Computationally Designed Cyclic Peptides Derived from an Antibody Loop Increase Breadth of Binding for Influenza Variants.

Computationally Designed Cyclic Peptides Derived from an Antibody Loop Increase Breadth of Binding for Influenza Variants.
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DOI:
10.1016/j.str.2020.04.005
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发表时间:
2020-10-06
期刊:
Structure (London, England : 1993)
影响因子:
--
通讯作者:
Crowe JE Jr
Crowe JE Jr
中科院分区:
其他
文献类型:
--
作者:
Sevy AM;Gilchuk IM;Brown BP;Bozhanova NG;Nargi R;Jensen M;Meiler J;Crowe JE Jr

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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 to 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. Sevy et al. have developed a method for creating cyclic peptides from antibody loops using computational design. These peptides have broad binding activity against seasonal influenza variants and represents a new strategy for peptide discovery.
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