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Surface dynamics of genomic DNAs upon lowering the pH, in the presence of graphene/AgNPs-based SERS detection platform

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Abstract

Graphene/AgNPs-based surface dynamics of native DNA functional groups at different acidic pH values was discussed using surface-enhanced Raman spectroscopy (SERS). Also, ab initio dynamics of Verlet type was investigated for nucleic acid nitrogenous bases adsorbed on a graphene surface, respectively. The experimental dynamical parameters were given in terms of full widths at half-maximum (FWHMs) and (sub)picosecond global relaxation times, associated with SERS bands. Furthermore, using density functional theory (DFT) as implemented in SIESTA and the velocity autocorrelation function (VACF), we have obtained the vibrational density of states (VDOS) for each of the four DNA bases placed on a pristine graphene layer.

Top: computed VbDOS for guanine. Bottom: Verlet temperature as a function of time.

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Acknowledgments

The authors wish to thank Prof. Dr. Nicolae Leopold for facilitating the surface-enhanced Raman spectroscopic measurements at “Babeş-Bolyai” University, Cluj-Napoca, Romania, to Eng. Sorina Niţu from National Institute of Research and Development for Potato and Sugar Beet, Brasov, Romania, for providing the leaf tissues from medicinal plants, to Dr. Adela Halmagyi from Institute of Biological Research, Cluj-Napoca, Romania, branch of National Institute of Research and Development for Biological Sciences for the help with extracting genomic DNA from medicinal plants leaves, and to our colleague Dr. Cristian Morari for useful discussions on theoretical considerations.

Funding

This research was in part financially supported by the Romanian Ministry of Education and Research, Core Program, project PN 19 35 02 01 and partially by Romanian Ministry of Research and Innovation, project PN-II-ID-PCE-2012-4-0115.

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Correspondence to Cristina M. Muntean.

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Muntean, C.M., Dina, N.E., Biter, TL. et al. Surface dynamics of genomic DNAs upon lowering the pH, in the presence of graphene/AgNPs-based SERS detection platform. J Mol Model 26, 211 (2020). https://doi.org/10.1007/s00894-020-04477-3

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