Inverse Conformational Selection in Lipid-Protein Binding.

Interest in lipid interactions with proteins and other biomolecules is emerging not only in fundamental biochemistry but also in the field of nanobiotechnology where lipids are commonly used, for example, in carriers of mRNA vaccines. The outward-facing components of cellular membranes and lipid nanoparticles, the lipid headgroups, regulate membrane interactions with approaching substances, such as proteins, drugs, RNA, or viruses. Because lipid headgroup conformational ensembles have not been experimentally determined in physiologically relevant conditions, an essential question about their interactions with other biomolecules remains unanswered: Do headgroups exchange between a few rigid structures, or fluctuate freely across a practically continuous spectrum of conformations? Here, we combine solid-state NMR experiments and molecular dynamics simulations from the NMRlipids Project to resolve the conformational ensembles of headgroups of four key lipid types in various biologically relevant conditions. We find that lipid headgroups sample a wide range of overlapping conformations in both neutral and charged cellular membranes, and that differences in the headgroup chemistry manifest only in probability distributions of conformations. Furthermore, the analysis of 894 protein-bound lipid structures from the Protein Data Bank suggests that lipids can bind to proteins in a wide range of conformations, which are not limited by the headgroup chemistry. We propose that lipids can select a suitable headgroup conformation from the wide range available to them to fit the various binding sites in proteins. The proposed inverse conformational selection model will extend also to lipid binding to targets other than proteins, such as drugs, RNA, and viruses.

Liquid-liquid phase coexistence in lipid membranes observed by natural abundance 1H-13C solid-state NMR.

We demonstrate that 1H-13C solid-state MAS NMR is suitable to detect liquid disordered/liquid ordered phase coexistence in a DOPC/DPPC/cholesterol mixture with natural abundance of isotopes as an alternative to 2H NMR. Such methodology is potentially applicable to study lipid phase coexistence phenomena in biological matter with high lipid content, e.g. lung surfactant or myelin, for which isotopic labeling is not possible.

Acyl Chain Disorder and Azelaoyl Orientation in Lipid Membranes Containing Oxidized Lipids.

Oxidized phospholipids occur naturally in conditions of oxidative stress and have been suggested to play an important role in a number of pathological conditions due to their effects on a lipid membrane acyl chain orientation, ordering, and permeability. Here we investigate the effect of the oxidized phospholipid 1-palmitoyl-2-azelaoyl-sn-glycero-3-phosphocholine (PazePC) on a model membrane of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) using a combination of (13)C-(1)H dipolar-recoupling nuclear magnetic resonance (NMR) experiments and united-atom molecular dynamics (MD) simulations. The obtained experimental order parameter SCH profiles show that the presence of 30 mol % PazePC in the bilayer significantly increases the gauche content of the POPC acyl chains, therefore decreasing the thickness of the bilayer, although with no stable bilayer pore formation. The MD simulations reproduce the disordering effect and indicate that the orientation of the azelaoyl chain is highly dependent on its protonation state with acyl chain reversal for fully deprotonated states and a parallel orientation along the interfacial plane for fully protonated states, deprotonated and protonated azelaoyl chains having negative and positive SCH profiles, respectively. Only fully or nearly fully protonated azelaoyl chain are observed in the (13)C-(1)H dipolar-recoupling NMR experiments. The experiments show positive SCH values for the azelaoyl segments confirming for the first time that oxidized chains with polar termini adopt a parallel orientation to the bilayer plane as predicted in MD simulations.

Simulating Bacterial Membrane Models at the Atomistic Level: A Force Field Comparison.

Molecular dynamics (MD) simulations are currently an indispensable tool to understand both the dynamic and nanoscale organization of cell membrane models. A large number of quantitative parameters can be extracted from these simulations, but their reliability is determined by the quality of the employed force field and the simulation parameters. Much of the work on parametrizing and optimizing force fields for biomembrane modeling has been focused on homogeneous bilayers with a single phospholipid type. However, these may not perform effectively or could even be unsuitable for lipid mixtures commonly employed in membrane models. This work aims to fill this gap by comparing MD simulation results of several bacterial membrane models using different force fields and simulation parameters, namely, CHARMM36, Slipids, and GROMOS-CKP. Furthermore, the hydrogen isotope exchange (HIE) method, combined with GROMOS-CKP (GROMOS-H2Q), was also tested to check for the impact of this acceleration strategy on the performance of the force field. A common set of simulation parameters was employed for all of the force fields in addition to those corresponding to the original parametrization of each of them. Furthermore, new experimental order parameter values determined from NMR of several lipid mixtures are also reported to compare them with those determined from MD simulations. Our results reveal that most of the calculated physical properties of bacterial membrane models from MD simulations are substantially force field and lipid composition dependent. Some lipid mixtures exhibit nearly ideal behaviors, while the interaction of different lipid types in other mixtures is highly synergistic. None of the employed force fields seem to be clearly superior to the other three, each having its own strengths and weaknesses. Slipids are notably effective at replicating the order parameters for all acyl chains, including those in lipid mixtures, but they offer the least accurate results for headgroup parameters. Conversely, CHARMM provides almost perfect estimates for the order parameters of the headgroups but tends to overestimate those of the lipid tails. The GROMOS parametrizations deliver reasonable order parameters for entire lipid molecules, including multicomponent bilayers, although they do not reach the accuracy of Slipids for tails or CHARMM for headgroups. Importantly, GROMOS-H2Q stands out for its computational efficiency, being at least 3 times faster than GROMOS, which is already faster than both CHARMM and Slipids. In turn, GROMOS-H2Q yields much higher compressibilities compared to all other parametrizations.

Time-domain proton-detected local-field NMR for molecular structure determination in complex lipid membranes.

Proton-detected local-field (PDLF) NMR spectroscopy, using magic-angle spinning and dipolar recoupling, is presently the most powerful experimental technique for obtaining atomistic structural information from small molecules undergoing anisotropic motion. Common examples include peptides, drugs, or lipids in model membranes and molecules that form liquid crystals. The measurements on complex systems are however compromised by the larger number of transients required. Retaining sufficient spectral quality in the direct dimension requires that the indirect time-domain modulation becomes too short for yielding dipolar splittings in the frequency domain. In such cases, the dipolar couplings can be obtained by fitting the experimental data; however ideal models often fail to fit PDLF data properly due to effects of radiofrequency field (RF) spatial inhomogeneity. Here, we demonstrate that by accounting for RF spatial inhomogeneity in the modeling of R-symmetry-based PDLF NMR experiments, the fitting accuracy is improved, facilitating the analysis of the experimental data. In comparison to the analysis of dipolar splittings without any fitting procedure, the accurate modeling of PDLF measurements makes possible three important improvements: the use of shorter experiments that enable the investigation of samples with a higher level of complexity, the measurement of C-H bond order parameters with smaller magnitudes |SCH| and of smaller variations of |SCH| caused by perturbations of the system, and the determination of |SCH| values with small differences from distinct sites having the same chemical shift. The increase in fitting accuracy is demonstrated by comparison with 2H NMR quadrupolar echo experiments on mixtures of deuterated and non-deuterated dimyristoylphosphatidylcholine (DMPC) and with 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE) membranes. Accurate modeling of PDLF NMR experiments is highly useful for investigating complex membrane systems. This is exemplified by application of the proposed fitting procedure for the characterization of membranes composed of a brain lipid extract with many distinct lipid types.