Exploiting glycan topography for computational design of Env glycoprotein antigenicity
Mounting evidence suggests that glycans, rather than merely serving as a “shield”, contribute critically to antigenicity of the HIV envelope (Env) glycoprotein, representing critical antigenic determinants for many broadly neutralizing antibodies (bNAbs). While many studies have focused on defining...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
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Public Library of Science
2018
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| Online Access: | http://hdl.handle.net/1721.1/117701 https://orcid.org/0000-0002-0050-989X |
| _version_ | 1826217601365180416 |
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| author | Zhao, Peng Draghi, Monia Arevalo, Claudia Karsten, Christina B. Suscovich, Todd J. Gunn, Bronwyn Streeck, Hendrik Brass, Abraham L. Tiemeyer, Michael Seaman, Michael Mascola, John R. Wells, Lance Alter, Galit Yu, Wen-Han Lauffenburger, Douglas A |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Zhao, Peng Draghi, Monia Arevalo, Claudia Karsten, Christina B. Suscovich, Todd J. Gunn, Bronwyn Streeck, Hendrik Brass, Abraham L. Tiemeyer, Michael Seaman, Michael Mascola, John R. Wells, Lance Alter, Galit Yu, Wen-Han Lauffenburger, Douglas A |
| author_sort | Zhao, Peng |
| collection | MIT |
| description | Mounting evidence suggests that glycans, rather than merely serving as a “shield”, contribute critically to antigenicity of the HIV envelope (Env) glycoprotein, representing critical antigenic determinants for many broadly neutralizing antibodies (bNAbs). While many studies have focused on defining the role of individual glycans or groups of proximal glycans in bNAb binding, little is known about the effects of changes in the overall glycan landscape in modulating antibody access and Env antigenicity. Here we developed a systems glycobiology approach to reverse engineer the complexity of HIV glycan heterogeneity to guide antigenicity-based de novo glycoprotein design. bNAb binding was assessed against a panel of 94 recombinant gp120 monomers exhibiting defined glycan site occupancies. Using a Bayesian machine learning algorithm, bNAb-specific glycan footprints were identified and used to design antigens that selectively alter bNAb antigenicity as a proof-of concept. Our approach provides a new design strategy to predictively modulate antigenicity via the alteration of glycan topography, thereby focusing the humoral immune response on sites of viral vulnerability for HIV. |
| first_indexed | 2024-09-23T17:06:16Z |
| format | Article |
| id | mit-1721.1/117701 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T17:06:16Z |
| publishDate | 2018 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/1177012022-10-03T10:26:16Z Exploiting glycan topography for computational design of Env glycoprotein antigenicity Zhao, Peng Draghi, Monia Arevalo, Claudia Karsten, Christina B. Suscovich, Todd J. Gunn, Bronwyn Streeck, Hendrik Brass, Abraham L. Tiemeyer, Michael Seaman, Michael Mascola, John R. Wells, Lance Alter, Galit Yu, Wen-Han Lauffenburger, Douglas A Massachusetts Institute of Technology. Department of Biological Engineering Yu, Wen-Han Lauffenburger, Douglas A Mounting evidence suggests that glycans, rather than merely serving as a “shield”, contribute critically to antigenicity of the HIV envelope (Env) glycoprotein, representing critical antigenic determinants for many broadly neutralizing antibodies (bNAbs). While many studies have focused on defining the role of individual glycans or groups of proximal glycans in bNAb binding, little is known about the effects of changes in the overall glycan landscape in modulating antibody access and Env antigenicity. Here we developed a systems glycobiology approach to reverse engineer the complexity of HIV glycan heterogeneity to guide antigenicity-based de novo glycoprotein design. bNAb binding was assessed against a panel of 94 recombinant gp120 monomers exhibiting defined glycan site occupancies. Using a Bayesian machine learning algorithm, bNAb-specific glycan footprints were identified and used to design antigens that selectively alter bNAb antigenicity as a proof-of concept. Our approach provides a new design strategy to predictively modulate antigenicity via the alteration of glycan topography, thereby focusing the humoral immune response on sites of viral vulnerability for HIV. 2018-09-11T14:02:57Z 2018-09-11T14:02:57Z 2018-04 2017-05 2018-09-07T18:31:36Z Article http://purl.org/eprint/type/JournalArticle 1553-7358 1553-734X http://hdl.handle.net/1721.1/117701 Yu, Wen-Han, Peng Zhao, Monia Draghi, Claudia Arevalo, Christina B. Karsten, Todd J. Suscovich, Bronwyn Gunn, et al. “Exploiting Glycan Topography for Computational Design of Env Glycoprotein Antigenicity.” Edited by Greg Tucker-Kellogg. PLOS Computational Biology 14, 4 (April 2018): e1006093 © 2018 Public Library of Science (PLoS) https://orcid.org/0000-0002-0050-989X http://dx.doi.org/10.1371/journal.pcbi.1006093 PLOS Computational Biology Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/ application/pdf Public Library of Science PLoS |
| spellingShingle | Zhao, Peng Draghi, Monia Arevalo, Claudia Karsten, Christina B. Suscovich, Todd J. Gunn, Bronwyn Streeck, Hendrik Brass, Abraham L. Tiemeyer, Michael Seaman, Michael Mascola, John R. Wells, Lance Alter, Galit Yu, Wen-Han Lauffenburger, Douglas A Exploiting glycan topography for computational design of Env glycoprotein antigenicity |
| title | Exploiting glycan topography for computational design of Env glycoprotein antigenicity |
| title_full | Exploiting glycan topography for computational design of Env glycoprotein antigenicity |
| title_fullStr | Exploiting glycan topography for computational design of Env glycoprotein antigenicity |
| title_full_unstemmed | Exploiting glycan topography for computational design of Env glycoprotein antigenicity |
| title_short | Exploiting glycan topography for computational design of Env glycoprotein antigenicity |
| title_sort | exploiting glycan topography for computational design of env glycoprotein antigenicity |
| url | http://hdl.handle.net/1721.1/117701 https://orcid.org/0000-0002-0050-989X |
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