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Langmuir. 2016 Jun 21;32(24):6028-34. doi: 10.1021/acs.langmuir.6b00456. Epub 2016 Jun 06.

Complex Thermodynamic Behavior of Single-Stranded Nucleic Acid Adsorption to Graphene Surfaces.

Langmuir : the ACS journal of surfaces and colloids

Srivathsan V Ranganathan, Ken Halvorsen, Chris A Myers, Neil M Robertson, Mehmet V Yigit, Alan A Chen

Affiliations

  1. Department of Chemistry and ‡The RNA Institute, University at Albany, State University of New York , 1400 Washington Avenue, Albany, New York 12222, United States.

PMID: 27219463 DOI: 10.1021/acs.langmuir.6b00456

Abstract

In just over a decade since its discovery, research on graphene has exploded due to a number of potential applications in electronics, materials, and medicine. In its water-soluble form of graphene oxide, the material has shown promise as a biosensor due to its preferential absorption of single-stranded polynucleotides and fluorescence quenching properties. The rational design of these biosensors, however, requires an improved understanding of the binding thermodynamics and ultimately a predictive model of sequence-specific binding. Toward these goals, here we directly measured the binding of nucleosides and oligonucleotides to graphene oxide nanoparticles using isothermal titration calorimetry and used the results to develop molecular models of graphene-nucleic acid interactions. We found individual nucleosides binding KD values lie in the submillimolar range with binding order of rG < rA < rC < dT < rU, while 5mer and 15mer oligonucleotides had markedly higher binding affinities in the range of micromolar and submicromolar KD values, respectively. The molecular models developed here are calibrated to quantitatively reproduce the above-mentioned experimental results. For oligonucleotides, our model predicts complex binding features such as double-stacked bases and a decrease in the fraction of graphene stacked bases with increasing oligonucleotide length until plateauing beyond ∼10-15 nucleotides. These experimental and computational results set the platform for informed design of graphene-based biosensors, further increasing their potential and application.

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