Comparative Electroencephalographic Profile of a New Anesthetic and Anticonvulsant That is Selective for the GABA_AR Slow Receptor Subtype

Abstract

Background:

Anesthetics like propofol increase EEG power in delta frequencies (0.1 to 4 Hz), with a decrease of power in bandwidths above 30 Hz. Propofol is non-selective for gamma amino butyric acid type A receptor subtypes (GABA_AR) as it enhances all three GABA_AR subtypes (slow, fast, and tonic). Our newly developed anesthetic class selectively targets GABA_AR-slow synapses to depress brain responsiveness. We hypothesized that a selective GABA_AR -slow agonist, KSEB 01-S2, would produce a different EEG signature compared to the broad spectrum GABA_AR agonist (propofol), and tested this using rat EEG recordings.

Methods:

Male rats were studied following IACUC approval from the US Army Medical Research Institute of Chemical Defense and the University of Michigan. Rats were anesthetized using isoflurane (3-5% induction, 1-3% maintenance) with oxygen at 0.5-1.0 L/min. Stainless steel screws were placed in the skull and used to record subcranial cortical EEG signals. Following recovery, either propofol or KSEB 01-S2 was administered and effects on EEG signals were analyzed.

Results:

As previously reported, propofol produced increased power in delta frequencies (0.1 to 4 Hz) compared to pre-drug recordings and produced a decrease in EEG power above 30 Hz but no significant changes were seen within ±20 seconds of losing righting reflex. By contrast, KSEB 01-S2 produced a significant increase in theta frequency percent power (median 14.7 %, 16.2/13.8, 75/25 CI; to 34.7 %, 35/31.8; p < 0.015) and a significant decrease in low gamma frequency percent power (16.9 %, 18.6/15.8; to 5.45%, 5.5/5.39; p < 0.015) for all rats at ± 20 seconds of LOC. Both anesthetics produced a flattening of chaotic attractor plots from non-linear dynamic analyses, like that produced by volatile and dissociative anesthetics at LOC.

Conclusion:

KSEB 01-S2 produced a markedly different EEG pattern, with a selective increase observed in the theta frequency range. KSEB 01-S2 also differs markedly in its activity at the GABA_AR-slow receptor subtype, suggesting a possible mechanistic link between receptor subtype specificity and EEG frequency band signatures. Increased theta together with depressed gamma frequencies are interesting because GABA_AR slow synapses have previously been suggested to underlie theta frequency oscillations, while fast synapses control gamma activity. These reciprocal effects support a previous model for theta and nested gamma oscillations based on inhibitory connections between GABA_AR fast and slow interneurons. Although each anesthetic produced a unique EEG response, propofol and KSEB 01-S2 both increased slow wave activity and flattened chaotic attractor plots at the point of LOC.

INTRODUCTION

Electroencephalography (EEG) is often used for a rigorous and quantitative measure of depth of anesthesia or unconsciousness. Clinically, EEG-derived indices have been used and tested to quantify anesthetic depth. These include bispectral index (BIS), Sedline, EEG Entropy, and Spectral Edge Frequency (SEF)^1-5. More recently, we have developed a very robust methodology for the characterization of the anesthetized state using Chaos Theory-based processing of EEG signals that, unlike many other indices of limited application, allows the characterization of unconsciousness across agents that act at both NMDA receptors as well as the gamma amino butyric acid-A receptor (GABA_AR)^6,7. This is critically important for clinical considerations as most anesthetic regimens often contain a mix of agents with activities at both of these receptors.

In particular, propofol has been shown to increase slow wave EEG activity and depress higher frequency responses. Its mechanism involves a specific interaction with a binding site in the outer third of the transmembrane domain within GABA_AR, a site of interaction that has been extensively characterized by our group⁸. It has been further shown to have nonspecific effects on both the “slow” and “fast” subtypes of this receptor⁹. Propofol and etomidate are positive allosteric modulators of GABA_ARs. Although propofol is an effective anesthetic and anticonvulsant, it has significant detrimental side effects that include both respiratory and hemodynamic depression^10,11. The latter has been a focus in the literature and is associated with significant costs related to enhanced perioperative morbidity and mortality^12-15. To advance safer anesthetic practice, we developed a promising class of agents that selectively modulate the “slow” subtype of the GABA_AR⁹.

The development of KSEB 01-S2 was based on the results of in silico docking to our validated model of the GABA_AR (Figure 1A and 1B), as discussed in our previous work⁹. Modeling revealed reasonable docking scores that were comparable to those of propofol and etomidate at the GABA_AR, suggesting potential for comparable in vitro activity with subsequent clinical activity in similar dosing ranges. This is a completely novel class of IV anesthetic (Figure 1D) with low micromolar/high nanomolar potencies in vitro. It produces potent in vivo states of sedation through anesthesia for tadpoles and rats. In rats, it lacks hemodynamic, respiratory and adrenal depression. KSEB 01-S2 (also known as compound BB in previous work) is the first agent to have well described specificity for the GABA_AR slow subtype. KSEB 01-S2 is among the first anesthetics to have effects characterized in cardiomyocytes where it also demonstrates effects similar to the hemodynamic preservation of etomidate and not the detrimental effects of propofol¹⁶. KSEB 01-S2 is also found to have potent therapeutic anticonvulsant effects, most notably against the potentially fatal status epilepticus induced by weaponized chemical nerve agents¹⁷. Finally, KSEB 01-S2 shows preliminary data suggestive of mitochondrial protection in a manner that is favorably similar to propofol¹⁸.

Figure 1:

Development and testing of anesthetics that target the propofol and etomidate binding site on GABA_AR. Anesthetics are known to bind at an interface between subunits GABA_AR (A). We developed a new series of anesthetics that were designed for optimal fit into this known binding site (B). Our new anesthetics were highly selective for enhancing channel opening of synaptic GABA_AR ‘slow’ receptors. The effects of ‘slow’ receptor enhancement on behavior and brain electrical activity were studied using parietal cortex (PC) intracranial EEG recordings in freely moving rats (C; y-axis power 0 to 100 μV²). Recorded signals were processed for effects on spectral and nonlinear dynamic (Chaotic Attractor) properties of the signals. (D) Rod and stick chemical representations of KSEB 01-S2.

Here, we quantitatively compare the EEG effects of one such compound, KSEB 01-S2, and propofol, on both traditional spectral measures and our new Chaotic Attractor method. We hypothesized that since KSEB 01-S2 has selective activity at the GABA_AR-slow subtype along with minimal cardiorespiratory depression, it may also have many unique EEG effects compared to propofol. However, we also hypothesized that given its similar ability to produce anesthesia, the Chaotic Attractor measure of anesthetic depth should be similar to that of propofol. Despite having a common anesthetic phenotype as well as chaotic attractor characteristic on EEG, the otherwise unique EEG profile of KSEB 01-S2 as well as its lack of cardiorespiratory depression may be mechanistically related to its differential effects on the GABA_AR -slow functional receptor subtype. It should be noted that the GABA_AR-slow was not targeted, since subunit stochiometry remains unknown, however, KSEB 01-S2, as well as etomidate were subsequently shown to selectively modulate GABA_AR-slow in electrophysiologic assays.

METHODS

Development of KSEB 01-S2

The development of our compound, KSEB 01-S2, has been discussed in greater detail previously⁹, where it was referred to by an older nomenclature as ‘compound BB’. In brief, we developed a molecular model of the GABA_AR (Figure 1A and 1B) with a well-defined and validated binding site for a variety of anesthetics including propofol and etomidate. This model was subsequently further demonstrated in the cryoEM structures published from the work of Kim et. al.¹⁹ This binding site is located in the outer third of the transmembrane domain and is bound by three critical residues that, when mutated, have been shown to alter anesthetic modulation of the GABA_AR. These three subunit locations are alpha1-LEU232, beta3-ASN265, and beta3-MET289. We then used high throughput molecular docking via the CHARMm Forcefield within the Discovery Studio software suite (Dassault Systemes, San Diego, CA) to screen various compound databases to arrive at a class of lead compounds that are N-arylpyrrole derivatives with favorable in silico docking scores. Electrophysiological analyses using an in vitro expression system with intact rodent hippocampal brain slice recordings demonstrated a GABA_AR-mediated mechanism specific to the “slow” receptor subtype. In vivo experiments also demonstrate overt anesthetic activity in both tadpoles and rats with a potency greater than that of propofol⁹. Unlike the clinically approved GABAergic anesthetic etomidate, the chemical structure of our N-arylpyrrole derivative is devoid of the chemical moieties producing adrenal suppression. In rats this class of compounds also shows minimal to no suppression of blood pressure or respirations, in marked contrast to the effects of propofol. Solubilization studies were performed by Pharmatek, inc (now Catalent, inc) and involved a proprietary assembly of solvents (involving PEG300, water, Pharmsolve, Ethanol, Solutol), for proper administration to rats.

EEG Recordings from Rats (Figure 1C)

Animals:

We studied adult male Sprague Dawley rats (n = 6; 300 – 350 gm) purchased from Charles River Laboratories. Rats were single-housed in a temperature and humidity-controlled facility with lights on at 0600 and lights off at 1800. They were provided with food and water ad libitum except during experimental procedures. The experimental protocols were approved by their respective Institutional Animal Care and use Committees (IACUC) at the United States Army Medical Research Institute of Chemical Defense or the University of Michigan. All procedures were conducted in accordance with the principles stated in the Guide for the Care and Use of Laboratory Animals, and the Animal Welfare Act of 1966 (P. L. 89-544).

Surgery:

At least 7 days after catheter implantation, stainless steel screw electrodes were implanted over the parietal cortex (differential recording electrodes) and unilaterally over cerebellum (ground) to enable EEG recordings. Screw electrodes were connected to a plug that was affixed to the skull with glass ionomer dental cement. Aseptic techniques were utilized, and rats were anesthetized with isoflurane (3-5% for induction, 1-3% for maintenance) throughout the procedure. Meloxicam (1 mg/kg, SC) was given ~30 min prior to surgery and again 24 hours later for pain management. After full recovery from anesthesia, rats were returned to their home cage and monitored daily for 5-7 days prior to testing of propofol or KSEB 01-S2.

EEG Recording:

We recorded approximately one hour of freely behaving baseline activity before the experimental procedures described below. The EEG signal was amplified, recorded, and visualized with a system from Cambridge Electronic Designs (CED) that consisted of a 1902 amplifier, a Micro1401 data acquisition interface, and Spike2 software. Data were sampled at 512 Hz and digitally filtered with a 0.3 Hz high-pass filter, a 100 Hz low pass filter, and a 60 Hz notch filter.

Drug Administration:

Seven days after EEG implant surgery, rats were connected to the EEG recording system. KSEB 01-S2 was formulated with a concentration of 10 mg/ml. Propofol (Diprivan; 880 μg/Kg/min until LORR, usually ~ 20 min) or KSEB 01-S2 (10 mg/Kg) were delivered in sterile saline through intra-jugular catheters. During and following the injection, rats were visually and physically observed for signs of sedation such as uncoordinated movement or loss of muscle tone. Their righting reflex was assessed by gently rolling them on their back. Righting reflex was deemed to be lost if they were unable to place at least 3 feet on the floor of the cage within 60 seconds. Righting reflex was considered to have returned when rats could successfully right themselves within 60 seconds two times in a row. The EEG recording was terminated after all rats in a recording session had regained their righting reflex and consistently displayed a normal, awake EEG pattern (low amplitude, mixed frequency, no sharp waves). They were then returned to their home cage.

EEG Analysis:

EEG signals were analyzed for spectral properties using the MatLab (Mathworks, Natick, Massachusetts), Chronux toolbox. A time-bandwidth product of 5, 9 tapers was applied to 20 second long EEG segments, bandpass filtered from 0 to 50 Hz. Power spectral density plots were generated, and error ranges were computed using a theoretical estimate method at 0.05 significance levels. Power values are expressed in decibels (dB). We computed normalized spectrograms and a Fourier transform (using the FFT function in MatLab, performed using Hann windows with half window overlap. Magnitude values were converted to dB and spectrograms were normalized to their maximum magnitude. Total power and spectral edge frequency (SEF, frequency below 95% of the total power) were calculated using multitaper analysis. Percentage of total power for individual frequency bands were also calculated across behavioral conditions (pre- and post-LORR, pre- and post-RORR). Frequency bands were defined as per previous studies: delta: 1 to 4 Hz; theta: 4 to 8 Hz; alpha: 8 to 12 Hz; beta: 12 to 25 Hz; and gamma: 25 to 50 Hz. ²⁰

Dynamical attractor plots of three-dimensional, time-delayed embeddings (4.0 ms) of the same EEG segments used for spectral measures were analyzed for correlation dimensions by dividing the shortest axis of each plot by the longest axis and expressing this as a ratio. For an awake EEG signal that produced a nearly spherical plot, the ratio would be close to 1.0, but the flattened attractor plot (ellipsoid) associated with LORR produced ratios of ~0.3 (see results Fig 7). Axis dimensions were determined from Eigenvector analysis of each 3-D attractor plot calculated using Igor Pro software (Wavemetrics, Portland, OR).

Figure 7:

Frequency analysis plots with corresponding chaotic attractor plots showing the transitions from the awake state, to anesthetized state, and back to a recovered awakening state produced by KSEB. 01-S2.

Statistical Analysis:

Cohen’s D for paired-data of EEG measures were compared before and after (20 seconds, respectively) LORR and before and after (20 seconds) RORR for spectral edge frequency, total power, and percentage of power in each frequency band (delta, theta, alpha, beta, and gamma). Significance values were determined using MatLab from Wilcoxon signed rank tests, corrected for multiple comparisons and a significance of p < 0.05 following correction.²⁰. Significance across multiple comparisons for each analysis type was corrected using a Holm-Bonferroni method (MatLab) with a sequential-rejective procedure ²⁰. A Student’s T test was used for paired measures of dynamical attractor plot ratios using Igor Pro software.

RESULTS

Electroencephalography effects of anesthetics

Propofol EEG analyses (figure 2) shows increased delta frequencies, increased power across frequencies from 0.5 to 20 Hz, but depressed slow wave rhythms (< 0.5 Hz) compared to pre-drug recordings. Propofol increased delta frequency activity (1 to 4 Hz) as well as theta, alpha and beta frequencies, but had little effect on gamma activity (30 to 40 Hz). KSEB 01-S2 also increased delta activity and dramatically increased theta activity (4 to 8 Hz; C), but also had relatively minor effects on gamma⁹, for both drugs compared to pre-drug recordings.

Figure 2:

Spectral density (SD Power) changes before (red) and after (blue) LORR are shown for two frequency ranges produced by propofol (A - 0 to 20 Hz; and B - 30 to 40 Hz) and by KSEB (C & D). Propofol increased delta frequency activity (1 to 4 Hz) as well as theta, alpha and beta frequencies, but had little effect on gamma activity (30 to 40 Hz; B). KSEB 01-S2 also increased delta activity and dramatically increased theta activity (4 to 8 Hz; SD Power; 0 to 100 μV² – A; 0 to 20 μV² – B & D; 0 to 200 μV²-C), but also had relatively minor effects on gamma (D).

The EEG power spectrum effects (Figure 3A and 3B) produced by propofol were compared to those produced by KSEB 01-S2 for recorded signals from 3 rats at the behavioral endpoint of loss of righting reflex (LORR) in each rat. Twenty second recordings are shown in the top traces of each panel before (Pre-LORR) and after (Post-LORR) each rat lost its ability to right itself. Below each trace is a spectrogram showing Local Field Potential frequency changes over the course of each twenty-second-long recording. The right side of each panel shows an average fast Fourier transform (FFT) for the twenty second recordings. Propofol (A) consistently increased the power of delta frequency activity (1 to 4 Hz; green arrows) at LORR and decreased low frequency activity (< 0.5 Hz; pink arrows). Increases in power are shown by warmer colors in the spectrograms. KSEB 01-S2 also increased delta frequency activity at LORR but produced a marked increase in theta activity (4 to 8 Hz; green arrow in B) that was not produced by propofol. KSEB 01-S2 did not produce the decrease in low frequency activity that was seen with propofol. Unlike the previous comparisons of pre-drug vs LORR changes produced by propofol, the pre-LORR vs post-LORR measures, while consistent for individual mice, did not produce significant differences for the combined data. This is consistent with our previous findings ²¹ when comparisons are made immediately before and after LORR.

Figure 3:

The EEG power spectrum effects produced by propofol (A) in comparison to those of KSEB01-S2 (B). Three horizontal panels in E and F are for each of 3 rats studied.

Propofol did not significantly alter spectral edge frequency (SEF), median frequency or total power across LORR in rats (Figure 4). In contrast, KSEB significantly decreased SEF (pre - 55.5, 66.7/48.2; to post – 35.4, 37.5/32.2; median, 75th/25th percentile; p < 0.04), and significantly increased total power (41.25, 42.2/40.6; to 46.3, 48/46.3; p< 0.04) mainly by increasing theta frequency power shown in Figures 4 and 5) The effects produced by vehicle injection are shown for comparison. Twenty second recordings were processed at vehicle post injection times that were comparable to those when LORR was seen following propofol and KSEB 01-S2 injections. No significant effects were seen.

Figure 4:

Differential effects of propofol, KSEB 01-S2 and vehicle on spectral edge frequency (SEF), median frequency and total power across LORR in all rats. Note that the only significant effects were produced by KSEB, neither propofol nor vehicle produced changes and, of course, no change in righting was produced by vehicle. Although the KSEB effect on Median Frequency approached significance (p < 0.06), more experimental subjects (i.e. > 3 rats) would be needed.

Figure 5:

Effects of propofol, KSEB 01-S2 and vehicle on power across multiple frequency bands both before and after LORR. Although several measured parameters approach significance, only KSEB’s effects on theta and gamma frequency power were significant (p < 0.05).

Propofol did not significantly alter the percent power in any frequency band across LORR (figure 5) for all rats. KSEB 01-S2 produced a significant increase in theta frequency activity (14.7, 16.2/13.8; to 34.7, 35/31.8; p < 0.015) and a significant decrease in low gamma frequency activity (16.9, 18.6/15.8; to 5.45, 5.5/5.39; p < 0.015) in all rats across LORR. No significant changes were produced by KSEB for delta, alpha, beta or high gamma frequencies.

Interestingly, despite the differential effects on other aspects of EEG characterizations as well as cardiorespiratory physiologies, Chaotic Attractor Analyses (Figure 6A and 6B) showed that at LORR there is a consistent flattening of the attractors for both propofol and KSEB 01-S2 when comparing twenty second EEG recordings before (Pre-LORR) to after loss of response (Post-LORR).

Figure 6:

Attractor plots from chaos analysis for rats administered propofol (A) or KSEB 01-S2 (B). Chaotic attractor eigenvector analyses (C) for propofol and KSEB 01-S2 showing the similar effects of both agents in the transition from the partially sedated state to the fully unconscious state associated with LORR.

Both propofol and KSEB 01-S2 produced significant flattening (paired t-test; p < 0.01; Figure 6C) of the attractors across the 40 second transition in EEG signals from the sedated state to LORR. Neither agent produced burst suppression activity at LOC.

DISCUSSION

KSEB 01-S2 development:

All currently used intravenous anesthetic agents are associated with a spectrum of undesirable side effects, most notably cardiovascular instabilities. These adverse effects can be poorly tolerated in all surgical patients without our intervention, but especially in patients with tenuous physiologies. Such tenuous physiologies characterize any of a multitude of infirmities including but not limited to hemodynamic instabilities (whether due to chronic illness or acute traumatic injury), respiratory depression, or baseline neurocognitive deficiencies. Such conditions may also relate to extremes of age, with pediatric patients often having immature compensatory capabilities and the geriatric patient having potentially compromised or exhausted compensatory physiologic reserve. We have therefore pursued the development of new lead compounds to produce the next generation of safer anesthetic agents. Our methodologies of in silico screening of compounds that bind to our model of the GABA_AR have identified a class of lead compounds that demonstrate anesthetic activity in both tadpoles and rats with a potency greater than that of propofol. These structures are devoid of the chemical moieties known to produce adrenal suppression, the dreaded side effect of etomidate. Importantly, our new class of compounds shows minimal to no depression of blood pressure and respiration, in stark contrast to propofol. Electrophysiologic analyses from both ion channel patch clamp studies as well as in vitro rat hippocampal brain slice recordings are consistent with a GABA_AR slow receptor subtype mediated mechanism. These compounds are derived from novel chemical structures and are the subject of patent filings through the Offices of Technology and Licensing from both Stanford University and the US Department of Veterans Affairs²².

The Important Distinction of the Three Functional GABA_AR Subtypes:

Three functional subtypes of GABA_ARs are characterized by their different cellular locations, agonist sensitivities and the kinetics of the chloride channels that they gate^23-25. They are termed GABA_AR-tonic, GABA_AR-fast and GABA_AR-slow. GABA_AR-tonic are located in non-synaptic regions of the cell membrane, throughout the dendritic arbor, on the cell body, on presynaptic nerve terminals, and even on non-synaptic regions of axons.²⁶ They are very sensitive to low, nanomolar concentrations of GABA, found in the interstitial CSF surrounding neurons and glia. Tonic receptors gate chloride channels that remain open for as long as GABA is bound to them, producing a sustained (tonic) current that can last for seconds or longer. The other two subtypes of GABA_ARs are both phasic (GABA_AR-fast and GABA_AR-slow) in that they produce transient channel openings lasting only several milliseconds when GABA is bound to their receptors, yet with different onset and offset characteristics. These subtypes are located only at synapses, usually in dendritic membrane regions, but also at the axon hillock region. These phasic receptors are less sensitive to the agonist, GABA, requiring high micromolar or even millimolar concentrations of agonist to open their chloride channels. This occurs with the transient release of high concentrations of GABA from synaptic nerve terminals. The two subtypes of phasic receptors differ not only in their chloride channel gating kinetics but also in their location²⁵. GABA_AR-fast are found at synapses coming from the most common types of interneurons (somatostatin positive, CCK positive, basket cells, chandelier cells etc.) that mediate rapid feedback and feed forward inhibition. GABA_AR-slow are found at synapses coming from ivy cells and neurogliaform interneurons, usually in dendritic regions, and mediate modulatory inhibition of excitatory synaptic inputs. GABA_AR-fast receptors gate channels that open quickly (< 1 ms) and close quickly (t_1/2 decay times < 20 ms), while GABA_AR-slow gate channels that open slower (2 to 3 ms) and close much slower (t_1/2 decay times >50 to 100 ms). Tonic, GABA_AR-fast, and slow receptors are all thought to be made up of different combinations of GABA_AR subunit proteins (e.g. alpha, beta, gamma, and delta subunits etc.) totaling to 19 different subunit types, although the stoichiometry of subunit arrangements within each pentameric channel for these functional subtypes remains to be determined.

Reciprocal inhibitory connections between GABAergic interneurons that exhibit fast vs slow synaptic currents have been proposed to account for the nesting of gamma oscillations on the peak of theta rhythms ²⁴. Fast interneurons are thought to drive gamma frequency oscillations in pyramidal neurons, while slow interneurons subserve theta frequency oscillations. A selective increase in slow inhibition would increase theta, but because of the reciprocal inhibition of fast interneurons, it would depress gamma oscillations. This is consistent with the effects we observed (figure 5).

It is the GABA_AR-slow subtype at which KSEB 01-S2 selectively acts, similar to etomidate but unlike propofol, which acts nonselectively at all types of GABA_AR’s⁹. This may explain the common lack of cardiovascular effects of etomidate and KSEB 01-S2. This suggests that these unwanted side effects could be due to propofol actions on GABA_AR-fast and/or GABA_AR-tonic currents, while actions on GABA_AR-slow currents cause sedation and LOC.

Chaos Attractor Index Provides a Better Measure of Anesthesia Across Several Anesthetic Types with Differing Receptor Mechanisms:

A chaotic attractor index provides a better, more consistent, and sensitive measure of brain state changes that occur at loss of consciousness and surgical planes of anesthesia, compared to traditional spectral based measures (BIS, SedLine, Entropy, etc.) ^7,27. The index measures a flattening of chaotic attractor plots using a simple ratio of the length and width of plots from several second long segments of EEG recordings. In awake patients, chaotic attractor plots are nearly circular, representing the 360 degrees of freedom that the brain electrical activity can explore. At loss of consciousness, the attractor plots flatten in the width dimension, producing a lower numerical index. Similarly, at deeper surgical planes of anesthesia the attractor plots flatten even more (figure 7), resulting in a very low numerical index. The flattening of attractor plots is observed in humans^20,28 and rodents ⁶ and other animals ^29,30 , suggesting common mechanisms of anesthetic action across species.

We hypothesized that a selective GABA_AR-slow agonist, KSEB 01-S2, would produce a different set of EEG frequency band signatures, and this proved correct. Propofol and KSEB 01-S2 also differ markedly in their activities at the GABA_AR-slow receptor subtype, suggesting a possible mechanistic link between receptor subtype specificity, EEG frequency band signatures and their differing cardiorespiratory stabilities. However, despite these differences with propofol, KSEB 01-S2 has a similar chaos attractor measure of anesthetic effect to that of propofol along with a similar ability to produce the anesthetic phenotype. Like propofol, KSEB 01-S2 produces a consistent flattening of the chaotic attractor index but contrastingly spares cardiorespiratory depression in the rat. This puts this new class of agents on track for the development of a safer anesthetic, especially for those in extremis, with a further focus on the GABA_AR-slow receptor subtype for more efficacious drug design.

KEY POINTS:

Questions:

What are the electroencephalographic and physiologic profiles of a new anesthetic and anticonvulsant that is selective for the GABA_AR slow receptor subtype as compared to that of propofol?

Findings:

Compared to propofol, KSEB 01-S2 produces a different set of EEG frequency band signatures, has a similar chaos attractor measure of anesthetic effect as well as a similar ability to produce the anesthetic phenotype, but contrastingly spares cardiorespiratory depression in the rat.

Meaning:

Our new class of agents are unique in their activities at the GABA_AR-slow receptor functional subtype while producing effective Chaos Attractor measures of anesthesia, suggesting a possible mechanistic link between receptor subtype specificity, EEG frequency band signatures and improved cardiorespiratory stabilities.