Edward J. Bertaccini

Correlation of approximate entropy, bispectral index, and spectral edge frequency 95 (SEF95) with clinical signs of "anesthetic depth" during coadministration of propofol and remifentanil.

Background Several studies relating electroencephalogram parameter values to clinical endpoints using a single (mostly hypnotic) drug at relatively low levels of central nervous system depression (sedation) have been published. However, the usefulness of a parameter derived from the electroencephalogram for clinical anesthesia largely depends on its ability to predict the response to stimuli of different intensity or painfulness under a combination of a hypnotic and an (opioid) analgesic. This study was designed to evaluate the predictive performance of spectral edge frequency 95 (SEF95), BIS, and approximate entropy for the response to increasingly intense stimuli under different concentrations of both propofol and remifentanil in the therapeutic range. Methods Ten healthy male and ten healthy female volunteers were studied during coadministration of propofol and remifentanil. After having maintained a specific target concentration for 10 min, the depth of sedation–anesthesia was assessed using the responsiveness component of the Observers Assessment of Alertness/Sedation (OAA/S) rating scale, which was modified by adding insertion of a laryngeal mask and laryngoscopy. The electroencephalogram derived parameters approximate entropy, bispectral index, and SEF95 were recorded just before sedation level was assessed. Results The prediction probability values for approximate entropy were slightly, but not significantly, better than those for bispectral index, SEF95, and the combination of drug concentrations. A much lower prediction ability was observed for tolerance of airway manipulation than for hypnotic endpoints. Conclusion Approximate entropy revealed informations on hypnotic and analgesic endpoints using coadministration of propofol and remifentanil comparable to bispectral index, SEF95, and the combination of drug concentrations.

A Double-blind, Randomized Comparison of IV Lorazepam versus Midazolam for Sedation of ICU Patients via a Pharmacologic Model

Background Benzodiazepines, such as lorazepam and midazolam, are frequently administered to surgical intensive care unit (ICU) patients for postoperative sedation. To date, the pharmacology of lorazepam in critically ill patients has not been described. The aim of the current study was to characterize and compare the pharmacokinetics and pharmacodynamics of lorazepam and midazolam administered as continuous intravenous infusions for postoperative sedation of surgical ICU patients. Methods With Institutional Review Board approval, 24 consenting adult surgical patients were given either lorazepam or midazolam in a double-blind fashion (together with either intravenous fentanyl or epidural morphine for analgesia) through target-controlled intravenous infusions titrated to maintain a moderate level of sedation for 12–72 h postoperatively. Moderate sedation was defined as a Ramsay Sedation Scale score of 3 or 4. Sedation scores were measured, together with benzodiazepine plasma concentrations. Population pharmacokinetic and pharmacodynamic parameters were estimated using nonlinear mixed-effects modeling. Results A two-compartment model best described the pharmacokinetics of both lorazepam and midazolam. The pharmacodynamic model predicted depth of sedation for both midazolam and lorazepam with 76% accuracy. The estimated sedative potency of lorazepam was twice that of midazolam. The predicted C50,ss (plasma benzodiazepine concentrations where P(Sedation ≥ ss) = 50%) values for midazolam (sedation score [SS] ≥ n, where n = a Ramsay Sedation Score of 2, 3, . . . 6) were 68, 101, 208, 304, and 375 ng/ml. The corresponding predicted C50,ss values for lorazepam were 34, 51, 104, 152, and 188 ng/ml, respectively. Age, fentanyl administration, and the resolving effects of surgery and anesthesia were significant covariates of benzodiazepine sedation. The relative amnestic potency of lorazepam to midazolam was 4 (observed). The predicted emergence times from sedation after a 72-h benzodiazepine infusion for light (SS = 3) and deep (SS = 5) sedation in a typical patient were 3.6 and 14.9 h for midazolam infusions and 11.9 and 31.1 h for lorazepam infusions, respectively. Conclusions The pharmacology of intravenous infusions of lorazepam differs significantly from that of midazolam in critically ill patients. This results in significant delays in emergence from sedation with lorazepam as compared with midazolam when administered for ICU sedation.

Non–steady State Analysis of the Pharmacokinetic Interaction between Propofol and Remifentanil

Background The pharmacokinetics of both propofol and remifentanil have been described extensively. Although they are commonly administered together for clinical anesthesia, their pharmacokinetic interaction has not been investigated so far. The purpose of the current investigation was to elucidate the nature and extent of pharmacokinetic interactions between propofol and remifentanil. Methods Twenty healthy volunteers aged 20–43 yr initially received either propofol or remifentanil alone in a stepwise incremental and decremental fashion via a target controlled infusion. Thereafter, the respective second drug was infused to a fixed target concentration in the clinical range (0–4 &mgr;g/ml and 0–4 ng/ml for propofol and remifentanil, respectively) and the stepwise incremental pattern repeated. Frequent blood samples were drawn for up to 6 h for propofol and 40 min for remifentanil after the end of administration and assayed for the respective drug concentrations with gas chromatography–mass spectrometry. The time courses of the measured concentrations were fitted to standard compartmental models. Calculations were performed with NONMEM. After having established the individual population models for both drugs and an exploratory analysis for hypothesis generation, pharmacokinetic interaction was identified by including an interaction term into the population model and comparing the value of the objective function in the presence and absence of the respective term. Results The concentration–time courses of propofol and remifentanil were described best by a three- and two-compartment model, respectively. In the concentration range examined, remifentanil does not alter propofol pharmacokinetics. Coadministration of propofol decreases the central volume of distribution and distributional clearance of remifentanil by 41% and elimination clearance by 15%. This effect was not concentration-dependent in the examined concentration range of propofol. Conclusions Coadministration of propofol decreases the bolus dose of remifentanil needed to achieve a certain plasma–effect compartment concentration but does not alter the respective maintenance infusion rates and recovery times to a clinically significant degree.

Microsecond simulations indicate that ethanol binds between subunits and could stabilize an open-state model of a glycine receptor.

Cys-loop receptors constitute a superfamily of ion channels gated by ligands such as acetylcholine, serotonin, glycine, and γ-aminobutyric acid. All of these receptors are thought to share structural characteristics, but due to high sequence variation and limited structure availability, our knowledge about allosteric binding sites is still limited. These sites are frequent targets of anesthetic and alcohol molecules, and are of high pharmacological importance. We used molecular simulations to study ethanol binding and equilibrium exchange for the homomeric α1 glycine receptor (GlyRα1), modeled on the structure of the Gloeobacter violaceus pentameric ligand-gated channel. Ethanol has a well-known potentiating effect and can be used in high concentrations. By performing two microsecond-scale simulations of GlyR with/without ethanol, we were able to observe spontaneous binding in cavities and equilibrium ligand exchange. Of interest, it appears that there are ethanol-binding sites both between and within the GlyR transmembrane subunits, with the intersubunit site having the highest occupancy and slowest exchange (∼200 ns). This model site involves several residues that were previously identified via mutations as being crucial for potentiation. Finally, ethanol appears to stabilize the GlyR model built on a presumably open form of the ligand-gated channel. This stabilization could help explain the effects of allosteric ligand binding in Cys-loop receptors.

Evidence that ethanol acts on a target in Loop 2 of the extracellular domain of α1 glycine receptors

Considerable evidence indicates that ethanol acts on specific residues in the transmembrane domains of glycine receptors (GlyRs). In this study, we tested the hypothesis that the extracellular domain is also a target for ethanol action by investigating the effect of cysteine substitutions at positions 52 (extracellular domain) and 267 (transmembrane domain) on responses to n‐alcohols and propyl methanethiosulfonate (PMTS) in α1GlyRs expressed in Xenopus oocytes. In support of the hypothesis: (i) The A52C mutation changed ethanol sensitivity compared to WT GlyRs; (ii) PMTS produced irreversible alcohol‐like potentiation in A52C GlyRs; and (iii) PMTS binding reduced the n‐chain alcohol cutoff in A52C GlyRs. Further studies used PMTS binding to cysteines at positions 52 or 267 to block ethanol action at one site in order to determine its effect at other site(s). In these situations, ethanol caused negative modulation when acting at position 52 and positive modulation when acting at position 267. Collectively, these findings parallel the evidence that established the TM domain as a target for ethanol, suggest that positions 52 and 267 are part of the same alcohol pocket and indicate that the net effect of ethanol on GlyR function reflects the summation of its positive and negative modulatory effects on different targets.

Meperidine exerts agonist activity at the α2B-adrenoceptor subtype

Background The opioid agonist meperidine has actions, such as antishivering, that are more pronounced than those of other opioid agonists and that are not blocked with nonselective opioid antagonists. Agonists at the &agr;2 adrenoceptors, such as clonidine, are very effective antishivering drugs. Preliminary evidence also indicates that meperidine interacts with &agr;2 adrenoceptors. The authors therefore studied the ability of meperidine to bind and activate each of the &agr;2-adrenoceptor subtypes in a transfected cell system. Methods The ability of meperidine to bind to and inhibit forskolin-stimulated cyclic adenosine monophosphate formation as mediated by the three &agr;2-adrenoceptor subtypes transiently transfected into COS-7 cells has been tested. The ability of the opioid antagonist naloxone and the &agr;2-adrenoceptor antagonists yohimbine and RX821002 to block the analgesic action of meperidine in the hot-plate test was also assessed. The ability of meperidine to fit into the &agr;2B adrenoceptor was assessed using molecular modeling techniques. Results Meperidine bound to all &agr;2-adrenoceptor subtypes, with &agr;2B having the highest affinity (&agr;2B, 8.6 ± 0.3 &mgr;m; &agr;2C, 13.6 ± 1.5 &mgr;m, P < 0.05; &agr;2A, 38.6 ± 0.7 &mgr;m). Morphine was ineffective at binding to any of the receptor subtypes. Meperidine inhibited the production of forskolin-stimulated cyclic adenosine monophosphate mediated by all receptor subtypes but was most effective at the &agr;2B adrenoceptor (&agr;2B, 0.6 &mgr;m; &agr;2A, 1.3 mm; &agr;2C, 0.3 mm), reaching the same level of inhibition (approximately 70%) as achieved with the &agr;2-adrenoceptor agonist dexmedetomidine. The analgesic action of meperidine was blocked by naloxone but not by the &agr;2-adrenoceptor antagonists yohimbine and RX821002. The modeling studies demonstrated that meperidine can fit into the &agr;2B-adrenoceptor subtype. Conclusion Meperidine is a potent agonist at the &agr;2 adrenoceptors at its clinically relevant concentrations, especially at the &agr;2B-adrenoceptor subtype. Activation of the &agr;2B receptor does not contribute significantly to the analgesic action of meperidine. This raises the possibility that some of its actions, such as antishivering, are transduced by this mechanism.

The common chemical motifs within anesthetic binding sites.

BACKGROUND: It is not yet possible to obtain crystal structures of anesthetic molecules bound to proteins that are plausible neuronal targets; for example, ligand-gated ion channels. However, there are x-ray crystal structures in which anesthetics are complexed with proteins that are not directly related to anesthetic action. Much useful information about anesthetic–protein interactions can be derived from the x-ray crystal structures of halothane–cholesterol oxidase, bromoform–luciferase, halothane–albumin, and dichloroethane–dehalogenase. These structures show anesthetic-protein interactions at the atomic level. METHODS: We obtained the known coordinate files for bromoform–luciferase, halothane– albumin, dichloroethane–dehalogenase, and halothane–cholesterol oxidase. These were then modified by adding hydrogens, edited into subsets, and underwent a series of restrained molecular mechanics optimizations. Final analysis of anesthetic polarization within the anesthetic binding site occurred via combined molecular mechanics–quantum mechanics calculations. RESULTS: The anesthetic binding sites within these well-characterized anesthetic– protein complexes possess a set of common characteristics that we refer to as “binding motifs.” The common features of these motifs are polar and nonpolar interactions within an amphiphilic binding cavity, including the presence of weak hydrogen bond interactions with amino acids and water molecules. Calculations also demonstrated the polarizing effect of the amphipathic binding sites on what are otherwise considered quite hydrophobic anesthetics. This polarization appears energetically favorable. CONCLUSIONS: Anesthetic binding to proteins involves amphipathic interactions.

Molecular mechanism for the dual alcohol modulation of cys loop receptors

Cys-loop receptors constitute a superfamily of pentameric ligand-gated ion channels (pLGICs), including receptors for acetylcholine, serotonin, glycine and γ-aminobutyric acid. Several bacterial homologues have been identified that are excellent models for understanding allosteric binding of alcohols and anesthetics in human Cys-loop receptors. Recently, we showed that a single point mutation on a prokaryotic homologue (GLIC) could transform it from a channel weakly potentiated by ethanol into a highly ethanol-sensitive channel. Here, we have employed molecular simulations to study ethanol binding to GLIC, and to elucidate the role of the ethanol-enhancing mutation in GLIC modulation. By performing 1-µs simulations with and without ethanol on wild-type and mutated GLIC, we observed spontaneous binding in both intra-subunit and inter-subunit transmembrane cavities. In contrast to the glycine receptor GlyR, in which we previously observed ethanol binding primarily in an inter-subunit cavity, ethanol primarily occupied an intra-subunit cavity in wild-type GLIC. However, the highly ethanol-sensitive GLIC mutation significantly enhanced ethanol binding in the inter-subunit cavity. These results demonstrate dramatic effects of the F(14′)A mutation on the distribution of ligands, and are consistent with a two-site model of pLGIC inhibition and potentiation.

Molecular Dynamics Simulation of Anesthetic-Phospholipid Bilayer Interactions

To probe the hypothesis of a lipid-mediated mechanism of general anesthetic action on a molecular level, and to help elucidate the nature of the interactions of bioactive compounds with membranes, the effects of trichloroethylene (TCE), an inhalational general anesthetic, on a dioleoylphosphatidylcholine (DOPC) lipid bilayer have been investigated by molecular dynamics (MD) simulations at 37 degrees C and 1 atm and the results compared with 31P and 2H NMR experimental studies (Ref 1). The model used included a single TCE molecule embedded in a lipid bilayer consisting of 24 DOPC molecules and an 8 A layer of explicit water of solvation in each polar head group region of the bilayer, together with constant-pressure periodic boundary conditions in three dimensions. A comparison of the bilayer properties calculated in the presence and absence of the anesthetic led to the detection of three major perturbations of the bilayer caused by the anesthetic at 1 atm: i) an increase in the ratio of the effective areas of hydrocarbon tails and the head group per lipid, predicting the tendency of lipids near the anesthetic site of action to form a hexagonal phase (HII); ii) a slight increase in the frequency of chain dihedral angles found in the gauche conformation; and iii) a significant increase in the lateral mean-square displacement of lipid molecules, an indication of increased lipid lateral diffusion and membrane fluidity. The pressure antagonism of these effects was also studied by MD simulations at pressures of 200 and 400 atm. The study of the pressure reversibility of these effects at 200 and 400 atm indicated that they were partially prevented at 200 atm and essentially blocked at 400 atm, suggesting their probable relevance to the pressure reversal effect seen with general anesthesia. These results may thus provide insights into the interaction between general anesthetics and similar small organic molecules with membranes.

Homology modeling of a human glycine alpha 1 receptor reveals a plausible anesthetic binding site.

The superfamily of ligand-gated ion channels (LGICs) has been implicated in anesthetic and alcohol responses. Mutations within glycine and GABA receptors have demonstrated that possible sites of anesthetic action exist within the transmembrane subunits of these receptors. The exact molecular arrangement of this transmembrane region remains at intermediate resolution with current experimental techniques. Homology modeling methods were therefore combined with experimental data to produce a more exact model of this region. A consensus from multiple bioinformatics techniques predicted the topology within the transmembrane domain of a glycine alpha one receptor (GlyRa1) to be alpha helical. This fold information was combined with sequence information using the SeqFold algorithm to search for modeling templates. Independently, the FoldMiner algorithm was used to search for templates that had structural folds similar to published coordinates of the homologous nAChR (1OED). Both SeqFold and Foldminer identified the same modeling template. The GlyRa1 sequence was aligned with this template using multiple scoring criteria. Refinement of the alignment closed gaps to produce agreement with labeling studies carried out on the homologous receptors of the superfamily. Structural assignment and refinement was achieved using Modeler. The final structure demonstrated a cavity within the core of a four-helix bundle. Residues known to be involved in modulating anesthetic potency converge on and line this cavity. This suggests that the binding sites for volatile anesthetics in the LGICs are the cavities formed within the core of transmembrane four-helix bundles.