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dc.contributor.authorConti, Simone
dc.contributor.authorOvchinnikov, Victor
dc.contributor.authorFaris, Jonathan G
dc.contributor.authorChakraborty, Arup K
dc.contributor.authorKarplus, Martin
dc.contributor.authorSprenger, Kayla G
dc.date.accessioned2026-04-07T21:07:08Z
dc.date.available2026-04-07T21:07:08Z
dc.date.issued2022-04-22
dc.identifier.urihttps://hdl.handle.net/1721.1/165358
dc.description.abstractThe design of vaccines against highly mutable pathogens, such as HIV and influenza, requires a detailed understanding of how the adaptive immune system responds to encountering multiple variant antigens (Ags). Here, we describe a multiscale model of B cell receptor (BCR) affinity maturation that employs actual BCR nucleotide sequences and treats BCR/Ag interactions in atomistic detail. We apply the model to simulate the maturation of a broadly neutralizing Ab (bnAb) against HIV. Starting from a germline precursor sequence of the VRC01 anti-HIV Ab, we simulate BCR evolution in response to different vaccination protocols and different Ags, which were previously designed by us. The simulation results provide qualitative guidelines for future vaccine design and reveal unique insights into bnAb evolution against the CD4 binding site of HIV. Our model makes possible direct comparisons of simulated BCR populations with results of deep sequencing data, which will be explored in future applications.en_US
dc.language.isoen
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionof10.1371/journal.pcbi.1009391en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourcePublic Library of Scienceen_US
dc.titleMultiscale affinity maturation simulations to elicit broadly neutralizing antibodies against HIVen_US
dc.typeArticleen_US
dc.identifier.citationConti S, Ovchinnikov V, Faris JG, Chakraborty AK, Karplus M, Sprenger KG (2022). Multiscale affinity maturation simulations to elicit broadly neutralizing antibodies against HIV. PLoS Comput Biol 18(4): e1009391.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemical Engineeringen_US
dc.contributor.departmentInstitute for Medical Engineering and Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Physicsen_US
dc.contributor.departmentRagon Institute of MGH, MIT and Harvarden_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistryen_US
dc.relation.journalPLOS Computational Biologyen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2026-04-07T21:00:05Z
dspace.orderedauthorsConti, S; Ovchinnikov, V; Faris, JG; Chakraborty, AK; Karplus, M; Sprenger, KGen_US
dspace.date.submission2026-04-07T21:00:14Z
mit.journal.volume18en_US
mit.journal.issue4en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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