Issue |
EPJ Nonlinear Biomed Phys
Volume 3, Number 1, December 2015
|
|
---|---|---|
Article Number | 5 | |
Number of page(s) | 8 | |
DOI | https://doi.org/10.1140/epjnbp/s40366-015-0020-6 | |
Published online | 23 May 2015 |
https://doi.org/10.1140/epjnbp/s40366-015-0020-6
Research
Is it possible to predict electromagnetic resonances in proteins, DNA and RNA?
1
RMIT University, Melbourne, 3000, VIC, Australia
2
AMALNA Consulting, 46 Second St, Black Rock, 3193, VIC, Australia
* e-mail: irenacosic@me.com
Received:
14
April
2015
Accepted:
6
May
2015
Published online:
23
May
2015
Background
It has been shown that there are electromagnetic resonances in biological molecules (proteins, DNA and RNA) in the wide range of frequencies including THz, GHz, MHz and KHz. These resonances could be important for biological function of macromolecules, as well as could be used in development of devices like molecular computers. As experimental measurements of macromolecular resonances are timely and costly there is a need for computational methods that can reliably predict these resonances.
We have previously used the Resonant Recognition Model (RRM) to predict electromagnetic resonances in tubulin and microtubules. Consequently, these predictions were confirmed experimentally.
Methods
The RRM is developed by authors and is based on findings that protein, DNA and RNA electromagnetic resonances are related to the free electron energy distribution along the macromolecule.
Results
Here, we applied the Resonant Recognition Model (RRM) to predict possible electromagnetic resonances in telomerase as an example of protein, telomere as an example of DNA and TERT mRNA as an example of RNA macromolecules.
Conclusion
We propose that RRM is a powerful model that can computationally predict protein, DNA and RNA electromagnetic resonances.
Key words: Molecular resonances / Proteins / DNA / RNA / Resonant recognition model
© The Author(s), 2015