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dc.contributor.authorDubacheva, Galina Ven
dc.contributor.authorCurk, Tineen
dc.contributor.authorFrenkel, Daanen
dc.contributor.authorRichter, Ralf Pen
dc.date.accessioned2019-02-22T18:01:02Z
dc.date.available2019-02-22T18:01:02Z
dc.date.issued2019-02-05en
dc.identifier.issn0002-7863
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/289852
dc.description.abstractThe interaction between a biological membrane and its environment is a complex process, as it involves multivalent binding between ligand/receptor pairs, which can self-organize in patches. Any description of the specific binding of biomolecules to membranes must account for the key characteristics of multivalent binding, namely, its unique ability to discriminate sharply between high and low receptor densities (superselectivity), but also for the effect of the lateral mobility of membrane-bound receptors to cluster upon binding. Here we present an experimental model system that allows us to compare systematically the effects of multivalent interactions on fluid and immobile surfaces. A crucial feature of our model system is that it allows us to control the membrane surface chemistry, the properties of the multivalent binder, and the binding affinity. We find that multivalent probes retain their superselective binding behavior at fluid interfaces. Supported by numerical simulations, we demonstrate that, as a consequence of receptor clustering, superselective binding is enhanced and shifted to lower receptor densities at fluid interfaces. To translate our findings into a simple, predictive tool, we propose an analytical model that enables rapid predictions of how the superselective binding behavior is affected by the lateral receptor mobility as a function of the physicochemical characteristics of the multivalent probe. We believe that our model, which captures the key physical mechanisms underpinning multivalent binding to biological membranes, will greatly facilitate the rational design of nanoprobes for the superselective targeting of cells.
dc.description.sponsorshipEU ETN grant 674979-NANOTRANS
dc.format.mediumPrint-Electronicen
dc.languageengen
dc.titleMultivalent Recognition at Fluid Surfaces: The Interplay of Receptor Clustering and Superselectivity.en
dc.typeArticle
prism.endingPage2588
prism.issueIdentifier6en
prism.publicationDate2019en
prism.publicationNameJournal of the American Chemical Societyen
prism.startingPage2577
prism.volume141en
dc.identifier.doi10.17863/CAM.37091
dcterms.dateAccepted2019-01-24en
rioxxterms.versionofrecord10.1021/jacs.8b12553en
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2019-02-05en
dc.contributor.orcidDubacheva, Galina V [0000-0003-1417-5381]
dc.contributor.orcidFrenkel, Daan [0000-0002-6362-2021]
dc.contributor.orcidRichter, Ralf P [0000-0003-3071-2837]
dc.identifier.eissn1520-5126
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idEuropean Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (674979)
cam.orpheus.successThu Jan 30 10:50:14 GMT 2020 - Embargo updated*
rioxxterms.freetoread.startdate2020-02-05


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