Classification of the binding modes in bovine serum albumin using terminally substituted alkane analogues.

With the fluorescence probe of 8-anilino-1-naphthalenesulfonate (ANS), the binding modes of terminally substituted alkane analogues (C(n)X; X = COOH, OH, CHO, NH(3), CONH(2)) to bovine serum albumin (BSA) were investigated using a competitive binding technique. The Scatchard plot of the fluorometric titration of BSA with ANS showed that the maximum binding number of ANS, n(max), was 3.81, with the binding constant, K(bnd), of 1.42 x 10(6) mol(-1) dm(3). The binding modes of C(n)X to BSA were analyzed based on the fluorometric titration of the ANS and BSA mixture with C(n)X. C(n)COOH completely displaced the ANS bound to BSA, whereas C(n)OH and C(n)CHO displaced only about 40% of the ANS bound to BSA. In contrast, C(n)NH(2) and C(n)CONH(2) displaced very little bound ANS. By comparing these results, we classified the binding modes of C(n)X to BSA into three types. Two of them are detectable with the ANS fluorescence and the remaining one is not detectable with the fluorescence.

Temperature dependence of thermodynamic activity in volatile anesthetics: correlation between anesthetic potency and activity.

Temperature dependence of the saturated concentration and the activity coefficient of anesthetics (1-propanol, diethyl ether, chloroform, and halothane) in water were evaluated using vapor pressure and H NMR measurement. We found that these physical values (quantities) correlate with anesthetic potencies estimated according to the thermodynamic equilibrium model. The anesthetic potency for hydrophilic anesthetic (diethyl ether) decreased with decreasing temperature because of the temperature specificity of this saturated concentration. In contrast, potencies of hydrophobic anesthetics (chloroform and halothane) increased with decreasing temperature because of the temperature specificity of those activity coefficients. By assuming that anesthetics interact with hydrated water of cell membranes, the temperature dependence of anesthetic potencies in vivo is qualitatively explicable.

Action mechanism of water soluble ethanol on phospholipid monolayers using a quartz crystal oscillator.

Interaction between phospholipid monolayers (dihexadecyl phosphate: DHP, dipalmitoyl phosphatidyl choline: DPPC) and water soluble ethanol has been studied using quartz crystal microbalance (QCM) method and quartz crystal impedance (QCI) method. The quartz crystal oscillator was attached horizontally on the DHP and DPPC monolayers that were formed on the water surface. At low concentration, increased ethanol concentration decreased the frequency for QCM and increased the resistance for QCI. Both frequency and resistance approached asymptotically to a saturation value. A further increase in ethanol concentration induced a sudden and discontinuous linear change (a decrease in frequency and an increase in resistance). Based on these results, we propose the following action mechanism of ethanol on phospholipid monolayers: at low concentration, the ethanol hydrates adsorb into the monolayer/water interface and saturate on the interface. The monolayer viscosity also increases with the adsorption of hydrates. A further increase in concentration causes multilayer formation of hydrates and/or penetration of hydrates into the monolayer core. The viscosity of the interfacial layer (monolayer and interfacial structured water) changes dramatically according to the action of ethanol hydrates.

Inhibition of firefly luciferase by alkane analogues.

We reported that anesthetics increased the partial molal volume of firefly luciferase (FFL), while long-chain fatty acids (LCFA) decreased it. The present study measured the actions of dodecanol (neutral), dodecanoic acid (negatively charged), and dodecylamine (positively charged) hydrophobic molecules on FFL. The interaction modes are measured by (1) ATP-induced bioluminescence of FFL and (2) fluorescence of 2-(p-toluidino)naphthalene-6-sulfonate (TNS). TNS fluoresces brightly in hydrophobic media. It competes with the substrate luciferin on the FFL binding. From the Scatchard plot of TNS titration, the maximum binding number of TNS was 0.83, and its binding constant was 8.27 x 10(5) M(-1). Job's plot also showed that the binding number is 0.89. From the TNS titration of FFL, the binding constant was estimated to be 8.8 x 10(5) M(-1). Dodecanoic acid quenched the TNS fluorescence entirely. Dodecanol quenched about 25% of the fluorescence, whereas dodecylamine increased it. By comparing the fluorescence of TNS and bioluminescence of FFL, the binding modes and the inhibition mechanisms of these dodecane analogues are classified in three different modes: competitive (dodecanoic acid), noncompetitive (dodecylamine), and mixed (dodecanol).

Preferential partitioning of uncharged local anesthetics into the surface-adsorbed film.

The surface tension and pH of aqueous solutions of three hydrochloric acid (HCl) - uncharged anesthetic (mepivacaine (MC), bupibacaine (BC) and dibucaine (DC)) mixtures were measured as a function of total molality and composition of local anesthetic in order to investigate the competitive surface-adsorption of uncharged and charged local anesthetics. The behavior of the surface tension versus total molality and pH versus total molality curves remarkably changed at the composition corresponding to an equimolar mixture. The pH measurements showed that uncharged and charged forms coexisted only at compositions more than the equimolar mixture. The partitioning quantities of respective uncharged and charged anesthetics into the surface-adsorbed film were estimated from their surface densities calculated thermodynamically. The greater quantity of uncharged anesthetics existed in the adsorbed film at the coexisting composition, that is, the uncharged anesthetics adsorbed more preferentially than charged ones. The relative ease with which uncharged anesthetics transferred into the surface-adsorbed film was proportional to the hydrophobicities and well correlated the anesthetic potencies. At compositions in the vicinity of physiological pH (ca. 7.4), the bulk solution is more abundant in charged anesthetics than uncharged ones, whereas the uncharged molecules is conversely more abundant in the surface region. The present results clearly imply that the surface-active molecule of local anesthetic in the physiological pH is the uncharged form and the partitioning is greatly dependent on the hydrophobicity among the anesthetics.

Multi-Unit and Multi-Path system of the neural network can explain the steep dose-response of MAC.

PURPOSE: The slope of the dose-response curves of inhalation anesthetics is steep around the minimum alveolar concentration of inhalation anesthetics (MAC) value. Contrastingly, the anesthetic dose-response curves of ion channels and enzymes are gradual. This discrepancy in the steepness may be a key to solve the mechanisms of anesthesia. To explain the steepness we propose a mathematical model of the neural network related to MAC. METHODS: We assumed that, in order to show movement in response to a noxious stimulus, a signal needed to be transmitted from A to B. There are m conduction pathways (Multi-Path) in the nerve network between A and B, and there are n conduction units (Multi-Unit) in each conduction pathway. Anesthetics bind to each conduction unit and block signal transmission. Anesthetics prevent movement in response to a stimulus, when at least one conduction unit among all conduction pathways has been blocked. We derived the equation for the probability of the signal being blocked by anesthetics. RESULTS: The steep dose-response curve of in vivo anesthesia requires a very large number of conduction units ( n > 100) and conduction pathways ( m > 10(6)). The EC50 for each conduction unit was at least 3.8-fold larger than the apparent EC50 for the whole system under the experimental condition of simulation. CONCLUSIONS: We constructed a model for the neural networks that relates to MAC as a Multi-Unit and Multi-Path system (MUMPS). To obtain highly cooperative dose-response curves comparable to those of in vivo anesthesia, at least 10(6) conduction pathways and more than 100 conduction units are required for each pathway. In these systems, the apparent anesthetic potency on the whole system (MAC) is much stronger than the anesthetic action on each unit. Because of this discrepancy, it is important to set anesthetic concentrations appropriately for experiments with in vitro systems.