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Computational Design of ACE2-Based Peptide Inhibitors of SARS-CoV-2.
Han, Yanxiao; Král, Petr.
  • Han Y; Department of Chemistry, University of Illinois at Chicago, Chicago, Illinois 60607, United States.
  • Král P; Department of Chemistry, University of Illinois at Chicago, Chicago, Illinois 60607, United States.
ACS Nano ; 14(4): 5143-5147, 2020 04 28.
Article in English | MEDLINE | ID: covidwho-52399
ABSTRACT
Peptide inhibitors against the SARS-CoV-2 coronavirus, currently causing a worldwide pandemic, are designed and simulated. The inhibitors are mostly formed by two sequential self-supporting α-helices (bundle) extracted from the protease domain (PD) of angiotensin-converting enzyme 2 (ACE2), which bind to the SARS-CoV-2 receptor binding domains. Molecular dynamics simulations revealed that the α-helical peptides maintain their secondary structure and provide a highly specific and stable binding (blocking) to SARS-CoV-2. To provide a multivalent binding to the SARS-CoV-2 receptors, many such peptides could be attached to the surfaces of nanoparticle carriers. The proposed peptide inhibitors could provide simple and efficient therapeutics against the COVID-19 disease.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Peptides / Pneumonia, Viral / Drug Design / Coronavirus Infections / Peptidyl-Dipeptidase A / Molecular Dynamics Simulation / Betacoronavirus / Computational Chemistry Limits: Humans Language: English Journal: ACS Nano Year: 2020 Document Type: Article Affiliation country: Acsnano.0c02857

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Peptides / Pneumonia, Viral / Drug Design / Coronavirus Infections / Peptidyl-Dipeptidase A / Molecular Dynamics Simulation / Betacoronavirus / Computational Chemistry Limits: Humans Language: English Journal: ACS Nano Year: 2020 Document Type: Article Affiliation country: Acsnano.0c02857