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首页> 外文期刊>EPJ Nonlinear Biomedical Physics >Is it possible to predict electromagnetic resonances in proteins, DNA and RNA?
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Is it possible to predict electromagnetic resonances in proteins, DNA and RNA?

机译：是否可以预测蛋白质，DNA和RNA中的电磁共振？

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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.
机译：背景技术已经表明，在包括THz，GHz，MHz和KHz在内的各种频率下，生物分子（蛋白质，DNA和RNA）中都存在电磁共振。这些共振对于大分子的生物学功能可能很重要，也可以用于分子计算机等设备的开发。由于大分子共振的实验测量是及时且昂贵的，因此需要能够可靠地预测这些共振的计算方法。我们以前曾使用共振识别模型（RRM）来预测微管蛋白和微管中的电磁共振。因此，这些预测在实验上得到了证实。方法RRM是由作者开发的，其发现基于蛋白质，DNA和RNA的电磁共振与沿大分子的自由电子能量分布有关。结果在这里，我们应用了共振识别模型（RRM）来预测端粒酶（例如蛋白质），端粒（DNA）和TERT mRNA（RNA分子）的可能的电磁共振。结论我们认为RRM是一个功能强大的模型，可以通过计算预测蛋白质，DNA和RNA的电磁共振。

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