2D-MES | Two Dimensional Molecular Electronics Spectroscopy for DNA/RNA Mutation Recognition

Summary
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.
Unfold all
/
Fold all
More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/841673
Start date: 01-07-2020
End date: 30-06-2023
Total budget - Public funding: 172 932,48 Euro - 172 932,00 Euro
Cordis data

Original description

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.

Status

CLOSED

Call topic

MSCA-IF-2018

Update Date

28-04-2024
Images
No images available.
Geographical location(s)
Structured mapping
Unfold all
/
Fold all
Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.3. EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions (MSCA)
H2020-EU.1.3.2. Nurturing excellence by means of cross-border and cross-sector mobility
H2020-MSCA-IF-2018
MSCA-IF-2018