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Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2.
Pavlova, Anna; Zhang, Zijian; Acharya, Atanu; Lynch, Diane L; Pang, Yui Tik; Mou, Zhongyu; Parks, Jerry M; Chipot, Chris; Gumbart, James C.
  • Pavlova A; School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
  • Zhang Z; School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
  • Acharya A; School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
  • Lynch DL; School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
  • Pang YT; School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
  • Mou Z; UT/ORNL Center for Molecular Biophysics, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States.
  • Parks JM; UT/ORNL Center for Molecular Biophysics, Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States.
  • Chipot C; Université de Lorraine, UMR 7019, Laboratoire International Associé CNRS and University of Illinois at Urbana-Champaign, Vandoeuvre-lès-Nancy F-54506, France.
  • Gumbart JC; Department of Physics, University of Illinois at Urbana-Champaign, Urbana 61801-3003, Illinois, United States.
J Phys Chem Lett ; 12(23): 5494-5502, 2021 Jun 17.
Article in English | MEDLINE | ID: covidwho-1258538
Semantic information from SemMedBD (by NLM)
1. ACE2 gene|ACE2 PART_OF Homo sapiens
Subject
ACE2 gene|ACE2
Predicate
PART_OF
Object
Homo sapiens
2. complex (molecular entity) INTERACTS_WITH ACE2 gene|ACE2
Subject
complex (molecular entity)
Predicate
INTERACTS_WITH
Object
ACE2 gene|ACE2
3. ACE2 gene|ACE2 PART_OF Homo sapiens
Subject
ACE2 gene|ACE2
Predicate
PART_OF
Object
Homo sapiens
4. complex (molecular entity) INTERACTS_WITH ACE2 gene|ACE2
Subject
complex (molecular entity)
Predicate
INTERACTS_WITH
Object
ACE2 gene|ACE2
ABSTRACT
SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Herein, we have used molecular dynamics (MD) simulations, machine learning (ML), and free-energy perturbation (FEP) calculations to elucidate the differences in binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD-ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Spike Glycoprotein, Coronavirus / Machine Learning / Angiotensin-Converting Enzyme 2 Limits: Humans Language: English Journal: J Phys Chem Lett Year: 2021 Document Type: Article Affiliation country: Acs.jpclett.1c01494

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Spike Glycoprotein, Coronavirus / Machine Learning / Angiotensin-Converting Enzyme 2 Limits: Humans Language: English Journal: J Phys Chem Lett Year: 2021 Document Type: Article Affiliation country: Acs.jpclett.1c01494