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dc.contributor.authorQuartararo, Anthony James
dc.contributor.authorGates, Zachary P
dc.contributor.authorSomsen, Bente A.
dc.contributor.authorHartrampf, Nina
dc.contributor.authorYe, Xiyun
dc.contributor.authorShimada, Arisa
dc.contributor.authorKajihara, Yasuhiro
dc.contributor.authorOttmann, Christian
dc.contributor.authorPentelute, Bradley L.
dc.date.accessioned2020-10-27T20:18:24Z
dc.date.available2020-10-27T20:18:24Z
dc.date.issued2020-06
dc.date.submitted2019-12
dc.identifier.issn2041-1723
dc.identifier.urihttps://hdl.handle.net/1721.1/128217
dc.description.abstractHigh-diversity genetically-encoded combinatorial libraries (108−1013 members) are a rich source of peptide-based binding molecules, identified by affinity selection. Synthetic libraries can access broader chemical space, but typically examine only ~ 106 compounds by screening. Here we show that in-solution affinity selection can be interfaced with nano-liquid chromatography-tandem mass spectrometry peptide sequencing to identify binders from fully randomized synthetic libraries of 108 members—a 100-fold gain in diversity over standard practice. To validate this approach, we show that binders to a monoclonal antibody are identified in proportion to library diversity, as diversity is increased from 106–108. These results are then applied to the discovery of p53-like binders to MDM2, and to a family of 3–19 nM-affinity, α/β-peptide-based binders to 14-3-3. An X-ray structure of one of these binders in complex with 14-3-3σ is determined, illustrating the role of β-amino acids in facilitating a key binding contact.en_US
dc.description.sponsorshipNIH/NIGMS (Grant T32-GM008334)en_US
dc.language.isoen
dc.publisherSpringer Science and Business Media LLCen_US
dc.relation.isversionofhttp://dx.doi.org/10.1038/s41467-020-16920-3en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceNatureen_US
dc.titleUltra-large chemical libraries for the discovery of high-affinity peptide bindersen_US
dc.typeArticleen_US
dc.identifier.citationQuartararo, Anthony J. et al. "Ultra-large chemical libraries for the discovery of high-affinity peptide binders." Nature Communications 11, 1 (June 2020): 3183 © 2020 The Author(s)en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Center for Environmental Health Sciencesen_US
dc.contributor.departmentKoch Institute for Integrative Cancer Research at MITen_US
dc.relation.journalNature Communicationsen_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.updated2020-09-21T14:56:31Z
dspace.date.submission2020-09-21T14:56:33Z
mit.journal.volume11en_US
mit.journal.issue1en_US
mit.licensePUBLISHER_CC
mit.metadata.statusComplete


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