SCIENTIFIC REPORTS
Anesthetic Alterations of Collective
Terahertz Oscillations in Tubulin
Correlate with Clinical Potency:
Received: 8 May 2017
Accepted: I August 2017 Implications for Anesthetic Action
Published online: 29 August 2017
and Post-Operative Cognitive
Dysfunction
Travis J. A. Craddock. 1, Philip Kurian2, Jordane Preto3, Kamlesh Sahitts,
Stuart R. Hameroffs, Mariusz Klobukowski2 & Jack A. Tuszynski3,4
Anesthesia blocks consciousness and memory while sparing non•conscious brain activities.While the
exact mechanisms of anesthetic action are unknown, the Meyer•Overton correlation provides a link
between anesthetic potency and solubility in a lipid -like, non•polar medium. Anesthetic action is also
related to an anesthetic's hydrophobicity, permanent dipole, and polarizability, and is accepted to
occur in lipid-like, non-polar regions within brain proteins. Generally the protein target for anesthetics is
assumed to be neuronal membrane receptors and ion channels, however new evidence points to critical
effects on intra•neuronal microtubules, a target of interest due to their potential role in post-operative
cognitive dysfunction (POCD). Here we use binding site predictions on tubulin, the protein subunit of
microtubules, with molecular docking simulations, quantum chemistry calculations, and theoretical
modeling of collective dipole interactions in tubulin to investigate the effect of a group of gases
including anesthetics, non•anesthetics, and anesthetic/convulsants on tubulin dynamics. We found
that these gases alter collective terahertz dipole oscillations in a manner that is correlated with their
anesthetic potency. Understanding anesthetic action may help reveal brain mechanisms underlying
consciousness, and minimize POCD in the choice and development of anesthetics used during surgeries
for patients suffering from neurodegenerative conditions with compromised cytoskeletal microtubules.
Anesthesia is one of the world's greatest serendipitous pharmacological discoveries, selectively and reversi-
bly blocking consciousness while sparing non-conscious brain activities, enabling modern surgery. Yet, the
mechanism by which anesthesia acts, and how the brain produces conscious experience remain unknown.
Understanding anesthesia may help explain consciousness, and vice versa. On a more practical level, discov-
ering sites and mechanisms of anesthetic action can help in clinical decisions (e.g. the choice of anesthetic in
patients with cancer, neurodegenerative, and other disorders), lead to new anesthetics, and reduce the risk of
anesthesia-related post-operative cognitive dysfunction (POCD).
'Departments of Psychology & Neuroscience, Computer Science, and Clinical Immunology, and the Clinical
Systems Biology Group, Institute for Neuro-Immune Medicine, Nova Southeastern University, Fort Lauderdale,
Florida, USA. 'National Human Genome Center and Department of Medicine, Howard University College of
Medicine, and Computational Physics Laboratory, Howard University, Washington, DC, USA. 'Department of
Experimental Oncology, Cross Cancer Institute, Edmonton, Alberta, Canada. `Department of Physics, University
of Alberta, Edmonton, Alberta, Canada. 'Department of Medical Microbiology and Immunology, University of
Alberta, Edmonton, Canada. 'Departments of Anesthesiology and Psychology, Center for Consciousness Studies,
The University of Arizona Health Sciences Center, Tucson, Arizona, USA. 'Department of Chemistry, University of
Alberta. Edmonton. Alberta. Canada. Correspondence and requests for materials should be addressed to T.J.A.C.
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Desfhwase tellurene Halothane
Nitrou• Oxide
Figure 1. Chemical structure of investigated agents. Blue - anesthetics; Red - non-anesthetics; Green -
anesthetic/convulsant.
The link between anesthesia, POCD, and the exacerbation of neurodegenerative disorders is a major con-
cern'''. After surgery at least 30% of adults show cognitive dysfunction two days following surgery, and lasting up
to at least 3-months in 12% of the elderly'. This is clearly problematic for patients with neurodegenerative condi-
tions, with anesthesia having a significant impact on disease progression and cognitive decline". As Alzheimer's
disease (AD) and other dementias currently cost the American taxpayer $236 billion annually's and with increas-
ing anesthesia required for age-related surgery, this cost is only expected to rise as the population ages.
The mystery of anesthesia stems from the baffling structure-activity relationship of general anesthetics, as
effective agents can span a 35-fold range in molecular volume from a single atom (xenon) to 56-atom steroids,
with numerous types of chemical structures, including ethers and halogenated hydrocarbons, in between"
(Fig. l). Examining the anesthetic action of gases with such disparate structures, Hans Meyer" and Charles
Overton" discovered that anesthetic potency (e.g. the inverse of the minimum alveolar concentration (MAC)
at which half of animals tested would lose purposeful behavior) correlates highly with their solubility in a par-
ticular non-polar solvent akin to olive °V.". Thus, the 'Meyer-Overton correlation revealed that the anesthetic
potency of a gas molecule correlates with its solubility in a non-polar, 'lipid-like', hydrophobic (i.e. water exclud-
ing) medium (Fig. 2A, Table SI). Surprisingly, this correlation holds for general anesthetic activity in many organ-
isms" from paramecia to humans", and even plants30-22. Furthermore, anesthesia is completely reversible.
The Meyer-Overton correlation suggests a common, unitary mechanism of anesthetic action. Initially this
was taken to imply critical effects on the excitability oflipid bilayers in neuronal membranes. However, anesthetic
effects on lipids cannot account for differences between mirror image chiral' anesthetic molecules", the 'cut-off'
effect (lack of anesthetic effect of molecules which follow Meyer-Overton but are too large, e.g. increasing length
of n-alcohols" or n-alkanes"), or the lack of anesthesia by temperature induced re-ordering in lipids which
mimics anesthetic effects therein'''. Finally, there are exceptions to the Meyer-Overton rule. Agents, such as 1,3,5
tris(trifluoromethyl)senzene (TFMB) and 1,2 dichlorohexafluorocyclobutane (F6), which are predicted by their
lipid solubility to have significant anesthetic potency but do not, even at higher concentrations (represented by an
estimated MAC of 1000% atmospheres (atm)) (Fig. 2A). Consequently, these agents are called non-anesthetics.
Other gases, such as flurothyl (indoldan), show unresponsiveness at their Meyer-Overton predicted anesthetic
potency, but cause seizures at lower concentrations and are thus denoted as anesthetidconvulsants". Discerning
how non-anesthetics differ from anesthetics may be an important clue to understanding anesthesia.
It is well accepted that the effect of anesthetics is related to their hydrophobicity, as well as their permanent
dipole strength, and polarizability"• E9. Considering the problems with the lipid bilayer theories of anesthesia,
Franks and Lieb demonstrated that the Meyer-Overton correlation was consistent with anesthetics acting directly
on proteins, specifically in non-polar, lipid-like 'hydrophobic pockets' within protein interiors". These non-polar
intra-protein regions provide for a chiral environment, and therefore, the orientation of the pocket-bound anes-
thetic is determined by its structure and permanent dipole moment. Furthermore, these regions are composed
largely of highly polarizable, it-resonance clouds of aromatic amino acids such as tryptophan, tyrosine, and phe-
nylalanine. Polarizability, which refers to the degree to which a molecule can be instantaneously polarized by
nearby charge distributions, correlates strongly with anesthetic potency"•" (Fig. 2B, Table SI). However, the
polarizability correlation also implies that the predicted MAC of the non-anesthetics F6 and TFMB are less than
predicted by the Meyer-Overton relation suggesting an even higher anesthetic potency for these agents than pre-
viously believed, but this is clearly not the case as they have no anesthetic effect even at significantly higher doses.
What this does indicate is that there is a clear deviation from the correlation between the physical parameters
SCIENTIFIC REPORTS17: 9877 IDC810.1038/s41598-017-09992-7 2
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Figure 2. Correlation of anesthetic properties with anesthetic potency. (a) Meyer-Overton correlation of
oil:gas partition coefficient versus MAC (Blue points - anesthetics; Red points - non-anesthetics; Green points
- anesthetic/convulsant Red line - difference between non-anesthetic predicted and estimated (-1000% atm)
MAC). (b) Correlation of polarizability versus MAC, with MAC for non-anesthetics determined from the
Meyer-Overton correlation. (c) Correlation of polarizability versus solubility shows a difference in the relation
between these properties for non-anesthetics and anesthetics. Trend lines and equations based on anesthetics
alone, without the contributions from the non-anesthetics and anesthetic/convulsant.
SCIENTIFIC RE PORTS17: 9877 IDOI:10.1038N41598-017-09992-7 3
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for lipid solubility and molecular polarizability for these non-anesthetic agents compared to anesthetics (Fig. 2C,
Table Si). Thus, it appears that non-polar 'lipid' solubility determines anesthetic binding at the site of action, i.e.
within hydrophobic pockets, but how does this cooperate with molecular polarizability to act in the brain and
cause loss of consciousness?
Anesthetic binding within protein interiors is thought to block critical conformational changes or other spe-
cific dynamic protein functions, but the question of which proteins are critically involved remains unclear. Franks
and Lieb, and many others, assumed that anesthetics target membrane receptor and ion channel proteins, as these
directly govern dendritic-somatic membrane excitability and depolarization, which govern axonal firing rates.
Specifically, post-synaptic GABAA, acetylcholine, serotonin, glutamate, glycine, n2-adrenergic, acetylcholine, or
adenosine receptors have been the presumptive membrane protein targets, and anesthetics have been shown to
have a high binding affinity for these sites. However, under anesthesia, there's more anesthetic in the peripheral
fat stores of the patient's body than in their brain, yet anesthetics act in the brain. Thus, anesthetics clearly bind
to these receptors and channels at their MAC value, but as anesthetic actions on them are highly variable and
inconsistent, they have been deemed fruitless in terms of a common mechanism of action".
Yet, while membrane- bound receptors and ion channels continue to be considered the primary sites of anes-
thetic action, the microtubule cytoskeleton inside neurons remains overlooked". In 1968, Allison and Nunn
showed that the anesthetic halothane caused depolymerization of microtubules, although at high anesthetic
concentrations of about 5 times their MAC value". While this is beyond clinical concentrations, a systematic
approach by the Eckenhoff lab using radiolabeled halothane in mice showed that at clinically relevant concentra-
tions (—the MAC value for mice), anesthetics bind to —70 different neuronal proteins, halfin membranes and half
in the cytoplasm". Among these was cytoskeletal tubulin, the component subunit protein of microtubules. Many
studies since have indicated direct binding of several anesthetics directly to tubulin including halothaner"• 3s,
6-Azi-pregnanolone36, and 1-azidoanthracene". Furthermore, proteomic analysis ofgenetic expression following
exposure to the volatile anesthetics halothane, isoflurane, desfiurane, and sevollurane show alterations in tubulin
gene expression several days after treatment'" 40 with no changes observed in the expression of membrane pro-
teins". Clearly, anesthetics do bind to membrane receptors and channels as well as lipids at their MAC value, but
they also bind to tubulin in microtubules.
These findings are of relevance because learning, memory, cognition, and the long-term potentiation para-
digm specifically require a cytoskeleton capable of complex reorganization to accommodate changes in synaptic
activity and strength"-". This further suggests that anesthetic-induced changes in cytoskeletal stability may be
a common mechanism for anesthesia". Neurodegenerative diseases share the pathology of a dysfunctional neu-
ronal cytoskeleton (e.g. Alzheimer's, Parkinson's etc.)", and since the architecturally complex cytoskeletal matrix
within neurons is responsible for neuron morphology and intracellular transport, the interaction of anesthetics
with tubulin and microtubules is important for understanding the effects of anesthesia-induced post-operative
cognitive dysfunction (POCD).
While this is clearly an issue, the mechanisms leading to cognitive impairment after anesthesia and surgery are
not yet fully understood. It has been previously hypothesized that anesthetics can alter resonance in it-electron
cloud oscillations among highly polarizable non-polar amino acids in tubulin". Overall, dipoles can be induced
within these electron clouds by nearby charges, dipoles, or other polarizable structures. When in proper orienta-
tion it-resonance structures (exemplified in simplest form by benzene) attract each other by van der Waals-type
London dispersion forces, which then couple and oscillate. As dispersion forces tend to be stronger between mol-
ecules that are easily polarized, and as these dispersion forces contribute to protein folding and protein-protein
interactions", the effect of anesthetic polarizability on tubulin has implications for the dynamics of microtubule
stability during and after surgery.
As any mechanism ofanesthesia is expected to discriminate between true anesthetics and non-anesthetics, we
aim to further test this hypothesis by assessing the effects of several volatile anesthetics, the non-anesthetics F6
and TFMB, as well as the convulsant flurothyl on the London dispersion interactions between highly polarizable
aromatic amino acids in tubulin. To investigate how molecular solubility and polarizability may contribute to
anesthetic action we use results of previous anesthetic binding site predictions on tubulin with molecular dock-
ing, quantum chemistry calculations, and theoretical modeling of collective London dispersion interactions to
investigate the effects of this group of gases on tubulin function. As this mechanism has direct bearing on the
link between anesthesia, post-operative cognitive disorder (POCD) and its effect on neurodegenerative disease,
it has the potential to provide new insights on the site and mechanism of anesthetic action, and may in the future
contribute to the design and development of new anesthetics with fewer potentially harmful side effects. Below,
we discuss the results obtained in our study.
Results
Anesthetic Docking to Tubulin. To computationally predict the effect of anesthetics on the tubulin protein
we ran docking simulations of 8 anesthetic molecules, 2 non-anesthetic molecules, and the convulsant flurothyl
(Fig. 1), on previously predicted high affinity sites of binding to tubulin". The results of anesthetic docking to
tubulin are summarized in Table S2.
Successful docking was completed for all 9 high-affinity binding sites for all l l agents except for the
non-anesthetic F6 to tubulin site 5 and non-anesthetic TFMB to site 7. Most likely these agents failed to dock
due to the binding site being too small or containing unfavorable functional groups, donor/acceptor interac-
tions, hydrogen bonds or hydrophobic effects. Whether this relates to their non-anesthetic effect is unknown. All
binding energy values range between -4 and — 12ki/mol, which is indicative of weak non-covalent interactions
consistent with the known binding action of anesthetic agents by van der Waals-type London dispersion forces.
To determine if there is a preferred binding site on tubulin for all anesthetics, ANOVA analysis was run to
compare anesthetic binding at each site. Figure S1 provides a graphical illustration of the distribution of binding
SCIENTIFIC RE PORTS17: 9877 IDOI:181038N41598-017-09992-7 4
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sites of the various anesthetics on tubulin. On average, the preference for anesthetics to bind at a tubulin site
are ordered as site 7, 5, 38, 4, 1, 23, 37, and finally 21. However, statistical difference (p < 0.05) was only found
between site 21 and sites 4, 5, 7 and 38. No other significant differences were found, suggesting that there is no
overall preferred binding site for anesthetics to tubulin. Still, it is worth noting that sites 7 and 38 are within 5
angstroms of key residues of the colchicine-binding pocket which is consistent with the volatile anesthetic hal-
othane being shown to reduce colchicine binding to tubulini9. Furthermore, sites 5, 7, and 38 are all within 5
angstroms of residues that interact with either the intradimer non-exchangeable GTP molecule or the magnesium
ion required for the intradimer alpha-beta tubulin stability, and may be a mechanism by which volatile anesthet-
ics disrupt microtubule structureS0.
Quantum Chemical Estimate of Polarizability and MAC. We calculated the mean polarizability and
polarizability tensors for all It agents listed in Fig. 1 using a density functional theory approach. The results of
our quantum chemical estimate of mean polarizability are shown in Fig. 2B and listed in Table SI, along with
experimental measures of anesthetic MAC and predicted MAC for non-anesthetics and convulsants. However,
these estimates are based on the mean polarizabilities of the molecules and does not account for the directions of
polarization, permanent dipole moments, or docking orientation of agents to a given protein.
To investigate the full effect of anesthetic, non-anesthetic, and convulsant polarizabilities and permanent
dipole moments on the collective electronic behavior of the tubulin dimer, we calculated the molecular dipole
components induced by London dispersion forces between the highly polarizable aromatic amino acids tryp-
tophan, tyrosine, and phenylalanine based on their molecular polarizability tensors, and evaluated the change
between collective dipole oscillations in the presence and absence of the agent molecules. In the absence ofagent
molecules the aromatic amino acids of tubulin set up normal oscillatory modes that range in frequency between
480 and 700 THz (1THz = 1012 Hz). This result provides a first-order description of the collective oscillation in
tubulin. A full quantum mechanical parametrization of the coupled atomic dipolar fluctuations in valence elec-
tronic response, as done in the many-body dispersion approach to describe collective wavelike charge density
fluctuations", would provide a more refined estimate of this behavior.
The presence of an agent molecule creates another normal mode of dipole oscillation for the aromatic-agent
network In Fig. 3 we plot these new normal modes created by the addition ofan agent as a function of their MAC.
A clear polynomial trend can be seen for anesthetics alone, with a very high degree of correlation (R.2= 0.995),
which is slightly greater than that found for the Meyer-Overton relation (Fig. 2A). While the anesthetidconvul-
sant tlurothyl also follows this trend, the non-anesthetics both do not. Rather, due to the polynomial nature of the
relation the minimum possible frequency that would lie on the curve is 594 THz, which is marginally greater than
both of the frequencies introduced by the non-anesthetics investigated, suggesting the non-anesthetics fall below
a cutoffrequired for anesthetic action. The biological importance of this range is not fully understood at this time.
The introduction of an agent also shifts the normal oscillatory modes of the aromatic dipoles by an order of
to 100 GHz (1GHz = 10°Hz). Figure 4A shows specific plots illustrating the shifts in the oscillation frequencies
of tubulin's aromatic amino acids for agents docked at each of the predicted tubulin binding sites. No correlation
between peak shift in frequency and binding site energy was found. The most prominent shift observed for all
the anesthetic agents was observed as a decrease in the normal mode of oscillation in the range of (613 ± 8) THz.
Both the biological significance of this range and the relevance of a decrease in oscillation frequency to anesthetic
action, versus an increase, require further investigation. The maximum frequency decrease in this range induced
by anesthetics correlates with MAC (R2= 0.999) (Fig. 4B). Flurothyl again followed the same trend as the anes-
thetics, while F6 and TFMB did not show any decreases in this range, but rather showed increases in oscillation
frequency. Of note is that the predicted MAC of the non-anesthetics is greater than 1000% atm well beyond phys-
iologically relevant concentrations, correctly predicting their lack of anesthetic action.
Discussion
Anesthesia is one of the great achievements of modern medicine, yet the mechanisms by which anesthetics selec-
tively block consciousness and memory formation, while sparing non-conscious brain activities, remain unclear
in spite of a century and a half of clinical use. Understanding anesthetic mechanisms may shed light on several
problems in consciousness studies, which would be an important scientific and philosophical achievement. More
practically, a better understanding of anesthesia can aid in clinical decisions to reduce the risk of adverse effects
including POCD, particularly in those suffering from neurodegenerative conditions, and/or lead to the rational
design and development of anesthetics with fewer deleterious side effects.
Yet how do anesthetic gases, a disparate group of volatile chemical compounds, exert a common, unitary
effect in all animals at concentrations specific to each gas? The Meyer-Overton correlation implies a unifying
factor related to the solubility of a gas in lipid-like, non-polar hydrophobic solvents. Binding in these solvents
occurs by very weak London dipole dispersion, a type of weak van der Waals force, but the significance of the
Meyer-Overton correlation remains elusive. Solubility in lipids alone does not account for the cut-off' effect2azs
anesthetic differences due to chirality", the lack of other lipid-altering effects to cause anesthesia", or the role of
membrane proteins in neuron excitability, leading to the conclusion that anesthetics act in non-polar, hydropho-
bic regions within proteins. Furthermore, there are exceptions to the Meyer-Overton rule where an agent's lipid
solubility predicts it to have a significant anesthetic potency, but it does not (i.e. P6, TFMB). These exceptions,
however, may provide insight into the mechanisms of anesthetics.
Examining how molecular polarizability correlates with anesthetic potency reveals a discontinuity with the
Meyer-Overton rule, specifically for the non-anesthetics F6 and TFMB. What is the difference in relation between
non-polar, 'lipid' solubility and polarizability such that these gases don't cause anesthesia? In this paper we investi-
gate this relationship and present a computational study aimed at examining the effect ofanesthetic, non-anesthetic,
and anesthetic/convulsant agent polarizabilities and permanent dipole moments on protein function.
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Flur En
a 7rIma F6 Moth Halo 11
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Ra a 0.995
p = 2e-6
0
0.10 1.00 10.00 100.00 1,000.00
Illabouon Mimes Concontraeon, MAC (% atm)
Figure 3. Collective dipole modes ofoscillation in tubulin. (a) Average energies of the collective dipole modes
of oscillation in tubulin. Gray - normal modes predicted for tryptophan, tyrosine and phenylalanine in tubulin
in the absence of agents. (Blue - additional normal modes introduced due to the presence of an anesthetic agent;
Red - additional normal modes introduced due to the presence of a non-anesthetic agent; Green - additional
normal mode introduced to the presence of the anesthetic/convulsant agent flurothyl). (b) Agent-induced new
frequency modes ofoscillation versus MAC. As the non-anesthetics fall below the trend line minimum there
is no predicted MAC for non-anesthetics available at any value. (Blue points - anesthetics; Red points - non-
anesthetics; Green points - anesthetidconvulsant; Red line - difference between non-anesthetic predicted and
actual (- I 00096 atm) MAC).
While membrane receptors and ion channel proteins are the assumed target of anesthetic action, genomic
and proteomic studiesm4s point to microtubules as a functional target of anesthetic action. Relating anesthetic
action to microtubules is relevant clinically because learning, memory, cognition, and the long-term potentia-
tion paradigm specifically require a cytoskeleton capable of complex reorganization to accommodate changes in
synaptic activity and strength''"". Furthermore, this suggests that anesthetic effects on microtubules which may
affect cytoskeleton stability may be a common mechanism for anesthesiaJ6. As neurodegenerative diseases share
the pathology of a dysfunctional neuronal cytoskeleton (e.g. Alzheimer's, Parkinson's etc.)°, and since the archi-
tecturally complex cytoskeletal matrix within neurons is responsible for neuron morphology and intracellular
transport, the interaction of anesthetics with tubulin and microtubules may be important for understanding the
effects of anesthesia-induced POCD. As dispersion forces tend to be stronger between molecules that are easily
polarized, and as these dispersion forces contribute to protein folding and protein-protein interactionsi8, the
effect of anesthetic polarizability on tubulin has implications for dynamics and stability of microtubules during
and after surgery. As such we focused our investigation on tubulin, the constituent protein of microtubules, as it
is a direct target of anesthetics, has explicit relevance to POCD in cytoskeleton-compromised neurodegenerative
disorders, and may be the site of a common, unitary mechanism of anesthesia.
Our results indicate that for anesthetics there is a very strong correlation between their potency and the shifts
they induce in the characteristic dipole collective modes in the tubulin dimer. Specifically we found tubulin aro-
matic amino acids alone to possess collective oscillations in networks of London-force dipoles among pi electron
resonance clouds of aromatic amino adds in the range of 480 to 700THz. The presence of an anesthetic (repre-
sented as an additional polarizable molecule in the aromatic network) creates another normal mode of the dipolar
oscillations. The introduction of an anesthetic also shifts the normal oscillatory modes of the dipoles downward
(slower) by an order of 1 to 100GHz. The most prominent shift observed for the anesthetics is situated around a
specific normal mode ofoscillation at (613 ± 8) THz. These new oscillatory modes introduced by anesthetics also
highly correlate with their anesthetic potency. Interestingly, non-anesthetics follow this trend with a predicted
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Figure 4. Change in tubulin collective dipole modes due to the addition of anesthetic/non-anesthetic molecules
for different binding sites. (a) Site specific changes for anesthetics and anesthetic/convulsant flurothyl shows
a prominent downwards shift at (613 ± 8) THz, while non-anesthetics F6 and TFMB show an increase at this
frequency band. (b) Maximum agent induced change in tubulin normal mode oscillation frequency at (613 ± 8)
THz versus agent MAC (Blue points - anesthetics; Red points - non-anesthetics; Green points - anesthetic/
convulsant).
MAC of well over 100% atmospheres, suggesting that this mechanism correctly distinguishes anesthetic and
non-anesthetic agents, a requirement for a common anesthetic mechanism. As the anesthetic/convulsant gas
fiurothyl also lies on this trend line with a clinically relevant MAC it must be noted that flurothyl can indeed
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produce anesthesia in mice at a MAC consistent with the Meyer-Overton correlation". The convulsions from
flurothyl appear at clinical concentrations an order ofmagnitude less than the MAC to cause loss ofconsciousness
suggesting an alternate mode and/or target of action for its convulsant properties".
Thus, alterations of the existing oscillatory modes in proteins by anesthetics may be a common mechanism
of action, which may tend to alter microtubule polymerization and function. The organizing behavior of mac-
romolecular entities, such as tubulin, indicates the existence of a complex and very fast information processing
activity". Indeed, modern experiments suggest that proteins are able to find their cognate partners at a rate
10-100 times faster than allowed by the stochastic dynamics of Brownian motion"`". One alternative to these
purely stochastic interactions is molecules that interact at long range by communicating signals. The assembly of
complex macromolecular biological systems from simpler building blocks, as in the case of microtubules, is often
driven by weak non-covalent van der Waals or dispersion interactions that arise from electrodynamic correlations
between instantaneous charge fluctuations in matter"."-".
Indeed, collective excitations and dispersion effects within other macromolecules of biological relevance have
been shown by recent experimentsV9-". These spectral features are commonly attributed to coherent oscillation
modes of the whole biomolecule or of a substantial fraction of its atoms. Computational studies of collective
electronic motions include normal modes62, quasi-harmonic modes'1•", and coarse-grain modes". Comparisons
between theory and experiment have yielded consistent results" favoring the presence of such collective
motion. These collective conformational vibrations, which are observed in the frequency range of 0.1-1000
Terahertz (THz), bring about oscillations of configurations ofelectric dipole moments with the calculated times-
cales for these correlated motions ranging from picoseconds to nanoseconds and beyond63.65.
The collective behavior of the dipole network is a degree of freedom not accounted for by the modeling ofsim-
ple Coulomb charges. The mode of interest, 613 THz, corresponds to -2.5 eV, in the visible blue range (489nm),
which is an order of magnitude stronger than typical binding interaction energies ( -0.2 eV, about 10 times ther-
mal energy, or kT). These collective dipole oscillations are a global effect due to synchronous/coherent elec-
tronic behaviors in tubulin, and such oscillations are energetically relevant by at least two orders of magnitude
beyond thermal noise. Theoretically, these long-range dipolar interactions between macromolecules are effective
when the interacting system is out of thermal equilibrium", as in most all biological cases. In such a system at
physiological temperature two molecules whose dipole moments are "on-resonance" oscillate at the same fre-
quency and undergo an attractive interaction that scales as r 3, where r is the distance between molecules". In the
"off-resonance" situation, such an attractive interaction produces a standard van der Waals-like potential scaling
as r 6. Such a frequency-selective interaction, when applied in a biological context such as tubulin selforganiza-
tion and polymerization, is of relevance during the approach of a molecule toward its interacting partner. Shifts in
the resonance patterns between tubulin dimers, such as by the addition of an anesthetic molecule as shown here,
could "mask" this long range recognition required for ideal polymerization rates by substantially changing the
distance dependence from a proportionality ofr 3 to r 6.
Thus, the effect ofanesthetic polarizability upon binding in protein hydrophobic pockets has real implications
for the general dynamics of protein-protein interactions. While complete depolymerization of microtubules is
not necessary for anesthesia, the presence of anesthetic molecules can serve to weaken the integrity of the micro-
tubule structure leading to decreased polymerization rates, thus affecting cytoskeletal reordering in learning,
memory, cognition, and long-term potentiation.
In regards to anesthetic action, high-frequency neural oscillations have been associated with conscious states,
while low-frequency activity has been associated with unconscious states". Coherence theories of anesthesia
suggest that general anesthetics act by disrupting coherent neuronal activity in critical brain structures". On a
finer scale, mechanics of individual microtubules contribute to neuronal shape and structure and the physical
processes underlying axonal growth cone and dendritic spine motility, as well as intracellular transport. Since
microtubule stiffness variation can affect whole cell morphology" and intracellular transport, this could lead
to changes in the timing of neuron firing and neuron function, resulting in a loss of coherence and ultimately
anesthesia. Controversial theories have been suggested that relate such microtubule processes directly to neural
coherence and consciousness"-73, but experimental confirmation is needed for validation of such claims. To date,
understanding London dispersion and van der Waals interactions in complex systems relies mostly on theoretical
concepts and the analysis of the results of computer modeling". While state-of-the-art experiments have pro-
vided strong evidence for the many-body nature of dispersion interactions in material surfaces and thin films,
it is expected that these effects only "scratch the surface" of the myriad of molecules and materials'. Compared
to idealized material surfaces and thin films, biomolecules are far more complex and present a significant chal-
lenge, as they are heterogeneous in nature and naturally reside in an aqueous environment. As such it would be
very challenging and beyond current capabilities to make precise enough measurements to detect polarizability
changes as a result of anesthetic binding to any protein.
Thus, with these observations in mind, and in the absence of other suitable single unitary mechanisms of
action, we conclude based on our results that anesthesia may be due to alteration of the dipolar oscillations of the
electronic degrees of freedom in aromatic molecules in proteins. Anesthetics have the ability to affect these col-
lective dipole oscillations and shift normal mode frequencies due to both their permanent dipoles and electrical
polarizabilities. We have examined the effect of anesthetics on the microtubule cytoskeleton due to its potential
role in POCD, and its potential to be a common unitary site of anesthetic action. Other proteins do exhibit col-
lective dipole modes in the THz regime, but the energies for the collective oscillations cover a different frequency
range owing to difference in the number and arrangement of polarizable amino acids (Le., for the DNA interact-
ing enzymes EcoRI, and Taq polymerase"). Thus, further tests on other candidate sites of anesthetic action (e.g.
GABAa, acetylcholine, serotonin, glutamate, glycine, a2-adrenergic, acetylcholine, or adenosine receptors) are
warranted to determine if this anesthetic effect is universal or unique to tubulin. While it remains to be seen if
this mechanism is general to all proteins, we have shown that this effect may take place in the aromatic networks
SCIENTIFIC RE PORTS17: 9877 IDOI:181038N41598-017-09992-7 8
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forming part of the structure of protein subcomponents of neuronal microtubules. Our proposed mechanism
may lead to the design and development of novel anesthetic molecules with greater potencies, faster clearance
rates, and other desirable properties, while remaining free of potentially detrimental side effects.
Methods
Anesthetic Binding Site Prediction. In previous work Craddock et aLn predicted putative binding sites
for volatile anesthetics on and between tubulin subunits in a microtubule B-type lattice using a combination of
homology modeling, molecular dynamics simulations and surface geometry techniques. The homology model
was constructed according to Carpenter et at" from the I JI7F79 and 1SA0" tubulin structures from the Protein
Data Bank" (www.rcsb.org) and simulated according to Craddock et al.n. The nine most persistent and prob-
able sites from the modeling predictions of Craddock et at'2 were used in the current study. The largest cluster
conformation of the tubulin dimer from the molecular dynamics simulations of Craddock et a1.77 was used for all
further calculations in this study.
Anesthetic Docking to Tubulin. Docking was performed with Molecular Operating Environment
(2015.10)" using the Alpha PMI placement method as it is fast and most suited to tight pockets. Each ligand was
docked separately in the regions around the nine most persistent and probable anesthetic-binding sites predicted
by Craddock et aLn. The ligand structures were then further refined using the food receptor option. This refine-
ment step is an energy minimization using the conventional Amber10:Extended Huckel Theory (EHT) molec-
ular mechanics force field to take electronic effects into account Partial charges were calculated and reassigned
accordingly. During this stage, solvation effects were also calculated using the reaction field functional form for
the electrostatic energy term with a dielectric constant equal to 4. The generalized Born solvation model (GB/
VI) was used at the end of the refinement step to estimate the final energy. The best conformations were selected
using the MOE's London AG scoring function to provide an estimate of the free energy of binding based on
the average gain/loss of rotational and translational entropy, the flexibility of the ligand and information about
hydrogen bonds. The conformation ofeach of the anesthetic and non-anesthetic molecules with the best score in
each of the nine binding regions was kept for further analysis such that nine final conformations were obtained
for each ligand.
Quantum Chemical Estimate of Molecular Polarizability Tensors. Quantum chemical estimates of
the molecular polarizability tensors were obtained for each anesthetic and non-anesthetic molecule in isolation
using the best conformation found in each of the nine binding pockets as described above. To calculate the polar-
izability tensors of the selected anesthetic and non-anesthetic molecules the density functional theory (DFT)
method was used with the long-range corrected functional CAM-B3LYP". This method was chosen as it has been
found to be very effective in predicting reliable values of polarizability". Calculations were performed with the
MAX basis set designed by Sadlej ei at for accurate predictions of molecular electric properties including dipole
moments and polarizabilities"-M. The basis sets were downloaded from http://www.qchins.uniba.sk/Baslib/POL
GAMESS-US99.94 was used for all calculations using the finite electric field perturbation methods"' with default
settings in the SFFCALC data group. For the DFT calculations the Janssen's grid JANS =2 was used, which gen-
erates about 71,000 grid points per atom.
Calculation of Collective Electronic Behavior. Networks of aromatic amino acids and polariza-
ble molecular agents were modeled as a set of interacting London-force dipoles. Collective dipole oscillations
between aromatic amino acids and anesthetic molecules were calculated by considering oriented dipole-dipole
interactions between constituent aromatics in the reference frame of tubulin-anesthetic complexes. Following
Kurian et Cli." ' SS, the polarizability tensors ofindole",phenol90, and benzene91-"' were used to represent the polar-
izability tensors of the amino adds tryptophan, tyrosine, and phenylalanine, respectively. Polarizability tensors
for the anesthetics, non-anesthetics and convulsants were determined as described above. The electronic angular
frequencies of induced dipole oscillations were determined as in". 99 from the fundamental dipole relation:
-. .--. -•
it = a • E (t)
Here, we only consider the diagonal elements of the polarizability tensors a w an, az:, and neglect off- diag-
onal terms. After alignment of the polarizabilities with the orientation of the aromatic amino acids in the protein
coordinate space, we take the magnitude of the mean polarizability to be 71 = l(an + a + a.) where the
induced dipole direction for each aromatic is defined by the vectors = (as, a ;'.7. aL) in thenprotein coordinate
frame.
The average angular frequency for the dipole oscillation is determined from w =d ca„+ 4+ ca2 , where
the elements of the angular frequency tensor for each amino-add dipole are determin from polarizability data
using:
ez
cal/ —
men:, (2)
where the mass im and charge e of an electron are used to approximate the charge-separated dipoles of the amino
acids.
Considering the collection of aromatics to be a network ofNharmonic oscillators coupled via induced dipole
interactions, the resulting Hamiltonian for such a collection ofNaromatic amino acid induced dipoles is then:
SCIENTIFIC REPORTS17: 9877 IDO1:181038/s41598-017-09992-7 9
EFTA00606076
H = T+ V
1 ill, ' fl - 3(4 • PnKi • g,„,) j
N-Iipl ,,2 N- t
m
. ....
E= 20‘
+ ad„
2
2) + -I2 „..„,E
„ ....,04ireo irssmi ( 3)
where the first term describes the kinetic energy of the system, the second term describes the harmonic oscillator
potentials with displacement coordinates a. = (x„, y„. z„)defined between each delocalized electron cloud and
its amino acid core, and the third term describes the pairwise interactions between each amino acid induced
dipole in the tubulin aromatic network
Pollowinezm the collective eigenmode frequencies for the oscillations are obtained from the symmetric lon-
gitudinal potential matrix V and the diagonal kinetic matrix T for the aromatic network. The problem then con-
sists of solving the characteristic equation for matrix eigenvalues:
det(V — H,T) = 0 (4)
Using numerical packages in Python, the eigenvalues of V were solved. As T is diagonal, these eigenvalues
correspond to mcf2„2.
Data availability. The datasets generated during and/or analyzed during the current study are available from
the corresponding author on reasonable request.
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Acknowledgements
TJAC would like to acknowledge financial support from the Department of Psychology and Neuroscience, the
Institute for Neuro-Immune Medicine at Nova Southeastern University (NSU), and the NSU President's Faculty
Research and Development Grant (PFRDG) program PFRDG 335426 (Craddock - PI). PK would also like to
acknowledge partial financial support from the Whole Genome Science Foundation. •this research was also partly
supported by a grant from NSERC (Canada) awarded to JAT. The opinions and assertions contained herein are
the private views of the authors and are not to be construed as official or as reflecting the views of the funding
agencies.
Author Contributions
T.J.A.C., S.R.H., and J.A.T. conceived of and designed the analysis. S.R.H. provided information on anesthetics,
non-anesthetics and convulsant agents. J.P. and KS. performed docking simulations. M.K. performed quantum
chemical calculations. P.K. performed the calculation of collective electronic behavior. T.J.A.C. prepared all
molecular structures, identified anesthetic sites and orientations, analyzed docking scores, polarizability data and
collective electronic behavior, and prepared all tables and figures. T.J.A.C., P.K., and J.A.T. interpreted all results.
T.J.A.C., P.K, S.R.H., and J.A.T. wrote the main manuscript text. All authors reviewed the manuscript and approve
of its content.
Additional Information
Supplementary information accompanies this paper at doi:10.1038/s41598-017-09992-7
Competing Interests: The authors declare that they have no competing interests.
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