Paper Info
Title
Computational design of ultrashort peptide inhibitors of the receptor-binding domain of the SARS-CoV-2 S protein
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 SI5 alpha and SI5 alpha-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.
Year
DOI
Venue
2021
10.1093/bib/bbab243
BRIEFINGS IN BIOINFORMATICS
Keywords
DocType
Volume
SARS-CoV-2, peptide inhibitor, computer-aided design, molecular dynamics simulation, COVID-19
Journal
22
Issue
ISSN
Citations 
6
1467-5463
0
PageRank 
References 
Authors
0.34
0
13
Name
Order
Citations
PageRank
Pengfei Pei100.68
Hongbo Qin200.68
Jialin Chen300.68
Fengli Wang400.34
Chengzhi He500.34
Shiting He600.68
Bixia Hong700.68
Ke Liu800.34
Ren Zhong Qiao900.34
Huahao Fan1001.01
Yigang Tong1112.40
Long Chen1200.68
Shi-Zhong Luo1301.01