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    Adsorption of DNA Fragments at Aqueous Graphite and Au(111) via Integration of Experiment and Simulation

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    Publication date
    2017-09-08
    Author
    Hughes, Zak E.
    Gang, W.
    Drew, K.L.M.
    Ciacchi, L.C.
    Walsh, T.R.
    Keyword
    DNA
    Single molecule force spectroscopy
    Graphene
    Gold
    Rights
    (c) 2017 ACS. This is an Open Access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html), which permits copying and redistribution of the article or any adaptations for non-commercial purposes.
    Peer-Reviewed
    Yes
    
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    Abstract
    We combine single molecule force spectroscopy measurements with all-atom metadynamics simulations to investigate the cross-materials binding strength trends of DNA fragments adsorbed at the aqueous graphite C(0001) and Au(111) interfaces. Our simulations predict this adsorption at the level of the nucleobase, nucleoside, and nucleotide. We find that despite challenges in making clear, careful connections between the experimental and simulation data, reasonable consistency between the binding trends between the two approaches and two substrates was evident. On C(0001), our simulations predict a binding trend of dG > dA ≈ dT > dC, which broadly aligns with the experimental trend. On Au(111), the simulation-based binding strength trends reveal stronger adsorption for the purines relative to the pyrimadines, with dG ≈ dA > dT ≈ dC. Moreover, our simulations provide structural insights into the origins of the similarities and differences in adsorption of the nucleic acid fragments at the two interfaces. In particular, our simulation data offer an explanation for the differences observed in the relative binding trend between adenosine and guanine on the two substrates.
    URI
    http://hdl.handle.net/10454/15780
    Version
    Published version
    Citation
    Hughes ZE, Gang W, Drew KLM et al (2017) Adsorption of DNA Fragments at Aqueous Graphite and Au(111) via Integration of Experiment and Simulation. Langmuir. 33(39): 10193-10204.
    Link to publisher’s version
    https://doi.org/10.1021/acs.langmuir.7b02480
    Type
    Article
    Collections
    Life Sciences Publications

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