I. Introduction

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Inhaled anesthetics can alter the activity of a wide variety of proteins, but the molecular nature of the interactions underlying the functional effect is poorly understood. In this review, we present and discuss the key evidence for potential molecular interactions with the intent of demonstrating that the many functional effects of inhaled anesthetics are mediated by direct interactions with protein. Although the overall implication is, of course, that these direct interactions ultimately underlie the behavioral state known as "anesthesia," we emphasize that this is not intended to be a review of the various theories of anesthetic action. We restrict this discussion to the more fundamental question of how inhaled anesthetics interact with proteins to alter their activity. At this point, too little is known about the molecular targets of inhaled anesthetics to relate these fundamental interactions to pharmacology. We will focus on soluble proteins, because the binding and structural investigations in these generally small proteins have been most productive and are not confounded by the presence of lipid, as in the case of membrane proteins. We recognize that soluble proteins may not mediate important components of anesthetic action; there seems to be consensus that membrane proteins serve this role (Pocock and Richards, 1991; Franks and Lieb, 1994; Harris et al., 1995). However, the information derived from the soluble proteins should allow an unambiguous definition of binding character and energetics, and the local and global conformational consequences of anesthetic binding, which almost certainly are relevant to the more complex membrane proteins. Because of the large number of compounds that can produce the behavioral state termed "anesthesia," we will further restrict our focus to the inhalational anesthetics, including those with vapor pressures higher than atmospheric at room temperature, such as xenon and nitrous oxide. Although receptor-specific compounds (such as ₂-adrenergic agonists, N-methyl-D-aspartate antagonists, opiates, and benzodiazepines) can produce behavioral states resembling anesthesia, their much higher affinity and specificity suggest that their molecular interactions are different from those of general anesthetics, which are characterized by low-affinity interactions and widespread effects. Even here, however, there may be overlap in how high- and low-affinity compounds influence the activity of proteins.

An interaction between inhalational anesthetics and protein was first suggested by Claude Bernard (1875), who stated that diethyl ether and chloroform produced a reversible coagulation of the "albuminoid" cell contents and that this somehow caused anesthesia. Later, Moore and Roaf (1904, 1905) reported that both ether and chloroform were more soluble in serum or hemoglobin solutions than in water or saline, suggesting some sort of attractive (binding) interaction with the protein. Further, they proposed that the uptake of anesthetics by "proteoid" rather than "lipoid" components was responsible for the production of anesthesia. Countering this idea was the independent work of Overton and Meyer, at about the same time, resulting in the famous correlation of anesthetic potency and olive oil solubility, indicating that anesthetics work by interacting with the olive oil-like components of the cell (Lipnick, 1986, 1989; Miller, 1993).

Nevertheless, observations in support of anesthetic interactions with protein continued. In 1915, Harvey reported that n-alkanols, diethyl ether, and chloroform reversibly depressed the luminescence of certain marine bacteria and that inhibitory potency correlated with n-alkanol chain length. Because the light from these microorganisms derives from the activity of specific enzymes, collectively called "luciferases," these observations suggested that not only could anesthetics bind to protein, but the binding could be associated with an alteration in protein activity. This early work spawned a whole series of more recent investigations with purified light-emitting proteins (see Sections II.B., II.D.1., III.B.) with the goal of demonstrating and characterizing direct anesthetic-protein interactions.

Extending studies on protein activity to protein structure, Östergren (1944) postulated that general anesthetics such as the n-alkanols, nitrous oxide, chloroform and trichloroethylene exert their effects on the lipophilic portion of proteins, based on his observations of anesthetic effects on the mitotic spindle. This speculation finally began to reconcile the observations of Overton and Meyer with those of protein target proponents. The interaction of anesthetics with these lipophilic (hydrophobic) domains was hypothesized to lead to decreased flexibility of the protein (Östergren, 1944). Given the recent appreciation for the importance of marginal stability and conformational dynamics to protein function, this was a remarkably precocious proposal.

Almost thirty years later, the description of the structure of the cell membrane (Singer and Nicolson, 1972), when combined with the observations of Overton and Meyer, once again led the field of anesthetic mechanisms research into the lipid bilayer, which unfortunately has produced much ambiguity. Years of study have indeed verified anesthetic influences on the properties of lipid bilayers (Trudell, 1991; Gruner and Shyamsunder, 1991; Qin et al., 1995; Cantor, 1997), but quantitative problems and heterogeneity of anesthetic effects have forced many investigators to refocus their attention to protein, now with an improved appreciation of the importance of hydrophobic forces to protein structure and function. Further, the functional inseparability of lipid and protein in the cell membrane is now better understood and thus provides a rich environment for reconciliation of the lipid and protein proponents.

	II. Anesthetic Binding to Protein

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The binding of an anesthetic (A^b) to a protein target (P) can be described as follows:

(1)

with forward and reverse rate constants k₁ and k₁, respectively. The dissociation constant of this interaction, K_d, is defined by:

(2)

As is apparent from Equation [2], the K_d is expressed in molar units and is important because it reflects the strength and average lifetime of an interaction. The lower the K_d, the stronger the interaction and the longer compound A is immobilized in the binding site of P. In general, a strong interaction increases the probability that there will be a structural, dynamic, and functional consequence of an interaction between A and P.

What are the dissociation constants for inhalational anesthetics? Initial estimates are possible. If we assume that anesthetic action results from binding to a limited number of sites and that occupancy of these sites is linearly coupled to the clinical response, then the aqueous EC₅₀ concentration will approximate the K_d, which, for most inhalational anesthetics, is between 200 and 300 µM (Franks and Lieb, 1993). Using this approximate K_d, and assuming that the forward rate constant (k₁) is diffusion-limited (limited only by the time required to have reactants collide through diffusion, which for a protein and small ligand is ~10⁹ M¹·sec¹), we calculate a dissociation rate constant (k₁) of ~0.25 to 1.0 · 10⁶ sec¹, implying that binding sites are occupied for lifetimes of only 1 to 4 µsec. A comparison with more familiar high-affinity ligands like the catecholamines or the peptide hormones (K_d values of 2 to 10 nM; Cooper et al., 1982), which have site occupancies of many minutes, emphasizes how weak inhaled anesthetic binding interactions really are. However, the improbable assumptions associated with this simplistic analysis make such estimates only tentative. The probability of multiple binding sites and nonlinear coupling between occupancy and response would suggest that anesthetic K_d values are really much higher than observed EC₅₀ values. This is, of course, entirely in keeping with the behavior of other ligands, like the opioids. Fentanyl, for example, has analgesic (Olkkola et al., 1995) or inhibition of intestinal motility (Magnan et al., 1982) EC₅₀ values in the 1 to 10 ng/ml plasma range, translating to 0.5- to 5 nM free concentrations (assuming 85% protein binding). Measured fentanyl µ-opioid receptor dissociation constants, on the other hand, range from 7 to 400 nM (Magnan et al., 1982; Carroll et al., 1988), the higher numbers (lower affinity) generally reflecting more physiological conditions (e.g., the presence of sodium, G proteins, and GTP). Although possibly expected in the highly amplified G protein-coupled receptor response, a wide separation of EC₅₀ and K_d is also seen in other receptor systems, like the ligand-gated ion channels. Pancuronium produces a 50% suppression of twitch tension at a free drug concentration of 0.3 to 0.4 µM (Shanks, 1986), whereas the K_d for the nicotinic acetylcholine receptor (nAChR) has been reported to be ~60 µM (Loiacono et al., 1993). In addition, whereas a 10 nM free concentration of diazepam is anxiolytic (Greenblatt et al., 1980), the K_d of this ligand for the gamma-aminobutyric acid_A (GABA_A) receptor is estimated to be at least four times that value (DeLorey and Brown, 1992). Therefore, although K_d is often higher than functional EC₅₀, the magnitude is not predictable a priori, suggesting that their match is a poor criterion of the functional relevance of binding sites.

How can dissociation constants be determined more precisely? Because individual rate constants are difficult to measure directly, K_d is usually estimated from equilibrium binding studies with radiolabeled ligands (Weiland and Molinoff, 1981). Even this approach, however, has proven challenging for the inhalational anesthetics because of the difficulty of separating the free from the bound states with such rapidly dissociating volatile compounds. Recently, however, four methods to estimate the K_d for inhalational anesthetic-protein interactions have been reported. First, simple partitioning between the gas phase and a solution of protein, as compared with buffer alone, can be used to estimate the amount of anesthetic bound by the protein (Dubois and Evers, 1992; Dubois et al., 1993). The separation of specific from nonspecific binding is problematic with this approach, however, but occasionally can be achieved by comparison with partitioning into solutions of denatured protein. This, of course, requires sufficient structural knowledge to ensure that the binding domain is actually removed by the denaturing conditions. It is possible that anesthetics bind preferentially to the denatured state of some proteins, rendering it a very poor model of nonspecific binding. Nevertheless, using low pH to denature bovine serum albumin (BSA) for the estimation of nonspecific binding, isoflurane and halothane have been reported to bind to the native pH 7 form of the protein with K_d values of 1.4 mM and 1.3 mM, respectively (Dubois and Evers, 1992; Dubois et al., 1993). Similar estimates of the halothane K_d for binding to BSA have been obtained with ¹⁹F-nuclear magnetic resonance (NMR) (Dubois et al., 1993) and tryptophan fluorescence quenching (Johansson et al., 1995a). A slightly lower estimate of the halothane K_d (0.4 mM) was obtained with direct photoaffinity labeling (Eckenhoff and Shuman, 1993), probably because of selective labeling at sites of highest affinity. Nevertheless, all of these K_d values are well within an order of magnitude and therefore are comparable when considering the overall binding energetics. Consistent with our predictions, all of these estimates for the anesthetic binding to albumin are higher than the clinical EC₅₀ values. Although possibly indicating that the albumin binding domains do not accurately reflect the character of the site(s) responsible for anesthetic action, it bears repeated emphasis that EC₅₀ and K_d need only be similar if one assumes that anesthesia is produced by interactions at few similar sites and that occupancy is linearly coupled to the clinical effect. These assumptions are untenable, considering the widely varied targets for anesthetics reported in the literature and the rarity of linear coupling in biological systems.

The ¹⁹F-NMR measurements have also allowed an estimation of the average lifetime (1/k₁) of an anesthetic-albumin complex, which is 200 to 250 µsec for isoflurane, or approximately two orders of magnitude longer than estimated above (see Section II.A.2.) (Dubois and Evers, 1992; Xu et al., 1996). Substituting this dissociation rate in Equation [2] results in very high K_d values, in excess of 10 mM. The problem probably lies in the use of a diffusion-controlled rate for k₁ in Equation [2]. "Diffusion-controlled" implies that all collisions between anesthetic and protein target would result in the bound or complexed state. However, the actual binding site(s) on the protein surface, or the pathway to an interior binding domain, may only involve a small fraction of the protein surface area, and, therefore, the number of collisional encounters resulting in binding should be smaller than total collisions. Further, normal protein dynamics may limit the duration that the binding site is exposed or available, which will also clearly have an effect on k₁. So if we now use the experimentally derived K_d and k₁ values, k₁ can be estimated to be 3· 10⁶ M¹·sec¹, or almost three orders of magnitude slower than expected for a diffusion-controlled process. It is of interest that this estimate is comparable with the forward rate constants of 10⁴ to 10⁷ M¹·sec¹ observed for other ligand-receptor interactions (Eigen and Hammes, 1963; Gutfreund, 1987; Sklar, 1987). Most importantly, this slower than expected association rate is consistent with a limited number of discrete anesthetic binding sites in soluble proteins, rather than simple nonspecific surface (interfacial) binding (Ueda, 1991). We will now consider the binding event in greater detail.

Energetics or thermodynamics drives all chemical events, including binding interactions and is therefore a reasonable place to begin our consideration of anesthetic-protein interactions. Dissection of the energetics into enthalpic or entropic components yields insight into the forces and groups responsible for a given interaction. Building on our previous discussion, the magnitude of the dissociation constant (K_d) allows calculation of the Gibbs free energy change (G^o) associated with anesthetic binding to protein:

(3)

in which R is the gas constant and T is the absolute temperature, under molar standard state at pH 7. The Gibbs free energy change corresponds to the work involved in binding a ligand to a receptor and is negative if binding occurs spontaneously at the prevailing temperature and pressure. The size of the Gibbs free energy difference between the free and bound states determines the stability or strength of the interaction. Table 1 lists the change in free energy associated with given K_d values (anesthetic EC₅₀ values used as a rough approximation), and an example of a relevant "anesthetic" compound given for each K_d. Note that the change in G^o for different K_d values is fairly modest, especially when compared with the bond energy of a typical covalent interaction (~100 kcal/mol); a ten-fold change in K_d reflects free energy changes comparable to that produced by a single hydrogen bond (~1.0-1.5 kcal/mol; Johansson et al., 1995b).

Dissection of the thermodynamics into entropic (S^o) and enthalpic (H^o) components can provide clues to the types of interactions associated with binding (Testa et al., 1987; Raffa and Porreca, 1989). This can be accomplished by analysis of anesthetic binding at different temperatures using the integrated Van't Hoff equation:

(4)

a combination of Equation [3] and the Gibbs-Helmholtz equation:

(5)

A plot of lnK_d as a function of T¹ permits calculation of H^o and S^o from the slope (H^o/R) and intercept (S^o/R), respectively, assuming that the changes in enthalpy and entropy are constant over the temperature range examined. Although the majority of energetic data on ligand binding has been obtained using such Van't Hoff plots, more recently, investigators have used isothermal titration calorimetry, allowing direct measurement of the minute change in temperature of a system when ligand binds to protein (Jakoby et al., 1995; Fisher and Singh, 1995; Ueda and Yamanaka, 1997). It is of interest that almost no such data on anesthetic binding to protein exists.

How can such thermodynamic information be interpreted? Binding of a hydrophobic compound to a protein target would suggest an increase in the order of the system (a negative change in entropy), but the more important entropic event may be the elimination of the many "structured" water molecules surrounding the hydrophobic ligand in aqueous solution (Muller, 1990), a situation termed "hydrophobic hydration." Therefore, the net entropic change associated with binding to a target based strictly on this hydrophobic effect is actually positive (favorable). Even further entropic advantage is gained if the ligand binding site in the protein is normally occupied by water molecules (also likely to be "structured"), which are "released" by ligand binding (such as occurs when dichloroethane binds to insulin; see Section II.D.4.). Binding events based strictly on such hydrophobic events tend to be associated with little or no enthalpic change (no change in heat content) unless there are also some weak electrostatic interactions involved (e.g., van der Waals and/or hydrogen bonding; see Section II.C.2.). These weak attractive forces between ligand and target will improve the stability of the complex (negative free energy change) and decrease the enthalpy (i.e., decrease the heat content, an exothermic process). Typical ligand-receptor interactions are very stable, being dominated by large enthalpic components; anesthetic-protein interactions are thought to be less stable, with small H° values.

Thermodynamic analyses of anesthetic-protein interactions have, to date, been limited to only a few systems, most of these being the simpler soluble proteins. The Overton-Meyer relationship would emphasize the importance of hydrophobic interactions, suggesting that entropic contributions dominate. However, using a light-emitting enzyme purified from fireflies, Dickinson and colleagues (1993) reported that the interaction between inhalational anesthetics and firefly luciferase was also characterized by a negative enthalpy at 20°C, showing that heat was released when anesthetics bind to this protein and was consistent with some electrostatic attraction between target and anesthetic. This is in accord with earlier work by Ueda and Kamaya (1973), and, as suggested above, implies that anesthetic binding events are more complex than simple hydrophobic partitioning, at least in these soluble proteins.

Other anesthetic/soluble protein interactions that have been examined energetically include those with albumin, myoglobin, and lysozyme. We have used tryptophan fluorescence quenching to examine the temperature dependence of halothane binding to BSA and have found that the apparent K_d decreases as the temperature is reduced, giving the Van't Hoff plot shown in figure 1. This analysis yields a H^o of 1.9 kcal·mol¹ and a S° of +6.0 cal·mol¹·K¹, quantitatively similar to the values for the halothane-luciferase interaction (Dickinson et al., 1993). Recently, Ueda and Yamanaka (1997) also reported that chloroform binding to BSA is associated with a negative enthalpy change (H^o = 2.5 kcal/mol¹). Similarly, the binding of benzene in a hydrophobic cavity of a T4 lysozyme variant is also primarily an enthalpic process (Eriksson et al., 1992a; Morton et al., 1995). Even xenon binding to myoglobin (Ewing and Maestas, 1970) has been shown to be enthalpy-driven, with a G^o of 2.9 kcal mol¹ at 25°C. Thus, protein-anesthetic interactions can be characterized by a negative enthalpic change, implying weak electrostatic attractions in addition to the hydrophobic effect, but the relevance of this characteristic to anesthetic action must wait for more studies like these of many different protein systems, including the important membrane proteins.

View larger version (12K): [in this window] [in a new window]   Fig. 1.   The dependence of the affinity of BSA (5 µM) for halothane at pH 7 in phosphate buffer as a function of temperature as measured by tryptophan fluorsescence quenching. Data points are the means of three separate experiments. Buffer pH varies by ±0.2 units over this temperature range.

The energetics of anesthetic binding to membrane-bound protein could be very different, because the target itself is partitioned between two solvents: water and lipid. Few data exist. In the erythrocyte Ca²⁺-adenosine triphosphatase (ATPase), inhalational anesthetics inhibit activity less (higher IC₅₀) at 25°C as compared with physiological temperature, indicating a more positive H^o than found in anesthetic interactions with the soluble proteins mentioned above (Kosk-Kosicka, 1994). This is more consistent with the classical view of the hydrophobic effect and may reflect a greater role of hydrophobicity and a lesser role of electrostatic interactions in anesthetic binding to membrane proteins. Such energetic data could be interpreted as pointing toward the lipid-protein interface, or the lipid bilayer itself, as the relevant functional binding domain in these proteins. Although consistent with studies attempting to localize the inhalational anesthetic binding sites in membrane proteins (see Section II.D.3.) it clearly points toward the need for more work on the thermal dependence of anesthetic effects in membrane systems.

C. Binding Forces

1. The hydrophobic effect. Although presented above (See Section II.B.), the hydrophobic effect is a topic of some confusion, so we will discuss it in a little more depth here. The hydrophobic effect is classically thought to result from the attraction of water molecules for each other and the energetic cost of creating a cavity between these strongly hydrogen-bonded molecules to accommodate the hydrophobic molecule (Tanford, 1973; Ben-Naim, 1980). Although this energetic cost can be overcome by the strong electrostatic attraction between charged species (like ions) and the relatively high partial charges of water, the weakly polar anesthetic molecules have only feeble interactions with water and are therefore forced or squeezed into macromolecular domains of low hydration when available (e.g., hydrophobic regions), returning the more structured water lining the cavity to its more disordered state. This movement of the anesthetic from bulk water into a hydrophobic domain is therefore a favorable entropic event, consistent with a multitude of partitioning studies between organic solvents and water at 25°C (Tanford, 1973; Ben-Naim, 1980; Abraham et al., 1990).

View larger version (21K): [in this window] [in a new window]   Fig. 2.   Direct photoaffinity labeling of PLL (~200 residues) at pH 7 and 12. CD spectra (not shown) demonstrated only random coil character at pH 7, and predominantly -helix at pH 12. Halothane labeling of PLL is substantially increased under alkaline conditions and acquires a saturable character as shown from the curve fitted to the specific binding data (pH 12-pH 7), implying the creation of a suitable hydrophobic domain for halothane immobilization (binding). Reprinted with permission from Eckenhoff and Shuman (1993). conc., concentration.

2. Electrostatic interactions. The original Overton-Meyer correlation of anesthetic potency with lipid solubility was based on olive oil, an inconsistent mixture of various lipids (Hazzard et al., 1985; Halsey, 1992). A somewhat better correlation has been found for n-octanol than for strictly aliphatic solvents (Franks and Lieb, 1978), implying the importance of a polar component at the anesthetic site of action. A further improvement of the correlation is achieved with lecithin, strengthening the hypothesis that the anesthetic site(s) of action have polar and amphipathic features that interact with anesthetic molecules (Taheri et al., 1991; Halsey, 1992). Despite the fact that inhaled anesthetics are themselves formally uncharged, such interactions are electrostatic in nature. Weak electrostatic interactions can be conveniently (but not distinctly) divided into hydrogen bonding and van der Waals (or dispersion) interactions. We will also consider stereoselectivity here, because the spatial distribution of electrostatic interactions within a cavity is likely to be the basis for differential binding selectivity for enantiomers.

View larger version (23K): [in this window] [in a new window]   Fig. 3.   Potential electrostatic interactions for anesthetics. Panels (a) through (d) represent hydrogen bonding between anesthetic halogens and amid hydrogens, or peripheral aromatic ring hydrogens. Panel (e) shows an ether oxygen (e.g., from isoflurane or desflurane) acting as a hydrogen acceptor for a hydroxyl hydrogen from a serine residue, for example. Panel (f) represents an intrapeptide bond between a carbonyl oxygen and an amide hydrogen, with an anesthetic acting as a hydrogen donor, the implication being that the anesthetic may interact favorably with this group through hydrogen bonding without disruption of the native hydrogen bond. Panel (g) suggests an electrostatic interaction between an "acidic" hydrogen on an anesthetic and the -electrons of the aromatic ring.

View larger version (K): [in this window] [in a new window]   Fig. 4.   Binding of the substrate 1,2-dichoroethane to the active site of dehaloalkane dehalogenase from X. autotrophicus. (a) One of the chlorine atoms electrostatically interacts with the ring nitrogen protons of Trp 125 and 175, whereas the other chlorine interacts with the side chains (probably peripheral ring hydrogens) of Phe 128 and 172. (b) Crystallographic coordinates for this enzyme at 4°C and in the presence of 1,2-dichloroethane (DCE) were obtained from the Protein Data Bank, and RasMol v2.5 (Glaxo Research and Development, Greenford, Middlesex, UK) was used to produce this image. DCE and the interacting aromatics shown in panel a are shown here in spacefilling, and the remainder of the backbone and side chains shown in wireframe. DCE carbons are gray, and chlorines are green. The two phenylalanines are shown in yellow, with the closest carbon shown in dark blue. The tryptophans are orange, with the nitrogens shown in red. Note the tight fit of this ligand in this internal binding pocket and the close apposition of the two chlorines to the four aromatic side chains. It is of interest that this presumably optimized binding site for this ligand/substrate has an association constant of only 1250 M1. Adapted from Verschueren et al. (1993).

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1. Functional and equilibrium binding assays. The most common approach found in the literature is to examine whether the anesthetic binding site overlaps with a native substrate or ligand site. This information may be provided by determining the concentration dependence of the anesthetic effect on some functional assay or an equilibrium (radioligand) binding assay for a previously established ligand. Double reciprocal plots allow the interaction to be classified as competitive, noncompetitive, or some combination of the two. Competitive kinetics are usually interpreted as anesthetic binding at the same site or at an overlapping site in the protein as the ligand. There are numerous examples of this approach, ranging from soluble proteins, such as adenylate kinase (Sachsenheimer et al., 1977), firefly and bacterial luciferases (Adey et al., 1975; Franks and Lieb, 1984), to membrane bound proteins, such as the ligand-gated ion channels or catecholamine transporters (El-Maghrabi and Eckenhoff, 1993; Moody et al., 1993). In firefly luciferase, for instance, the double-reciprocal plot indicates competition with the native substrate luciferin and further suggests that two halothane molecules fit in the luciferin binding site on the protein (Franks and Lieb, 1984), consistent with the approximate molecular volumes of these two ligands.

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e. INFRARED SPECTROSCOPY. Infrared radiation includes wavelengths between 0.7 and 500 µm, or in wavenumbers (number of waves in 1 cm), between 14,000 and 20 cm¹. This part of the electromagnetic spectrum consists of low-energy photons that are ideal for probing the weak interactions thought to be of importance to anesthetic-macromolecule interactions. Infrared radiation is absorbed by the bending and stretching vibrations of various functional groups, resulting in a complex absorption spectrum. This form of spectroscopy has the advantage of rapid time resolution (10¹² seconds), allowing discrimination of environments and events not possible with conventional NMR approaches.

Caughey and coworkers have used infrared spectroscopy to characterize the binding environment of nitrous oxide in a variety of protein targets. They examined the shift in the wavenumber position of a specific antisymmetric stretch frequency (₃) of N₂O close to 2230 cm¹, which reflects the polarity of the environment of the anesthetic molecule (Gorga et al., 1985

1

3. Direct photoaffinity labeling. A recent approach developed in our laboratory is halothane direct photoaffinity labeling (Eckenhoff and Shuman, 1993; El-Maghrabi et al., 1992). As previously discussed (see Section II.A.), the rapid kinetics of halothane equilibrium binding preclude or complicate the use of several conventional methods for determining binding location. These rapid kinetics, however, can be converted to a stable covalent bond by cleaving the carbon-bromine bond of halothane with ultraviolet light to produce a reactive chlorotrifluoroethyl radical, which then covalently attaches to residues in its equilibrium-bound environment to form an adduct, probably through a two-step reaction process, should a suitable group be immediately available. If not, as in the case of halothane photolysis in water, the radical prefers to recombine with the free bromine atom, reforming the parent halothane molecule. An ability to recombine with the bromine atom makes it likely that sites of higher affinity will be preferentially labeled over those of lower affinity. After covalent linkage, the adduct location can be identified by including a radioactive atom, such as ¹⁴C on the trifluoromethyl carbon, or ³H on the 1-carbon, or by monitoring regional protein mass with mass spectrometry (Lindeman and Lovins, 1976; Grenot et al., 1994). Importantly, photoaffinity labeling is one of the few methods available for these small anesthetic ligands capable of separating specific from nonspecific binding, because unlabeled halothane can be used as a competitor. Accordingly, most halothane labeling of biological membranes was found to be specific, whereas labeling of the lipid portion alone (liposomes) was substantially less inhibited by unlabeled halothane (Eckenhoff, 1996b). Photolabeling has also permitted the mapping of halothane binding sites in soluble proteins, such as serum albumin. Two specific binding sites were identified in BSA (Eckenhoff, 1996a), and these correspond roughly to the location of the two tryptophans in this protein, in agreement with the tryptophan quenching studies (Johansson et al., 1995a). In accordance with the rapid kinetics and relatively small size of the parent molecule, halothane, the label is found bound to several amino acid residues in the large IIA cavity (Trp214-Arg219). Further, despite clear competition between fatty acids and halothane (Dubois and Evers, 1992; Eckenhoff and Shuman, 1993) for binding to BSA, the photolabeled residues do not coincide with the presumed fatty acid binding domains (Carter and Ho, 1994), indicating allosteric communication between these sites. This is consistent with the global conformational changes that albumin undergoes on binding fatty acids (Carter and Ho, 1994) and the large increase in thermal stability (Shrake and Ross, 1988). Also, t