Use of infrared and visible light radiation as modulator of protein activity/Infrapunase ja nahtava valguse kiirguse kasutamine valkude aktiveerimise modulaatorina.
Pirogova, Elena ; Cosic, Irena ; Fang, John 等
1. INTRODUCTION
It has been shown that light-activated changes in protein energy
states can induce or modulate biological processes. For instance,
light-activated excitation of rhodopsin (bacteriorhodopsin) molecules,
involved in the hyperpolarization process of the cell membrane, can
either generate nerve impulses, ATP synthesis, or regulate embryogenesis
[1-5]. It has been also suggested that cytochrome c oxidase and certain
dehydrogenases may play a key role in the photoreception process,
particularly in the near infrared (NIR) frequency range [5]. Recent
studies into effects of low-intensity non-thermal light irradiation on
eukaryotic and prokaryotic cells, both pulsed and continuous, have
reported the accelerated proliferation rate in yeast and mammalian cells
upon irradiation by He-Ne laser light [6,7] and increased E. coli
proliferation rate by argon laser light exposures [5,7]. The increased
proliferation rate has also been observed in various bacterial cultures,
irradiated by laser light with radiant exposures of 1-50 J/[cm.sup.2] at
wavelengths of 630 and 810 nm [8]. Several studies have reported a
change in the activity of human erythrocytes after low-intensity light
radiation at 810 nm. Various up-to-date methodologies that incorporate
low-intensity light into therapeutic procedures have been integrated
into modern medicine.
Here we have studied experimentally the hypothesis of the resonant
recognition model (RRM) that selectivity of protein activities is based
on specific resonant electromagnetic interactions [1,9]. The RRM theory
proposes that an external electromagnetic field at a particular
activation frequency would produce resonant effects on protein
biological activity. In our previous study [9] we have investigated the
effects of visible light radiation in a range of 550-850 nm on enzyme
kinetics of the LDH enzyme. In this study we have tested the influence
of electromagnetic radiation (EMR) on biological activity of the LDH
enzyme in the wavelengths ranging from 1140 up to 1200 nm. In addition,
we examined theoretically the possibility that lower frequencies, in the
microwaves range, can also activate long macromolecules such as proteins
and DNA. The RRM procedure for bioactive peptide design is also
presented using the example of oncogene proteins.
2. THE RESONANT RECOGNITION MODEL
2.1. Protein activation frequency
The RRM is designed for the analysis of protein (DNA) interactions
and their interaction with EMR [1,9]. Protein primary structures are
linear sequences of their constitutive elements, i.e. amino acids. The
RRM model interprets this linear information using digital signal
analysis methods that include spectral and space-frequency analyses. It
has been found that the spectrum of the distribution of the energies of
free electrons along the protein molecule is critical for the protein
function (interaction) [1]. In our previous work a relationship between
the RRM spectra of some protein groups and their interaction with
visible light was established. The RRM theory states that an external
electromagnetic field at a particular activation frequency would produce
resonant effects on the protein biological activity [1,9]. It has been
shown that all protein sequences with a common biological function have
a common frequency component in the free energy distribution of
electrons along the protein backbone. This characteristic frequency was
shown to be related to the protein biological function [10].
Furthermore, it was also shown that proteins and their targets share a
characteristic frequency. Thus it can be further postulated that RRM
frequencies characterize not only a general function but also
recognition/interaction between particular proteins and their target at
a distance [10,11]. Thus protein interactions can be viewed as a
resonant energy transfer between the interacting molecules. This energy
can be transferred through oscillations of a physical field, possibly
electromagnetic in nature [1].
Since there is evidence that proteins have certain conducting or
semiconducting properties, a charge, moving through the protein backbone
and passing different energy stages caused by different amino acid side
groups, can produce sufficient conditions for a specific electromagnetic
radiation or absorption. In our previous research we have shown that
such charge transfer through the protein backbone is possible through an
exciton process [1,12]. The frequency range of this field depends on a
charge velocity estimated to be 7.87 x [10.sup.5] m/s and on the
distance between amino acids in a protein molecule, which is 3.8
[Angstrom]. Therefore the maximum frequency due to the exciton transfer
is estimated to be [F.sub.max] <V/(2d) < 1 x [10.sup.5] Hz,
(L.sub.min] > 330 nm). The minimum frequency depends on the total
length L of the protein and is estimated to be around [10.sup.13] Hz (at
30 000 nm) for a protein of about 200 amino acids in length [1,2]. The
range from 30 000 to 300 nm is very wide, from far infrared through the
visible to the ultraviolet region of the spectrum. For larger structures
(e.g. longer proteins, DNA, protein clusters, membrane proteins and
membrane channels) the relevant bioactivity frequency range can be
estimated to start in the high microwave range of [10.sup.10] to
[10.sup.11] Hz. The frequency range predicted for protein interactions
is from [10.sup.13] to [10.sup.15] Hz. This estimated range includes
infrared (IR), visible and ultraviolet (UV) light.
The estimated electromagnetic energy levels were initially
investigated by the comparison of the absorption spectra of some groups
of chromophore-bearing proteins with their corresponding RRM
characteristic frequencies (Table 1, Fig. 1). As can be seen from Table
1 and Fig. 1, a strong linear correlation exists between the predicted
and experimentally determined frequencies. It is inferred that
approximate wavelengths in real frequency space can be calculated from
the RRM characteristic frequencies for each biologically related group
of sequences. These calculations can be used to predict the wavelength
of the light irradiation, which might affect the biological activity of
exposed proteins [9]. These computational predictions were confirmed by
comparison of absorption characteristics of light-absorbing proteins and
their characteristic RRM frequencies, frequency selective light effects
on cell growth and characteristic RRM frequencies of growth factors, and
activation of enzymes by laser radiation [1,13]. All these results
indicate that the specificity of protein interaction is based on a
resonant electromagnetic energy transfer at the frequency specific for
each interaction observed. A linear correlation between the absorption
spectra of proteins and their RRM spectra with a regression coefficient
of K = 201 has been established. Using RRM postulates, a computationally
identified characteristic frequency for a protein functional group can
be used to calculate the wavelength of applied irradiation [lambda]
which assumingly would activate this protein sequence and modify its
bioactivity
[lambda] = K/[f.sub.RRM].
[FIGURE 1 OMITTED]
Here we have utilized this relationship to calculate the
frequencies/wavelengths that might modulate the bioactivity of the
selected enzymes and investigate their activation experimentally.
2.2. Irradiation of the L-lactate dehydrogenase enzyme
Enzymes are proteins crucial in accelerating metabolic reactions in
the living organism. Dehydrogenase enzymes catalyse a variety of
oxidation-reduction reactions within the cells. As the protein example
we have chosen the L-lactate dehydrogenase (rabbit muscle). This enzyme
has been selected on the basis of its commercial availability,
simplicity of the assay, and the possibility of measuring their
bioactivity using the standard well accepted procedure, i.e. Continuous
Spectrophotometric Rate Determination. As a source of IR and visible
light we have used a SpectraPro 2300i monochromator (Acton Research
Corporation) with a wavelength range of 400-1200 nm, grating 600 g/mm
and a resolution of 0.1 nm. For measurement of absorbance of the
analysed enzyme solutions we use an Ocean Optics USB2000 spectrometer
coupled to a CCD array, which can detect in the 190-870 nm range.
LDH rabbit muscle EC1.1.1.27 catalyses the inter-conversion of the
L-lactate into pyruvate with the nicotinamide adenine dinucleotide
oxidized form (NAD+) acting as a coenzyme. The suitability of the LDH
enzyme for this reaction is attributed to the absorption characteristics
of the NADH (nicotinamide adenine dinucleotide reduced form). NADH is
able to absorb light at 340 nm contrary to the NAD, which is inactive at
this frequency. Due to different optical characteristics of NADH and NAD
we are able to optically asses if the reaction pyruvate [right arrow]
lactate in the presence of the LDH as an accelerator has occurred and
then determine the amount of the reactants. The experimental procedure
is presented below.
1. The samples are irradiated for 10 min using Monochromator
SpectraPro 2150i (Acton Research Corporation) set at the activation
wavelength identified computationally using the RRM approach.
2. These irradiated samples are added to the already prepared
solution of NADH and pyruvate.
3. The optical density of NADH is measured at 340 nm.
4. The values of the rate of change in absorbance of NADH and
changes of absorption coefficient values (at 340 nm) in time are
collected and presented graphically.
2.3. Bioactive peptide design
The ability to predict the functions and three-dimensional shapes
of biological molecules would certainly be useful in designing
therapeutic drugs. The structure of the drug molecule that can
specifically interact with a particular biomolecule could be modelled
using computational tools. These tools can allow a drug molecule to be
constructed using knowledge of its structure and the nature of its
active site. In order to design biologically active peptides it is of
primary importance to determine, which amino acids are responsible for
the biological activity of the native protein. Here we present the
results of our computational analysis of oncogene and proto-oncogene
proteins and the rational design of bioactive peptide analogues having
the oncogenic or proto-oncogeneic-like activity.
The RRM presents a completely new engineering approach to the
analysis of proteins and DNA. This model is based on the finding that
the distribution of delocalized electron energies along the protein
amino acid sequence correlates with the protein biological function
[1,10]. The application of the RRM involves two stages of calculation.
The first is the transformation of the amino acid sequence into a
numerical sequence. Each amino acid is represented by the value of the
electron-ion interaction potential (EIIP), describing the average energy
states of all valence electrons in a given amino acid. The EIIP values
for each amino acid were calculated using the following general model of
pseudo-potentials [14,15]:
[k+q[absolute value of w] k] = 0.25 Zsin(1.04[pi]Z)/2[pi],
where q is the change of momentum of the delocalized electron in
the interaction with potential , w while
Z = [[SIGMA].sub.i][Z.sub.i]/N,
where [Z.sub.i] is the number of valence electrons of the i-th
component of each amino acid and N is the total number of atoms in the
amino acid. A unique number can thus represent each amino acid or
nucleotide, irrespective of its position in a sequence. Numerical series
obtained this way are then analysed by digital signal analysis methods
in order to extract information relevant to the biological function. As
the average distance between amino acid residues in a polypeptide chain
is about 3.8 [Angstrom], it can be assumed that the points in the
numerical sequence derived are equidistant. For further numerical
analysis the distance between points in these numerical sequences is set
at an arbitrary value d = 1. Then the maximum frequency in the spectrum
is [f.sub.max] = 1/2d = 0.5. The total number of points in the sequence
influences the resolution of the spectrum only. Thus for -point N
sequence the resolution in the spectrum is equal to 1/N The n-th point
in the spectral function corresponds to the frequency f = n/N. In order
to extract common spectral characteristics of sequences having the same
or similar biological function, the following cross-spectral function
was used:
[S.sub.n] = [X.sub.n][Y.sup.*.sub.n], n = 1,2, ... , N/2
where [X.sub.n] are the DFT coefficients of the series x(m) and
[Y.sup.*.sub.n] are complex conjugate discrete Fourier transform
coefficients of the series y(m). Peak frequencies in the amplitude
cross-spectral function define common frequency components of the two
sequences analysed. To determine the common frequency components for a
group of protein sequences, the absolute values of multiple
cross-spectral function coefficients M have been calculated as follows:
[absolute value of [M.sub.n]] = [absolute value of [X1.sub.n]
[absolute value [X2.sub.n] ... [absolute value of [XM.sub.n], n = 1,2,
... , N/2.
Peak frequencies in such a multiple cross-spectral function denote
common frequency components for all sequences analysed. Signal-to-noise
ratio S/N for each peak is defined as a measure of similarity between
sequences analysed. S/N is calculated as the ratio between signal
intensity at the particular peak frequency and the mean value over the
whole spectrum. The presence of a peak frequency with significant
signal-to-noise ratio in a multiple-cross-spectral function implies that
all of the analysed sequences within the group have one frequency
component in common. From previous studies [1,10,11] the fundamental
conclusion was drawn: one RRM peak frequency characterizes one
particular biological function or interaction. Therefore, those peaks
were named as RRM characteristic frequencies.
Once the RRM characteristic frequencies and corresponding phases
for particular biological functions are determined, it is possible then
to design amino acid sequences having those spectral characteristics
only. It is expected the designed peptide will exhibit the desired
biological activity. The strategy for the design of such defined
peptides is as follows [16]:
* Within the multiple cross-spectral analysis of the group of
protein sequences sharing the corresponding biological function,
determine the unique RRM frequency that characterizes this specific
biological function or interaction.
* Define the characteristic phases at the characteristic
frequencies for the particular protein that is chosen as the parent for
agonist or antagonist peptide design.
* From the known characteristic frequencies and phases derive a
numerical sequence. This can be done by summing sinusoids of the
particular frequencies, amplitudes and phases. The length of the
numerical sequence is defined by the appropriate frequency resolution
and the required peptide length.
* To determine the amino acids that correspond to each element of
the new numerical sequence. It can be achieved by the tabulated EIIP or
other appropriate amino acid parameters.
Earlier we determined the characteristic frequencies of forty six
oncogene and fifteen proto-oncogene proteins, that characterize their
common biological activity, i.e. the ability to promote uncontrolled
cell proliferation, in case of the oncogene proteins, and normal cell
growth for proto-oncogenes [10]. This study emphasizes the de novo
design of peptide analogues only on the basis of the frequencies and
phases, predicted computationally. Ultimately, these designed peptides
would exhibit the desired oncogene or proto-oncogenic-like activity as
their parental protein.
3. RESULTS AND DISCUSSION
3.1. Enzyme activation by infrared light radiation of defined
wavelength
The RRM approach has been used here to identify the activation
frequency of the LDH enzyme. The experimental measurements of its
activity upon electromagnetic field exposures of defined wavelengths
were performed. A computational analysis using the RRM was carried out
resulting in two characteristic frequencies identified at [f.sub.1] =
0.1688 [+ or -] 0.004 and less prominent at [f.sub.2] = 0.2392 [+ or -]
0.004 (Fig. 2). These frequencies are related to the biological activity
of the LDH as it was found in our previous investigations [9]. Based on
the characteristic frequencies determined for the whole dehydrogenase
functional group, we have calculated the wavelength of irradiation,
[lambda] = 201/[f.sub.RRM], which assumingly would activate
dehydrogenase sequences and modify their bioactivity. Thus the
wavelengths of the electromagnetic exposure required for dehydrogenase
enzymes activation would be at 1191 [+ or -] 15 nm and 846 [+ or -] 15
nm. In our previous study we investigated the effects of EMR (550-850
nm) on the LDH kinetics [9]. Here we have studied the changes in the LDH
activity upon irradiation in a range of 1140-1200 nm.
[FIGURE 2 OMITTED]
3.2. Measurement of the NADH absorbance
We have diluted the stock coenzyme solution with the 0.003 M
potassium phosphate assay buffer. Using the properly diluted coenzyme
solution, we have measured the NDAH absorbance upon irradiation at
1140-1200 nm with the interval of 2-5 nm. The spectrophotometer is set
to 100% transmittance (zero absorbance) at each wavelength using the
0.003 M [K.sub.2][HPO.sub.4] assay buffer blank. The results obtained
have shown that NADH concentration corresponds to the maximum absorbance
of 1.6 at 340 nm. Figure 3 shows how NADH sample absorbance is affected
by the applied radiation of the defined wavelength.
[FIGURE 3 OMITTED]
3.3. Measurement of the LDH activity
The 2.5 ml cuvettes are filled with the following components:
* 0.1 ml of 0.0027 M sodium pyruvate (BioWhittaker);
* 0.1 ml NADH; disodium salt (C21H27N7O14P2Na2 Roche);
* 0.005 M phosphate buffered saline (SIGMA);
* 1.5 ml of deionized water; 0.3 ml LDH diluted in 2.5 [micro]g/ml
of phosphate buffered saline with BSA (SIGMA).
The experiments were performed at room temperature 27[degrees]C
(Temperature controller Quantum Northwest). The cuvettes were filled
with 0.3 ml of the LDH samples. The samples were previously irradiated
with the light of different wavelengths (1140-1200 nm) for 600 sec.
These irradiated samples were added then to the already prepared
solution of NADH and pyruvate. The optical density of NADH was measured
at 340 nm for each irradiating wavelength. These values are collected
and presented in Table 2 and Fig. 4. The results obtained have revealed
the change of the NADH absorbance under the influence of irradiated LDH.
Thus, the LDH activity has changed upon radiation, resulting in
accelerating the reaction
pyruvate + NADH [right arrow] lactate + [NAD.sup.+] + [H.sup.+].
From Figs. 3 and 4 we can observe that maximum optical density of
the NADH is achieved at the wavelengths 1192 and 1200 nm ([f.sub.1]
0.1688 [+ or -] 0.004) as was predicted by the RRM as the possible
activation frequency of the dehydrogenase enzymes. Hence, the results
suggest that this specific biological process can be modulated by
irradiation with defined frequencies strongly supporting the main
concept of the RRM methodology. The possibility to calculate the
frequencies with the following use of IR and visible light to produce
the desired biological mutations and alterations in proteins would
benefit the development of new biomaterials, non-invasive treatments and
advanced technologies.
[FIGURE 4 OMITTED]
3.4. Bioactive peptide design: oncogene/proto-oncogene analogy
In this study we applied the RRM approach to design bioactive
peptides having oncogene-like and proto-oncogene-like activities. The
oncogene proteins are generally involved in regulation of cell
proliferation through regulation of DNA transcription. The Ha-ras
oncogene proteins (p21 proteins) are known to function in vitro as GTP
binding proteins involved in signal transduction pathways, as well as in
control of DNA synthesis, cell transformation, proliferation and
differentiation [10]. In our previous studies a group of forty six
oncogene proteins were analysed and their RRM characteristic frequencies
were identified at [f.sub.1] = 0.0322 [+ or -] 0.004, S/N = 297.29 and
[f.sub.2] 0.0537 [+ or -] 0.004, S/N = 77.25. As is evident from Fig.
5a, both identified frequencies with significantly different amplitude
ratios are observed in the cross-spectral function of all oncogene
proteins. The prominent frequency at [f.sub.1] 0.0322 [+ or -] 0.004,
S/N 297.29 characterizes a common biological behaviour of this oncogene
product, i.e. an ability to promote an uncontrolled cell growth and
proliferation. These two peaks identified for oncogene proteins reveal
that oncogenes are multifunctional proteins, i.e. they can be involved
in different biological processes (interact with other proteins). The
same analysis was carried out on fifteen proto-oncogene sequences (Fig.
5b). As can be observed from Fig. 5b, there is a prominent peak at
[f.sub.2] = 0.0537 [+ or -] 0.004, S/N = 199.74, which represents a
characteristic feature of all proto-oncogene sequences and corresponds
to their common biological function, i.e. normal cell growth. It is
noteworthy that the same frequency [f.sub.2] = 0.0537 [+ or -] 0.004,
S/N = 77.25 was identified as the less significant peak existing in
multiple cross-spectral function of oncogene proteins (Fig. 5a).
Here the RRM has been applied to Ha-ras p21 (Harvey Murine sarcoma
virus) protein to design the peptide that exhibits ras-like activity,
i.e. ability to transform cells. The design of six de novo peptides A-F
was based on two characteristic frequencies and phases determined for
the entire functional group of oncogene proteins [f.sub.1] = 0.0322,
[[phi].sub.1] = 1.641 and [f.sub.2] = 0.0537, [[phi].sub.2] = 2.460 Each
peptide has either one or both frequencies with the same or opposite
phases at these frequencies as presented in Fig. 6.
[FIGURE 5 OMITTED]
[FIGURE 6 OMITTED]
Original protein:
Transforming protein (Ha-ras) - Harvey murine sarcoma virus 241
a.a.
MPAARAAPAADEPMRDPVAPVRAPALPRPAPGAVAPASGGA
RAPGLAAPVEAMTEYKLVVVGARGVGKSALTIQLIQNHFVDE
YDPTIEDSYRKQVVIDGETCLLDILDTTGQEEYSAMRDQYMRT
GEGFLCVFAINNTKSFEDIHQYREQIKRVKDSDDVPMVLVGNK
CDLAGRTVESRQAQDLARSYGIPYIETSAKTRQGVEDAFYTLVR
EIRQHKLRKLNPPDESGPGCMSCKCVLS
The designed peptides (18 amino acids):
1) 1.641, [f.sub.2] = 0.0537, [[phi].sub.2] = -2.460
A: NLNEPAWQTRDDDDDRFM
2) [f.sub.1] = 0.0322, [[phi].sub.2] = -1.641
B: LNEPHAYWQCRRDDDDDD
3) [f.sub.2] = 0.0537, [[phi].sub.2] = -2.460
C: EILEPAWQRDDDDDRQWK
4) [f.sub.1] = 0.0322, [[phi].sub.1] = 1.641, [f.sub.2] = 0.0537,
[[phi].sub.2] = 2.460
D: DRMWKPEILGPHKYYWWY
5) [f.sub.1] = 0.0322, [[phi].sub.1] = 1.641
E: DDDRFMQWAAPPEILINV
6) [f.sub.2] = 0.0537, [[phi].sub.2] = 2.460
F: CWAHEILEPAWQRDDDDD
Proto-oncogene proteins are the products of proto-oncogenes.
Generally, they do not have oncogenic or transforming properties but are
involved in the normal regulation or differentiation of cell growth.
However, proto-oncogenes can promote cancer development only if they
acquire new properties as a result of mutations at which point they are
known as oncogenes. Most common cancers involve modification of certain
proto-oncogenes. Determination of two distinct characteristic
frequencies, which correspond to two different functions, i.e. normal
cell growth (proto-oncogenes) and uncontrolled cell transformation
(oncogenes), reveal that the RRM approach can assist in distinguishing
between the oncogene and proto-oncogene activity of oncogene proteins.
Thus, these results can lead to the conclusion that the RRM approach is
capable of identifying "cancerous" feature (frequency) within
the protein primary structures of the studied proteins. In addition, the
de novo peptides designed on the basis of the oncogenic (cancerous) and
proto-oncogenic (normal) frequencies determined within the RRM might be
used in the development of new testing and treatment procedures for
cancer.
3.5. Macromolecular activation by microwave radiation
In addition, we were interested to explore theoretically if
proteins or DNA molecules can be activated by much lower frequencies,
particularly by the frequencies in the microwave range (from [10.sup.9]
to [10.sup.10] Hz). Our preliminary results have shown that activation
of proteins can occur in the range of [10.sup.13] to [10.sup.15] Hz,
where the lower frequency is determined by the length of the protein,
which was supposed to be 200 amino acids. As the relation between the
lower frequency and the length of the protein is linear, it follows that
when aiming to activate proteins by microwaves using the above proposed
mechanism, the protein length needs to be in the order of 200 000 amino
acids. The largest known proteins are the titins, a component of the
muscle sarcomere, with a molecular mass of almost 3000 kDa and a total
length of almost 27 000 amino acids [16]. Thus the minimum frequency
that can activate the titin proteins according to the RRM would be about
[10.sup.11] Hz.
However, DNA sequences are much longer and thus may be considered
as good candidates for activation by microwaves. The analogous RRM
calculations of activation frequencies that we use for proteins can also
be applied to DNA sequences. The EIIP values of amino acids in protein
and nucleotides in DNA are presented in Table 3. We may assume that the
charge is able to travel through the DNA backbone, with a velocity
similar to the charge velocity in proteins:
V < 7.87 x [10.sup.5] m/sec.
If the charge is able to pass different energy levels as was
calculated using the EIIP for different nucleotides [17], then the only
factor that can influence the frequency is the distance between the
nucleotides, which is defined as d = 3.4 [Angstrom].
This distance is close to the distance d = 3.8 [Angstrom], which
was used for calculations for amino acids in the protein sequence.
Therefore, we propose that the maximum frequency that could be emitted
during the electron transfer is practically the same:
[F.sub.max] < V/2d,
[F.sub.max] <1 x [10.sup.15] Hz.
The minimum frequency that could be emitted depends on the total
length of the DNA sequence
[F.sub.min] = 2[F.sub.max]/N,
where N is the total number of nucleotides in the DNA sequence. For
example, for DNA of 200 nucleotides in length, the minimum frequency is
defined as
[F.sub.min] <1 X [10.sup.13] Hz.
However, DNA length is much longer, especially if we take into
account the entire chromosome (45 000 000 bp to 300 000 000 bp). DNA
contour length ranges from approximately 50 to 2700 nm, and could be
affected by the electromagnetic radiation in the microwave frequency
range from [10.sup.15] all the way down to [10.sup.7].
A chromosome in a mammalian cell is made up of a single DNA
molecule about 5 cm long, which is effectively compacted into each
chromosome. A study of the DNA lengths in each chromosome in several
organisms using the Entrez Swiss database shows that the base pair
lengths in each chromosome of several evolutionary distinct organisms
can be quite different. Some of this data is shown in Table 3.
Interestingly, if we consider the mitochondrial DNA, we observe much
greater homogeneity in the DNA length (Table 3). This is most likely
explained by the theory that mitochondria were once separate organisms
that were incorporated into the cellular structure of eukaryotic cells.
The slight differences in mitochondrial DNA length are due to
differences in the length of the control regions of the mitochondrial
DNA. The suggestion that the same mechanisms are applicable for lower
frequencies' interaction with macromolecules would imply that
activation would be possible only for longer macromolecules, i.e. for
extremely large proteins and DNA.
4. CONCLUSIONS
In this study we have irradiated the LDH enzyme with the light of
defined wavelength determined within the RRM. The results obtained have
shown that the RRM frequencies, identified for the dehydrogenase enzymes
at [f.sub.1] = 0.1688 [+ or -] 0.004 and less prominent at [f.sub.2] =
0.2392 [+ or -] 0.004 (corresponding to 1191 [+ or -] 15 and 846 [+ or
-] 15 nm respectively) can be directly related to the resonances in
electron differential scattering cross-section of these macromolecules.
Thus, we conclude that the RRM spectral characteristic and their
corresponding wavelengths of electromagnetic energy can be used to
modulate the protein activity, hence giving rise to an innovative
efficient methodology to program, predict, design and modify proteins
and their bioactivity.
We have shown previously, using the RRM concepts, that digital
signal processing methods can be used to analyse linear sequences of
amino acids to reveal the informational content of proteins and
determine functionally significant amino acids of the analysed proteins.
In this study we have shown that the RRM is capable of identifying the
difference between oncogenes and proto-oncogenes and thus, identifying
general "cancerous" feature within oncogene protein primary
structures. If such feature can be identified then it would be possible
to validate unknown or modified proteins as well as relevant DNA
sequences for their possible cancerous activity. In addition, as shown
here, it is possible to design peptides which would have only this
"cancerous" characteristic. Such peptides are predicted to
carry the common characteristic of all oncogenes and thus, they can be
used for development of a vaccine, which could be then preventive for
most kind of cancers. Thus, the RRM provides a new strategy for a wide
variety of protein and peptide structural manipulations, e.g., protein
engineering by recombinant techniques could be undertaken based on the
RRM predictions for the redesign of specific protein or peptide variants
with modified biological properties.
In this work we have also examined the possibility of activation of
large macromolecules such as proteins and DNA by lower frequencies in
the range of microwaves. Based on the RRM postulates it has been shown
that activation of macromolecules by microwaves can be only achieved for
linear macromolecules in excess of 200,000 residues/nucleotides. Thus,
it is unlikely that microwaves would be able to activate proteins, based
on the resonant energy transfer as was proposed in the RRM as their
length does not exceed the length required. However, DNA sequences are
much longer and there is a possibility that microwaves can activate DNA
through the resonant energy transfer as it is suggested in the RRM model
in a wide frequency range of [10.sup.7] - [10.sup.15]Hz.
ACKNOWLEDGEMENTS
We wish to acknowledge the financial support of this study provided
by the Australian Centre of Radiofrequency Bioeffects Research (ACRBR)
and RMIT Research Investment Fund.
Received 25 January 2008, in revised form 15 April 2008
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Elena Pirogova, Irena Cosic, John Fang and Vuk Vojisavljevic
School of Electrical and Computer Engineering, RMIT University, GPO
Box 2476V, Melbourne VIC 3001, Australia; elena.pirogova@rmit.edu.au
Australian Centre of Radiofrequency Bioeffects Research
Table 1. The RRM frequencies and characteristic absorption frequencies
of different visible light-absorbing protein groups and their
scaling factor, K [1,9]
Protein nm rrm [cm.sup.-1] K
cyt c 415 0.473 24 096.39 196
blue 430 0.475 23 255.81 204
green 540 0.355 18 518.52 191
red 570 0.346 17 543.86 197
hem. 14 770 0.02 677.0481 295
purple 860 0.281 11 627.91 241
flavodoxin 470 0.379 21 276.6 178
igf 400 0.492 25 000 196
fgf 441.6 0.453 22 644.93 200
insulin 552 0.344 18 115.94 189
growth f. 633 0.293 15 797.79 185
650 0.293 15 384.62 190
pdgf 830 0.242 12 048.19 200
chymotr. 851 0.236 11 750.88 200
calculative 400 0.5 25 000 200
Table 2. Absorbance and wavelength values of the NADH sample
t, sec Wavelength of irradiating light, nm
1140 1150 1160 1170 1175 1180 1185
0 1.311 1.318 1.223 1.104 1.276 1.235 1.243
30 1.257 1.255 1.161 1.048 1.231 1.186 1.191
60 1.196 1.196 1.104 0.989 1.169 1.115 1.132
90 1.138 1.131 1.049 0.938 1.121 1.061 1.082
120 1.096 1.071 0.986 0.878 1.067 1.000 1.029
150 1.031 1.010 0.931 0.824 1.016 0.936 0.975
180 0.983 0.947 0.866 0.758 0.962 0.877 0.913
210 0.926 0.891 0.806 0.696 0.915 0.823 0.863
240 0.873 0.831 0.752 0.649 0.853 0.755 0.811
270 0.813 0.772 0.689 0.596 0.808 0.703 0.762
300 0.761 0.714 0.629 0.538 0.754 0.644 0.706
330 0.711 0.661 0.572 0.488 0.704 0.589 0.659
360 0.656 0.608 0.515 0.436 0.656 0.530 0.603
390 0.601 0.547 0.458 0.385 0.613 0.480 0.561
420 0.550 0.494 0.404 0.336 0.566 0.429 0.513
450 0.509 0.435 0.354 0.290 0.518 0.374 0.464
480 0.403 0.403 0.304 0.244 0.470 0.324 0.426
510 0.420 0.341 0.259 0.205 0.427 0.279 0.379
540 0.392 0.300 0.221 0.170 0.373 0.234 0.338
570 0.348 0.260 0.189 0.137 0.335 0.198 0.302
600 0.301 0.225 0.16 0.110 0.294 0.162 0.259
Grad. 0.0018 0.0020 0.002 0.0019 0.0017 0.0020 0.001
t, sec Wavelength of irradiating light, nm
1190 1192 1194 1196 1198 1200 test01
0 1.261 1.286 1.285 1.296 1.307 1.456 1.283
30 1.218 1.228 1.217 1.233 1.268 1.411 1.238
60 1.168 1.184 1.153 1.185 1.205 1.353 1.176
90 1.117 1.113 1.089 1.116 1.146 1.307 1.125
120 1.058 1.053 1.028 1.055 1.088 1.260 1.074
150 1.012 0.987 0.970 1.004 1.037 1.201 1.014
180 0.956 0.927 0.914 0.942 0.978 1.158 0.960
210 0.912 0.871 0.859 0.882 0.918 1.120 0.904
240 0.858 0.811 0.797 0.827 0.859 1.066 0.850
270 0.805 0.751 0.741 0.771 0.810 1.011 0.787
300 0.755 0.694 0.681 0.712 0.752 0.961 0.732
330 0.705 0.636 0.622 0.657 0.695 0.913 0.678
360 0.653 0.579 0.571 0.606 0.643 0.868 0.625
390 0.596 0.524 0.512 0.545 0.583 0.823 0.575
420 0.535 0.469 0.455 0.495 0.530 0.769 0.537
450 0.488 0.413 0.404 0.442 0.482 0.708 0.496
480 0.444 0.366 0.358 0.392 0.435 0.666 0.440
510 0.394 0.319 0.314 0.340 0.396 0.620 0.387
540 0.358 0.276 0.276 0.292 0.346 0.576 0.348
570 0.314 0.238 0.243 0.255 0.300 0.538 0.301
600 0.275 0.207 0.211 0.223 0.267 0.498 0.267
Grad. 0.0017 0.0021 0.0020 0.0020 0.0019 0.0016 0.0018
Table 3. Chromosome and DNA length variation between different
organisms
Organism Chromo- Chromosome Organism
some length, kbp
Homo sapiens 20 90 000 Homo sapiens
Homo sapiens 19 100 000 Great Indian Rhino
Homo sapiens 17 125 000 Donkey
Homo sapiens 6 225 000 Atlantic cod
Dros. melanogaster 4 1 750 Locust (L. migratoria)
Dros. melanogaster 3 50 000
Dros. melanogaster 2 51 000
Mus musculus 11 45 000
Organism Length of
mitochondrial DNA
Homo sapiens 16K
Homo sapiens 16 829
Homo sapiens 16 670
Homo sapiens 16 696
Dros. melanogaster 15 722
Dros. melanogaster
Dros. melanogaster
Mus musculus
