Lipid conformation in model membranes and biological membranes

Protein molecules in solution or in protein crystals are characterized by rather well-defined structures in which α-helical regions, β-pleated sheets, etc., are the key features. Likewise, the double helix of nucleic acids has almost become the trademark of molecular biology as such. By contrast, the structural analysis of lipids has progressed at a relatively slow pace. The early X-ray diffraction studies by V. Luzzati and others firmly established the fact that the lipids in biological membranes are predominantly organized in bilayer structures (Luzzati, 1968). V. Luzzati was also the first to emphasize the liquid-like conformation of the hydrocarbon chains, similar to that of a liquid paraffin, yet with the average orientation of the chains perpendicular to the lipid-water interface. This liquid-crystalline bilayer is generally observed in lipid-water systems at sufficiently high temperature and water content, as well as in intact biological membranes under physiological conditions (Luzzati & Husson, 1962; Luzzati, 1968; Tardieu, Luzzati & Reman, 1973; Engelman, 1971; Shipley, 1973). In combination with thermodynamic and other spectroscopic observations these investigations culminated in the formulation of the fluid mosaic model of biological membranes (cf. Singer, 1971). However, within the limits of this model the exact nature of lipid conformation and dynamics was immaterial, the lipids were simply pictured as circles with two squiggly lines representing the polar head group and the fatty acyl chains, respectively. No attempt was made to incorporate the well-established chemical structure into this picture. Similarly, membrane proteins were visualized as smooth rotational ellipsoids disregarding the possibility that protruding amino acid side-chains and irregularities of the backbone folding may create a rather rugged protein surfac

Protein unfolding. Thermodynamic perspectives and unfolding models

Protein unfolding is a dynamic cooperative process with many short-lived intermediates. Cooperativity means that similar molecular elements act dependently on each other. The thermodynamics of protein unfolding can be determined with differential scanning calorimetry (DSC). The measurement of the heat capacity provides the temperature profiles of enthalpy, entropy and free energy. The thermodynamics of protein unfolding is completely determined with these thermodynamic properties. We emphasise the model-independent analysis of the heat capacity. The temperature profiles of enthalpy H(T), entropy S(T) and free energy G(T) can be obtained directly by a numerical integration of C p (T). In evaluating different models for protein unfolding. It is essential to simulate all thermodynamic properties, not only the heat capacity. A chemical equilibrium two-state model is a widely used approximation to protein unfolding. The model assumes a chemical equilibrium between only two protein conformations, the native protein (N) and the unfolded protein (U). The model fits the heat capacity C p (T) quite well, but fails in simulating the other thermodynamic properties. In this review we propose a modification of the chemical equilibrium two-state model, which removes these inconsistencies. We also propose a new statistical-mechanical two-state model based on a simple, two-parameter partition function Z(T), from which all thermodynamic parameters can be derived. The thermodynamic predictions of the new models are compared to published DSC-experiments obtained with lysozyme, a globular protein, and β-lactoglobulin, a β-barrel protein. Good fits to all thermodynamic properties are obtained. In particular, the models predict a zero free energy for the native protein, which is confirmed experimentally by DSC. This is in contrast to the often-cited chemical equilibrium two-state model, which predict a positive free energy for the native protein. Two-state models use macroscopic fit parameters, the conformational enthalpy and the heat capacity difference between native and unfolded protein. These simulations provide no molecular insight. The review therefore includes a recently published multistate cooperative model based on physicality well-defined molecular parameters only

Molecular Understanding of Calorimetric Protein Unfolding Experiments

Protein unfolding is a dynamic cooperative equilibrium between short lived protein conformations. The Zimm-Bragg theory is an ideal algorithm to handle cooperative processes. Here, we extend the analytical capabilities of the Zimm-Bragg theory in two directions. First, we combine the Zimm-Bragg partition function Z(T) with statistical-mechanical thermodynamics, explaining the thermodynamic system properties enthalpy, entropy and free energy with molecular parameters only. Second, the molecular enthalpy h0 to unfold a single amino acid residue is made temperature-dependent. The addition of a heat capacity term cv allows predicting not only heat denaturation, but also cold denaturation. Moreover, it predicts the heat capacity increase in protein unfolding. The theory is successfully applied to differential scanning calorimetry experiments of proteins of different size and structure, that is, gpW62 (62aa), ubiquitin (74aa), lysozyme (129aa), metmyoglobin (153aa) and mAb monoclonal antibody (1290aa). Particular attention was given to the free energy, which can easily be obtained from the heat capacity Cp(T). The DSC experiments reveal a zero free energy for the native protein with an immediate decrease to negative free energies upon cold and heat denaturation. This trapezoidal shape is precisely reproduced by the Zimm-Bragg theory, whereas the so far applied non-cooperative 2-state model predicts a parabolic shape with a positive free energy maximum of the native protein. We demonstrate that the molecular parameters of the Zimm-Bragg theory have a well-defined physical meaning. In addition to predicting protein stability, independent of protein size, they yield estimates of unfolding kinetics and can be connected to molecular dynamics calculations.Competing Interest StatementThe authors have declared no competing interest

Protein Stability─Analysis of Heat and Cold Denaturation without and with Unfolding Models

Protein stability is important in many areas of life sciences. Thermal protein unfolding is investigated extensively with various spectroscopic techniques. The extraction of thermodynamic properties from these measurements requires the application of models. Differential scanning calorimetry (DSC) is less common, but is unique as it measures directly a thermodynamic property, that is, the heat capacity; C; p; (; T; ). The analysis of; C; p; (; T; ) is usually performed with the chemical equilibrium two-state model. This is not necessary and leads to incorrect thermodynamic consequences. Here we demonstrate a straightforward model-independent evaluation of heat capacity experiments in terms of protein unfolding enthalpy Δ; H; (; T; ), entropy Δ; S; (; T; ), and free energy Δ; G; (; T; )). This now allows the comparison of the experimental thermodynamic data with the predictions of different models. We critically examined the standard chemical equilibrium two-state model, which predicts a positive free energy for the native protein, and diverges distinctly from the experimental temperature profiles. We propose two new models which are equally applicable to spectroscopy and calorimetry. The Θ; U; (; T; )-weighted chemical equilibrium model and the statistical-mechanical two-state model provide excellent fits of the experimental data. They predict sigmoidal temperature profiles for enthalpy and entropy, and a trapezoidal temperature profile for the free energy. This is illustrated with experimental examples for heat and cold denaturation of lysozyme and β-lactoglobulin. We then show that the free energy is not a good criterion to judge protein stability. More useful parameters are discussed, including protein cooperativity. The new parameters are embedded in a well-defined thermodynamic context and are amenable to molecular dynamics calculations

Chemical Protein Unfolding - A Simple Cooperative Model

Chemical unfolding with guanidineHCl or urea is a common method to study the conformational stability of proteins. The analysis of unfolding isotherms is usually performed with an empirical linear extrapolation method (LEM). A large positive free energy is assigned to the native protein, which is usually considered to be a minimum of the free energy. The method thus contradicts common expectations. Here, we present a multistate cooperative model that addresses specifically the binding of the denaturant to the protein and the cooperativity of the protein unfolding equilibrium. The model is based on a molecular statistical-mechanical partition function of the ensemble, but simple solutions for the calculation of the binding isotherm and the associated free energy are presented. The model is applied to 23 published unfolding isotherms of small and large proteins. For a given denaturant, the binding constant depends on temperature and pH but shows little protein specificity. Chemical unfolding is less cooperative than thermal unfolding. The cooperativity parameter σ is at least 2 orders of magnitude larger than that of thermal unfolding. The multistate cooperative model predicts zero free energy for the native protein, which becomes strongly negative beyond the midpoint concentration of unfolding. The free energy to unfold a cooperative unit corresponds exactly to the diffusive energy of the denaturant concentration gradient necessary for unfolding. The temperature dependence of unfolding isotherms yields the denaturant-induced unfolding entropy and, in turn, the unfolding enthalpy. The multistate cooperative model provides molecular insight and is as simple to apply as the LEM but avoids the conceptual difficulties of the latter

Deuterium magnetic resonance: theory and application to lipid membranes

Proton and carbon-13 nmr spectra of unsonicated lipid bilayers and biological membranes are generally dominated by strong proton-proton and proton-carbon dipolar interactions. As a result the spectra contain a large number of overlapping resonances and are rather difficult to analyse. Nevertheless, important information on the structure and dynamic behaviour of lipid systems has been provided by these techniques (Wennerström & Lindblom, 1977

Leakage and lysis of lipid membranes induced by the lipopeptide surfactin

Surfactin is a lipopeptide produced by Bacillus subtilis which possesses antimicrobial activity. We have studied the leakage and lysis of POPC vesicles induced by surfactin using calcein fluorescence de-quenching, isothermal titration calorimetry and 31P solid state NMR. Membrane leakage starts at a surfactin-to-lipid ratio in the membrane, R b≈0.05, and an aqueous surfactin concentration of C S w ≈2μM. The transient, graded nature of leakage and the apparent coupling with surfactin translocation to the inner leaflet of the vesicles, suggests that this low-concentration effect is due to a bilayer-couple mechanism. Different permeabilization behaviour is found at R b≈0.15 and attributed to surfactin-rich clusters, which can induce leaks and stabilize them by covering their hydrophobic edges. Membrane lysis or solubilization to micellar structures starts at R b sat =0.22 and C S w =9μM and is completed at R m sol =0.43 and C S w =11μM. The membrane-water partition coefficient of surfactin is obtained as K=2×104M−1. These data resolve inconsistencies in the literature and shed light on the variety of effects often referred to as detergent-like effects of antibiotic peptides on membranes. The results are compared with published parameters characterizing the hemolytic and antibacterial activit

Assignment of glial brain tumors in humans by in vivo 1H-magnetic resonance spectroscopy and multidimensional metabolic classification

This study presents a simple approach for the noninvasive assignment of glial brain tumors according to malignancy by single-voxel proteon magnetic resonance spectroscopy at short echo times (TE≦50 milliseconds). Based on peak area ratios, a five-dimensional data set was obtained for each investigated subject. This vector was then projected along metabolic coordinates in a two-dimensional metabolic space. These coordinates had been determined in a previous study (Hagberg G et al., 1995,Magn Reson Med 34: 242-252). Tumor assignment was done without any knowledge of histology by comparing the location of the new cases to the features of the previous study. All 11 investigated glioblastomas multiforme, as well as 4 of 5 astrocytomas grade II, could easily be assigned to the groups of high- and low-grade tumors, respectively. Classification was more difficult in the case of a cystic astrocytoma grade II and one astrocytoma grade III. Two spectra measured in normal-appearing matter of glioblastoma patients were not classified as healthy. Using single-voxel proton magnetic resonance spectroscopy at short echo times with the knowledge of a base study, a straightforward, fast, and noninvasive differential diagnosis of glial brain tumors is possibl