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Computational design of ultrashort peptide inhibitors of the receptor-binding domain of the SARS-CoV-2 S protein.
Pei, Pengfei; Qin, Hongbo; Chen, Jialin; Wang, Fengli; He, Chengzhi; He, Shiting; Hong, Bixia; Liu, Ke; Qiao, Renzhong; Fan, Huahao; Tong, Yigang; Chen, Long; Luo, Shi-Zhong.
  • Pei P; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • Qin H; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • Chen J; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • Wang F; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • He C; Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing 100029, China.
  • He S; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • Hong B; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • Liu K; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • Qiao R; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • Fan H; Beijing Advanced Innovation Center for Soft Matter Science and Engineering, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • Tong Y; Beijing Advanced Innovation Center for Soft Matter Science and Engineering, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • Chen L; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • Luo SZ; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
Brief Bioinform ; 22(6)2021 11 05.
Article in English | MEDLINE | ID: covidwho-1284855
ABSTRACT
Targeting the interaction between severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2)-receptor-binding domain (RBD) and angiotensin-converting enzyme 2 (ACE2) is believed to be an effective strategy for drug design to inhibit the infection of SARS-CoV-2. Herein, several ultrashort peptidase inhibitors against the RBD-ACE2 interaction were obtained by a computer-aided approach based on the RBD-binding residues on the protease domain (PD) of ACE2. The designed peptides were tested on a model coronavirus GX_P2V, which has 92.2 and 86% amino acid identity to the SARS-CoV-2 spike protein and RBD, respectively. Molecular dynamics simulations and binding free energy analysis predicted a potential binding pocket on the RBD of the spike protein, and this was confirmed by the specifically designed peptides SI5α and SI5α-b. They have only seven residues, showing potent antiviral activity and low cytotoxicity. Enzyme-linked immunosorbent assay result also confirmed their inhibitory ability against the RBD-ACE2 interaction. The ultrashort peptides are promising precursor molecules for the drug development of Corona Virus Disease 2019, and the novel binding pocket on the RBD may be helpful for the design of RBD inhibitors or antibodies against SARS-CoV-2.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Peptides / Spike Glycoprotein, Coronavirus / Angiotensin-Converting Enzyme 2 / SARS-CoV-2 / COVID-19 Drug Treatment Type of study: Prognostic study Limits: Humans Language: English Journal subject: Biology / Medical Informatics Year: 2021 Document Type: Article Affiliation country: Bib

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Peptides / Spike Glycoprotein, Coronavirus / Angiotensin-Converting Enzyme 2 / SARS-CoV-2 / COVID-19 Drug Treatment Type of study: Prognostic study Limits: Humans Language: English Journal subject: Biology / Medical Informatics Year: 2021 Document Type: Article Affiliation country: Bib