Computational Prediction of Broadly Neutralizing HIV-1 Antibody Epitopes from Neutralization Activity Data
Broadly neutralizing monoclonal antibodies effective against the majority of circulating isolates of HIV-1 have been isolated from a small number of infected individuals. Definition of the conformational epitopes on the HIV spike to which these antibodies bind is of great value in defining targets f...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | en_US |
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Public Library of Science
2014
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| Online Access: | http://hdl.handle.net/1721.1/86010 https://orcid.org/0000-0003-1268-9602 |
| _version_ | 1811077163917508608 |
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| author | Ferguson, Andrew L. Falkowska, Emilia Walker, Laura M. Seaman, Michael S. Burton, Dennis R. Chakraborty, Arup K |
| author2 | Massachusetts Institute of Technology. Institute for Medical Engineering & Science |
| author_facet | Massachusetts Institute of Technology. Institute for Medical Engineering & Science Ferguson, Andrew L. Falkowska, Emilia Walker, Laura M. Seaman, Michael S. Burton, Dennis R. Chakraborty, Arup K |
| author_sort | Ferguson, Andrew L. |
| collection | MIT |
| description | Broadly neutralizing monoclonal antibodies effective against the majority of circulating isolates of HIV-1 have been isolated from a small number of infected individuals. Definition of the conformational epitopes on the HIV spike to which these antibodies bind is of great value in defining targets for vaccine and drug design. Drawing on techniques from compressed sensing and information theory, we developed a computational methodology to predict key residues constituting the conformational epitopes on the viral spike from cross-clade neutralization activity data. Our approach does not require the availability of structural information for either the antibody or antigen. Predictions of the conformational epitopes of ten broadly neutralizing HIV-1 antibodies are shown to be in good agreement with new and existing experimental data. Our findings suggest that our approach offers a means to accelerate epitope identification for diverse pathogenic antigens. |
| first_indexed | 2024-09-23T10:38:51Z |
| format | Article |
| id | mit-1721.1/86010 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T10:38:51Z |
| publishDate | 2014 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/860102022-09-30T22:00:26Z Computational Prediction of Broadly Neutralizing HIV-1 Antibody Epitopes from Neutralization Activity Data Ferguson, Andrew L. Falkowska, Emilia Walker, Laura M. Seaman, Michael S. Burton, Dennis R. Chakraborty, Arup K Massachusetts Institute of Technology. Institute for Medical Engineering & Science Massachusetts Institute of Technology. Department of Chemical Engineering Massachusetts Institute of Technology. Department of Chemistry Massachusetts Institute of Technology. Department of Physics Ragon Institute of MGH, MIT and Harvard Chakraborty, Arup K. Broadly neutralizing monoclonal antibodies effective against the majority of circulating isolates of HIV-1 have been isolated from a small number of infected individuals. Definition of the conformational epitopes on the HIV spike to which these antibodies bind is of great value in defining targets for vaccine and drug design. Drawing on techniques from compressed sensing and information theory, we developed a computational methodology to predict key residues constituting the conformational epitopes on the viral spike from cross-clade neutralization activity data. Our approach does not require the availability of structural information for either the antibody or antigen. Predictions of the conformational epitopes of ten broadly neutralizing HIV-1 antibodies are shown to be in good agreement with new and existing experimental data. Our findings suggest that our approach offers a means to accelerate epitope identification for diverse pathogenic antigens. Massachusetts Institute of Technology. Ragon Institute of MGH, MIT and Harvard National Institutes of Health (U.S.) (Director's Pioneer Award) 2014-04-03T19:49:37Z 2014-04-03T19:49:37Z 2013-12 2013-06 Article http://purl.org/eprint/type/JournalArticle 1932-6203 http://hdl.handle.net/1721.1/86010 Ferguson, Andrew L., Emilia Falkowska, Laura M. Walker, Michael S. Seaman, Dennis R. Burton, and Arup K. Chakraborty. “Computational Prediction of Broadly Neutralizing HIV-1 Antibody Epitopes from Neutralization Activity Data.” Edited by Freddie Salsbury. PLoS ONE 8, no. 12 (December 2, 2013): e80562. https://orcid.org/0000-0003-1268-9602 en_US http://dx.doi.org/10.1371/journal.pone.0080562 PLoS ONE Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ application/pdf Public Library of Science PLoS |
| spellingShingle | Ferguson, Andrew L. Falkowska, Emilia Walker, Laura M. Seaman, Michael S. Burton, Dennis R. Chakraborty, Arup K Computational Prediction of Broadly Neutralizing HIV-1 Antibody Epitopes from Neutralization Activity Data |
| title | Computational Prediction of Broadly Neutralizing HIV-1 Antibody Epitopes from Neutralization Activity Data |
| title_full | Computational Prediction of Broadly Neutralizing HIV-1 Antibody Epitopes from Neutralization Activity Data |
| title_fullStr | Computational Prediction of Broadly Neutralizing HIV-1 Antibody Epitopes from Neutralization Activity Data |
| title_full_unstemmed | Computational Prediction of Broadly Neutralizing HIV-1 Antibody Epitopes from Neutralization Activity Data |
| title_short | Computational Prediction of Broadly Neutralizing HIV-1 Antibody Epitopes from Neutralization Activity Data |
| title_sort | computational prediction of broadly neutralizing hiv 1 antibody epitopes from neutralization activity data |
| url | http://hdl.handle.net/1721.1/86010 https://orcid.org/0000-0003-1268-9602 |
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