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Two Dimensional Molecular Electronics Spectroscopy for DNA/RNA Mutation Recognition

Two Dimensional Molecular Electronics Spectroscopy for DNA/RNA Mutation Recognition


In this project, Dr. Reza Rezapour will address, by a combination of quantum mechanical and classical simulations combined with electronic transport techniques, the sensing capabilities of graphene-based biosensors to identify DNA and RNA mutations in PNA-functionalized graphene nanoribbons.
In the search for fast, inexpensive and accurate tools for DNA sequencing and mutation recognition, computational techniques are being fruitfully used to address detection at the molecular level. We will extended the 2D-MES method previously developed by Dr. Rezapour to the identification, not only of single normal and mutated nucleobases on graphene, but of base mutations in DNA or RNA fragments attached to a graphene nanoribbon (GNR) in an aqueous environment. To this aim, after the quantum mechanical (QM) calculation of the transport characteristics of a nucleobases-GNR system in vacuum, we will study: (1) large DNA/RNA fragments in a solvent by molecular mechanics (MM) classical methods (to study mutation stability in a given sequence) and (2) the most stable mutations on a GNR by novel hybrid QM/MM simulations combining the accuracy of QM with the speed of MM.
Besides providing new insight on fundamental aspects of physical processes at the interface between solids, liquids and biomolecules, the project will train Dr. Rezapour in advanced new techniques, complementary to his current expertise; and it will provide the community with a new and efficient QM/MM-electronic transport tool by the implementation of transport routines into the existent QM/MM package. The obtained QM/MM transport molecular fingerprints of the mutated DNA/RNA on the GNR will serve as a proof-of-concept for the design of a graphene-based bionsensor fast, inexpensive, and with high spatial resolution.
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Cuesta Del Hospicio Sn
18071 Granada


Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 172 932,48

Project information

Grant agreement ID: 841673


Grant agreement signed

  • Start date

    1 September 2019

  • End date

    31 August 2021

Funded under:


  • Overall budget:

    € 172 932,48

  • EU contribution

    € 172 932,48

Coordinated by: