Computationally Designed Cyclic Peptides Derived from an Antibody Loop Increase Breadth of Binding for Influenza Variants.
Animals
Antibodies, Monoclonal
/ immunology
Antibodies, Neutralizing
/ chemistry
Binding Sites, Antibody
Complementarity Determining Regions
/ chemistry
Dogs
Drug Design
Epitopes
/ metabolism
Hemagglutinin Glycoproteins, Influenza Virus
/ chemistry
Influenza A Virus, H1N1 Subtype
/ chemistry
Madin Darby Canine Kidney Cells
Molecular Dynamics Simulation
Peptides, Cyclic
/ chemistry
Proof of Concept Study
Protein Conformation
Protein Engineering
/ methods
Workload
immunology
influenza inhibitors
peptide design
protein design
Journal
Structure (London, England : 1993)
ISSN: 1878-4186
Titre abrégé: Structure
Pays: United States
ID NLM: 101087697
Informations de publication
Date de publication:
06 10 2020
06 10 2020
Historique:
received:
19
11
2019
revised:
12
02
2020
accepted:
06
04
2020
pubmed:
2
7
2020
medline:
14
8
2021
entrez:
2
7
2020
Statut:
ppublish
Résumé
The influenza hemagglutinin (HA) glycoprotein is the target of many broadly neutralizing antibodies. However, influenza viruses can rapidly escape antibody recognition by mutation of hypervariable regions of HA that overlap with the binding epitope. We hypothesized that by designing peptides to mimic antibody loops, we could enhance breadth of binding to HA antigenic variants by reducing contact with hypervariable residues on HA that mediate escape. We designed cyclic peptides that mimic the heavy-chain complementarity-determining region 3 (CDRH3) of anti-influenza broadly neutralizing antibody C05 and show that these peptides bound to HA molecules with <100 nM affinity, comparable with that of the full-length parental C05 IgG. In addition, these peptides exhibited increased breadth of recognition to influenza H4 and H7 subtypes by eliminating clashes between the hypervariable antigenic regions and the antibody CDRH1 loop. This approach can be used to generate antibody-derived peptides against a wide variety of targets.
Identifiants
pubmed: 32610044
pii: S0969-2126(20)30124-6
doi: 10.1016/j.str.2020.04.005
pmc: PMC7544621
mid: NIHMS1585832
pii:
doi:
Substances chimiques
Antibodies, Monoclonal
0
Antibodies, Neutralizing
0
Complementarity Determining Regions
0
Epitopes
0
Hemagglutinin Glycoproteins, Influenza Virus
0
Peptides, Cyclic
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
1114-1123.e4Subventions
Organisme : NIAID NIH HHS
ID : HHSN272201400024C
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI141661
Pays : United States
Organisme : NIDDK NIH HHS
ID : F30 DK118774
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM007347
Pays : United States
Organisme : NIH HHS
ID : S10 OD023680
Pays : United States
Organisme : NIAID NIH HHS
ID : U19 AI117905
Pays : United States
Commentaires et corrections
Type : CommentIn
Informations de copyright
Copyright © 2020 Elsevier Ltd. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Interests J.E.C. has been a consultant to Valneva, has received research funding from Moderna Therapeutics and Takeda Vaccines, has been on the scientific advisory boards for Compuvax and Meissa Vaccines, and is Founder of IDBiologics. All other authors declare no conflicts of interest.
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