dc.date.accessioned | 2021-09-10T16:23:59Z | |
dc.date.available | 2021-09-10T16:23:59Z | |
dc.date.created | 2021-08-20T15:41:50Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Akbar, Rahmad Robert, Philippe Paul Auguste Pavlović, Milena Jeliazkov, Jeliazko R. Snapkov, Igor Slabodkin, Andrei Weber, Cédric R. Scheffer, Lonneke Miho, Enkelejda Haff, Ingrid Hobæk Haug, Dag Trygve Truslew Lund-Johansen, Fridtjof Safonova, Yana Sandve, Geir Kjetil Ferkingstad Greiff, Victor . A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding. Cell reports. 2021, 34:108856(11), 1-21 | |
dc.identifier.uri | http://hdl.handle.net/10852/87985 | |
dc.description.abstract | Antibody-antigen binding relies on the specific interaction of amino acids at the paratope-epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo antibody and (neo-)epitope design. A fundamental premise for the predictability of antibody-antigen binding is the existence of paratope- epitope interaction motifs that are universally shared among antibody-antigen structures. In a dataset of non-redundant antibody-antigen structures, we identify structural interaction motifs, which together compose a commonly shared structure-based vocabulary of paratope-epitope interactions. We show that this vocabulary enables the machine learnability of antibody-antigen binding on the paratope-epitope level using generative machine learning. The vocabulary (1) is compact, less than 104 motifs; (2) distinct from non-immune protein-protein interactions; and (3) mediates specific oligo- and polyreactive interactions between paratope-epitope pairs. Our work leverages combined structure- and sequence-based learning to demonstrate that machine-learning-driven predictive paratope and epitope engineering is feasible. | |
dc.language | EN | |
dc.publisher | Cell Press | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.title | A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding | |
dc.type | Journal article | |
dc.creator.author | Akbar, Rahmad | |
dc.creator.author | Robert, Philippe Paul Auguste | |
dc.creator.author | Pavlović, Milena | |
dc.creator.author | Jeliazkov, Jeliazko R. | |
dc.creator.author | Snapkov, Igor | |
dc.creator.author | Slabodkin, Andrei | |
dc.creator.author | Weber, Cédric R. | |
dc.creator.author | Scheffer, Lonneke | |
dc.creator.author | Miho, Enkelejda | |
dc.creator.author | Haff, Ingrid Hobæk | |
dc.creator.author | Haug, Dag Trygve Truslew | |
dc.creator.author | Lund-Johansen, Fridtjof | |
dc.creator.author | Safonova, Yana | |
dc.creator.author | Sandve, Geir Kjetil Ferkingstad | |
dc.creator.author | Greiff, Victor | |
cristin.unitcode | 185,53,18,12 | |
cristin.unitname | Immunologi og transfusjonsmedisin | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |
dc.identifier.cristin | 1927745 | |
dc.identifier.bibliographiccitation | info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Cell reports&rft.volume=34:108856&rft.spage=1&rft.date=2021 | |
dc.identifier.jtitle | Cell reports | |
dc.identifier.volume | 34 | |
dc.identifier.issue | 11 | |
dc.identifier.doi | https://doi.org/10.1016/j.celrep.2021.108856 | |
dc.identifier.urn | URN:NBN:no-90615 | |
dc.type.document | Tidsskriftartikkel | |
dc.type.peerreviewed | Peer reviewed | |
dc.source.issn | 2211-1247 | |
dc.identifier.fulltext | Fulltext https://www.duo.uio.no/bitstream/handle/10852/87985/2/Postnr%2B1927745_Akbar%2Bet%2Bal_Cell%2BRep_PIIS2211124721001704.pdf | |
dc.type.version | PublishedVersion | |
cristin.articleid | 108856 | |
dc.relation.project | EC/H2020/825821 | |
dc.relation.project | NFR/300740 | |
dc.relation.project | NOTUR/NORSTORE/NN9603K,NS9603K | |