9. 
      Molecular dynamics simulations were performed using NAMD to investigate the 
      hydrogen bonds between S proteins and hACE2. From the MD simulations it was found 
      that SARS-CoV-2 has four pairsof essential hydrogenbonds (high occupancy, >80%), 
      while SARS-CoV has three pairs, which indicates the SARS-CoV-2 S protein has 
      relatively more robust binding strategy than SARS-CoVS protein.Four key residues 
      forming essential hydrogen bonds from SARS-CoV-2 are identified, which are 
      potential drug targets for COVID-19 treatments. The findings in this study shed 
      lights on the current and future treatments for COVID-19 and other 
      coronaviruses-caused diseases.
FAU - Xie, Yixin
AU  - Xie Y
AD  - Computational Science Program, University of Texas at El Paso, El Paso, TX.
FAU - Guo, Wenhan
AU  - Guo W
AD  - Computational Science Program, University of Texas at El Paso, El Paso, TX.
FAU - Lopez-Hernadez, Alan
AU  - Lopez-Hernadez A
AD  - Computational Science Program, University of Texas at El Paso, El Paso, TX.
FAU - Teng, Shaolei
AU  - Teng S
AD  - Department of Biology, Howard University, Washington, D.C.
FAU - Li, Lin
AU  - Li L
AD  - Computational Science Program, University of Texas at El Paso, El Paso, TX.
AD  - Department of Physics, University of Texas at El Paso, El Paso, TX.
LA  - eng
GR  - SC1 GM132043/GM/NIGMS NIH HHS/United States
GR  - U54 MD007592/MD/NIMHD NIH HHS/United States
GR  - U54 MD007597/MD/NIMHD NIH HHS/United States
PT  - Preprint
DEP - 20210909
PL  - United States
TA  - Res Sq
JT  - Research square
JID - 101768035
UIN - Pathogens. 2022 Feb 11;11(2):. PMID: 35215181
PMC - PMC8437318
EDAT- 2021/09/15 06:00
MHDA- 2021/09/15 06:01
PMCR- 2021/09/13
CRDT- 2021/09/14 06:51
PHST- 2021/09/14 06:51 [entrez]
PHST- 2021/09/15 06:00 [pubmed]
PHST- 2021/09/15 06:01 [medline]
PHST- 2021/09/13 00:00 [pmc-release]
AID - rs.3.rs-871118 [pii]
AID - 10.21203/rs.3.rs-871118/v1 [doi]
PST - epublish
SO  - Res Sq [Preprint]. 2021 Sep 9:rs.3.rs-871118. doi: 10.21203/rs.3.rs-871118/v1.