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Lung surfactant is a thin lining covering the air-water interface inside the alveoli. Its main function is to reduce the surface tension at this interface and thus prevent the alveoli from collapsing at the end of the breathing cycle. In addition to its importance in maintaining proper lung function, it is suggested that this monolayer aects the permeation of small non-electrolytes such as molecular oxygen from inhaled air towards circulation. However, the results on this topic are extremely diverse. Earlier computational studies have been inadequate in terms of monolayer composition and state, simulation conditions and force eld parametrisations and the amount of employed computational resources. They have also often considered either energetic or kinetic factors on permeability alone. On the other hand, lack of resolution has been the main issue with experimental studies on oxygen permeability. To overcome these limitations, the permeation properties of protein-free surfactant membrane systems were studied through long atomistic molecular dynamics simulations with high spatial resolution. Monolayers at dierent compression states were employed with the lipid composition and simulation conditions of the systems mimicking that of the real surfactant. In addition to the permeation properties of the monolayer, information about oxygen pathways below the interface were also discussed with the data obtained from bilayer simulations with the same composition. A new model for molecular oxygen was sought in this study and its performance was verified with multiple benchmarks. A special free energy technique, the z constraint method was employed together with the inhomogeneous solubility{diusion model to study the permeabilities of the membrane systems as it provides one with detailed information about both energetic and kinetic factors on permeation. The key values of the spatially resolved free energy and diusion coe cient pro les along the membrane normal agree with those of earlier studies yet the detailed pro les also provide new and interesting information. The calculated permeabilities of the monolayer systems are successfully linked to the other physical quantities characterizing the monolayers. The possible suggested structures lying below the surfactant monolayer are compared based on their eect on oxygen transport. Finally, thorough comparison is performed between our calculations and earlier studies.
Molecular dynamics (MD) simulations have become a highly important technique to consider lipid membrane systems, and quite often they provide considerable added value to laboratory experiments. Rapid development of both software and hardware has enabled the increase of time and size scales reachable by MD simulations to match those attainable by several accurate experimental techniques. However, until recently, the quality and maturity of software tools available for building membrane models for simulations as well as analyzing the results of these simulations have seriously lagged behind.Here, we discuss the recent developments of such tools from the end-users' point of view. In particular, we review the software that can be employed to build lipid bilayers and other related structures with or without embedded membrane proteins to be employed in MD simulations. Additionally, we provide a brief critical insight into force fields and MD packages commonly used for membrane and membrane protein simulations. Finally, we list analysis tools that can be used to study the properties of membrane and membrane protein systems. In all these points we comment on the respective compatibility of the covered tools.We also share our opinion on the current state of the available software. We briefly discuss the most commonly employed tools and platforms on which new software can be built. We conclude the review by providing a few ideas and guidelines on how the development of tools can be further boosted to catch up with the rapid pace at which the field of membrane simulation progresses. This includes improving the compatibility between software tools and promoting the openness of the codes on which these applications rely.This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.
Molecular oxygen (O2) is key to all life on earth, as it is constantly cycled via photosynthesis and cellular respiration. Substantial scientific effort has been devoted to understanding every part of this cycle. Classical molecular dynamics (MD) simulations have been used to study some of the key processes involved in cellular respiration: O2 permeation through alveolar monolayers and cellular membranes, its binding to hemoglobin during transport in the bloodstream, as well as its transport along optimal pathways toward its reduction sites in proteins. Moreover, MD simulations can help interpret the results of several imaging techniques in which O2 is used because of its paramagnetic nature. However, despite the widespread use of computational models for the O2 molecule, their performances have never been systematically evaluated. In this paper, we assess the performances of 14 different models of O2 available in the literature by calculating four thermodynamic properties: density, heat of vaporization, free energy of hydration, and free energy of solvation in hexadecane. For each property, reliable experimental data are available. Most models perform reasonably well in predicting the correct trends, but they fail to reproduce the experimental data quantitatively. We then develop new models for O2, with and without a quadrupole moment, and compare their behavior with the behavior of previously published models. The new models show significant improvement in terms of density, heat of vaporization, and free energy of hydration. However, quantitative agreement with water-oil partitioning is not reached due to discrepancies between the calculated and measured free energies of solvation in hexadecane. We suggest that classical pairwise-additive models may be inadequate to properly describe the thermodynamics of solvation of apolar species, such as O2, in apolar solvents.
Shear viscosity of lipid membranes dictates how fast lipids, proteins, and other membrane constituents travel along the membrane and rotate around their principal axis, thus governing the rates of diffusion-limited reactions taking place at membranes. In this framework, the heterogeneity of biomembranes indicates that cells could regulate these rates via varying local viscosities. Unfortunately, experiments to probe membrane viscosity under various conditions are tedious and error prone. Molecular dynamics simulations provide an attractive alternative, especially given that recent theoretical developments enable the elimination of finite-size effects in simulations. Here, we use a variety of different equilibrium methods to extract the shear viscosities of lipid membranes from both coarse-grained and all-atom molecular dynamics simulations. We systematically probe the variables relevant for cellular membranes, namely, membrane protein crowding, cholesterol concentration, and the length and saturation level of lipid acyl chains, as well as temperature. Our results highlight that in their physiologically relevant ranges, protein concentration, cholesterol concentration, and temperature have significantly larger effects on membrane viscosity than lipid acyl chain length and unsaturation level. In particular, the crowding with proteins has a significant effect on the shear viscosity of lipid membranes and thus on the diffusion occurring in the membranes. Our work also provides the largest collection of membrane viscosity values from simulation to date, which can be used by the community to predict the diffusion coefficients or their trends via the Saffman-Delbrück description. Additionally, it is worth emphasizing that diffusion coefficients extracted from simulations exploiting periodic boundary conditions must be corrected for the finite-size effects prior to comparison with experiment, for which the present collection of viscosity values can readily be used. Finally, our thorough comparison to experiments suggests that there is room for improvement in the description of bilayer dynamics provided by the present force fields.
The coarse-grained Martini model is employed extensively to study membrane protein oligomerization. While this approach is exceptionally promising given its computational efficiency, it is alarming that a significant fraction of these studies demonstrate unrealistic protein clusters, whose formation is essentially an irreversible process. This suggests that the protein–protein interactions are exaggerated in the Martini model. If this held true, then it would limit the applicability of Martini to study multi-protein complexes, as the rapidly clustering proteins would not be able to properly sample the correct dimerization conformations. In this work we first demonstrate the excessive protein aggregation by comparing the dimerization free energies of helical transmembrane peptides obtained with the Martini model to those determined from FRET experiments. Second, we show that the predictions provided by the Martini model for the structures of transmembrane domain dimers are in poor agreement with the corresponding structures resolved using NMR. Next, we demonstrate that the first issue can be overcome by slightly scaling down the Martini protein–protein interactions in a manner, which does not interfere with the other Martini interaction parameters. By preventing excessive, irreversible, and non-selective aggregation of membrane proteins, this approach renders the consideration of lateral dynamics and protein–lipid interactions in crowded membranes by the Martini model more realistic. However, this adjusted model does not lead to an improvement in the predicted dimer structures. This implicates that the poor agreement between the Martini model and NMR structures cannot be cured by simply uniformly reducing the interactions between all protein beads. Instead, a careful amino-acid specific adjustment of the protein–protein interactions is likely required.
Biological membranes generate specific functions through compartmentalized regions such as cholesterol-enriched membrane nanodomains that host selected proteins. Despite the biological significance of nanodomains, details on their structure remain elusive. They cannot be observed via microscopic experimental techniques due to their small size, yet there is also a lack of atomistic simulation models able to describe spontaneous nanodomain formation in sufficiently simple but biologically relevant complex membranes. Here we use atomistic simulations to consider a binary mixture of saturated dipalmitoylphosphatidylcholine and cholesterol-the "minimal standard" for nanodomain formation. The simulations reveal how cholesterol drives the formation of fluid cholesterol-rich nanodomains hosting hexagonally packed cholesterol-poor lipid nanoclusters, both of which show registration between the membrane leaflets. The complex nanodomain substructure forms when cholesterol positions itself in the domain boundary region. Here cholesterol can also readily flip-flop across the membrane. Most importantly, replacing cholesterol with a sterol characterized by a less asymmetric ring region impairs the emergence of nanodomains. The model considered explains a plethora of controversial experimental results and provides an excellent basis for further computational studies on nanodomains. Furthermore, the results highlight the role of cholesterol as a key player in the modulation of nanodomains for membrane protein function.
The lateral diffusion of embedded proteins along lipid membranes in protein-poor conditions has been successfully described in terms of the Saffman-Delbrück (SD) model, which predicts that the protein diffusion coefficient D is weakly dependent on its radius R as D ∞ ln(1/R). However, instead of being protein-poor, native cell membranes are extremely crowded with proteins. On the basis of extensive molecular simulations, we here demonstrate that protein crowding of the membrane at physiological levels leads to deviations from the SD relation and to the emergence of a stronger Stokes-like dependence D ∞ 1/R. We propose that this 1/R law mainly arises due to geometrical factors: smaller proteins are able to avoid confinement effects much better than their larger counterparts. The results highlight that the lateral dynamics in the crowded setting found in native membranes is radically different from protein-poor conditions and plays a significant role in formation of functional multiprotein complexes.
Dry eye syndrome (DES), one of the most common ophthalmological diseases, is typically caused by excessive evaporation of tear fluid from the ocular surface. Excessive evaporation is linked to impaired function of the tear film lipid layer (TFLL) that covers the aqueous tear film. The principles of the evaporation resistance of the TFLL have remained unknown, however. We combined atomistic simulations with Brewster angle microscopy and surface potential experiments to explore the organization and evaporation resistance of films composed of wax esters, one of the main components of the TFLL. The results provide evidence that the evaporation resistance of the TFLL is based on crystalline-state layers of wax esters and that the evaporation rate is determined by defects in the TFLL and its coverage on the ocular surface. On the basis of the results, uncovering the nonequilibrium spreading and crystallization of TFLL films has potential to reveal new means of treating DES.
Biological membranes are tricky to investigate. They are complex in terms of molecular composition and structure, functional over a wide range of time scales, and characterized by nonequilibrium conditions. Because of all of these features, simulations are a great technique to study biomembrane behavior. A significant part of the functional processes in biological membranes takes place at the molecular level; thus computer simulations are the method of choice to explore how their properties emerge from specific molecular features and how the interplay among the numerous molecules gives rise to function over spatial and time scales larger than the molecular ones. In this review, we focus on this broad theme. We discuss the current state-of-the-art of biomembrane simulations that, until now, have largely focused on a rather narrow picture of the complexity of the membranes. Given this, we also discuss the challenges that we should unravel in the foreseeable future. Numerous features such as the actin-cytoskeleton network, the glycocalyx network, and nonequilibrium transport under ATP-driven conditions have so far received very little attention; however, the potential of simulations to solve them would be exceptionally high. A major milestone for this research would be that one day we could say that computer simulations genuinely research biological membranes, not just lipid bilayers.
Biomembranes are exceptionally crowded with proteins with typical protein-to-lipid ratios being around 1:50 - 1:100. Protein crowding has a decisive role in lateral membrane dynamics as shown by recent experimental and computational studies that have reported anomalous lateral diffusion of phospholipids and membrane proteins in crowded lipid membranes. Based on extensive simulations and stochastic modeling of the simulated trajectories, we here investigate in detail how increasing crowding by membrane proteins reshapes the stochastic characteristics of the anomalous lateral diffusion in lipid membranes. We observe that correlated Gaussian processes of the fractional Langevin equation type, identified as the stochastic mechanism behind lipid motion in noncrowded bilayer, no longer adequately describe the lipid and protein motion in crowded but otherwise identical membranes. It turns out that protein crowding gives rise to a multifractal, non-Gaussian, and spatiotemporally heterogeneous anomalous lateral diffusion on time scales from nanoseconds to, at least, tens of microseconds. Our investigation strongly suggests that the macromolecular complexity and spatiotemporal membrane heterogeneity in cellular membranes play critical roles in determining the stochastic nature of the lateral diffusion and, consequently, the associated dynamic phenomena within membranes. Clarifying the exact stochastic mechanism for various kinds of biological membranes is an important step towards a quantitative understanding of numerous intramembrane dynamic phenomena.
Lung surfactant and a tear film lipid layer are examples of biologically relevant macromolecular structures found at the air–water interface. Because of their complexity, they are often studied in terms of simplified lipid layers, the simplest example being a Langmuir monolayer. Given the profound biological significance of these lipid assemblies, there is a need to understand their structure and dynamics on the nanoscale, yet there are not many techniques able to provide this information. Atomistic molecular dynamics simulations would be a tool fit for this purpose; however, the simulation models suggested until now have been qualitative instead of quantitative. This limitation has mainly stemmed from the challenge to correctly describe the surface tension of water with simulation parameters compatible with other biomolecules. In this work, we show that this limitation can be overcome by using the recently introduced four-point OPC water model, whose surface tension for water is demonstrated to be quantitatively consistent with experimental data and which is also shown to be compatible with the commonly employed lipid models. We further establish that the approach of combining the OPC four-point water model with the CHARMM36 lipid force field provides nearly quantitative agreement with experiments for the surface pressure–area isotherm for POPC and DPPC monolayers, also including the experimentally observed phase coexistence in a DPPC monolayer. The simulation models reported in this work pave the way for nearly quantitative atomistic studies of lipid-rich biological structures at air–water interfaces.
Surfactant protein B (SP-B) is essential in transferring surface-active phospholipids from membrane-based surfactant complexes into the alveolar air–liquid interface. This allows maintaining the mechanical stability of the surfactant film under high pressure at the end of expiration; therefore, SP-B is crucial in lung function. Despite its necessity, the structure and the mechanism of lipid transfer by SP-B have remained poorly characterized. Earlier, we proposed higher-order oligomerization of SP-B into ring-like supramolecular assemblies. In the present work, we used coarse-grained molecular dynamics simulations to elucidate how the ring-like oligomeric structure of SP-B determines its membrane binding and lipid transfer. In particular, we explored how SP-B interacts with specific surfactant lipids, and how consequently SP-B reorganizes its lipid environment to modulate the pulmonary surfactant structure and function. Based on these studies, there are specific lipid–protein interactions leading to perturbation and reorganization of pulmonary surfactant layers. Especially, we found compelling evidence that anionic phospholipids and cholesterol are needed or even crucial in the membrane binding and lipid transfer function of SP-B. Also, on the basis of the simulations, larger oligomers of SP-B catalyze lipid transfer between adjacent surfactant layers. Better understanding of the molecular mechanism of SP-B will help in the design of therapeutic SP-B-based preparations and novel treatments for fatal respiratory complications, such as the acute respiratory distress syndrome.
Adsorption of metal cations onto a cellular membrane changes its properties, such as interactions with charged moieties or the propensity for membrane fusion. It is, however, unclear whether cells can regulate ion adsorption and the related functions via locally adjusting their membrane composition. We employed fluorescence techniques and computer simulations to determine how the presence of cholesterol - a key molecule inducing membrane heterogeneity - affects the adsorption of sodium and calcium onto zwitterionic phosphatidylcholine bilayers. We found that the transient adsorption of sodium is dependent on the number of phosphatidylcholine head groups, while the strong surface binding of calcium is determined by the available surface area of the membrane. Cholesterol thus does not affect sodium adsorption and only plays an indirect role in modulating the adsorption of calcium by increasing the total surface area of the membrane. These observations also indicate how lateral lipid heterogeneity can regulate various ion-induced processes including adsorption of peripheral proteins, nanoparticles, and other molecules onto membranes.
Extracellular and cytosolic leaflets in cellular membranes are distinctly different in lipid composition, yet they contribute together to signaling across the membranes. Here we consider a mechanism based on long-chain gangliosides for coupling the extracellular and cytosolic membrane leaflets together. Based on atomistic molecular dynamics simulations, we find that long-chain GM1 in the extracellular leaflet exhibits a strong tendency to protrude into the opposing bilayer leaflet. This interdigitation modulates the order in the cytosolic monolayer and thereby strengthens the interaction and coupling across a membrane. Coarse-grained simulations probing longer time scales in large membrane systems indicate that GM1 in the extracellular leaflet modulates the phase behavior in the cytosolic monolayer. While short-chain GM1 maintains phase-symmetric bilayers with a strong membrane registration effect, the situation is altered with long-chain GM1. Here, the significant interdigitation induced by long-chain GM1 modulates the behavior in the cytosolic GM1-free leaflet, weakening and slowing down the membrane registration process. The observed physical interaction mechanism provides a possible means to mediate or foster transmembrane communication associated with signal transduction.
We present a theoretical model describing the magnetic-state population dynamics of spin-degenerate two-level atoms interacting with a narrowband, on-resonance, partially polarized electromagnetic field. The field is allowed to have three uncorrelated orthogonal vector components. The model is applied to a four-magnetic-state atom system with a single excited and three ground states. Even if the field is narrowband, the population dynamics may be completely predicated by the fluctuating polarization of light. In our examples, the fluctuation effects are mainly governed by a single parameter, the degree of polarization of the field.
We use classical statistical mechanics and thermodynamics to describe the response of a trapped multi-species atomic sample to a local deformation in the confining potential. An adiabatic deformation may not only increase the peak phase-space density, but also lower the temperature and spin-polarize the atoms.
We use classical statistical mechanics and thermodynamics to describe the response of a trapped multi-species atomic sample to a local deformation in the confining potential. An adiabatic deformation may not only increase the peak phase-space density, but also lower the temperature and spin-polarize the atoms.
We present a theoretical model describing the magnetic-state population dynamics of spin-degenerate two-level atoms interacting with a narrowband, on-resonance, partially polarized electromagnetic field. The field is allowed to have three uncorrelated orthogonal vector components. The model is applied to a four-magnetic-state atom system with a single excited and three ground states. Even if the field is narrowband, the population dynamics may be completely predicated by the fluctuating polarization of light. In our examples, the fluctuation effects are mainly governed by a single parameter, the degree of polarization of the field.
G protein-coupled receptors (GPCRs) control cellular signaling and responses. Many of these GPCRs are modulated by cholesterol and polyunsaturated fatty acids (PUFAs) which have been shown to co-exist with saturated lipids in ordered membrane domains. However, the lipid compositions of such domains extracted from the brain cortex tissue of individuals suffering from GPCR-associated neurological disorders show drastically lowered levels of PUFAs. Here, using free energy techniques and multiscale simulations of numerous membrane proteins, we show that the presence of the PUFA DHA helps helical multi-pass proteins such as GPCRs partition into ordered membrane domains. The mechanism is based on hybrid lipids, whose PUFA chains coat the rough protein surface, while the saturated chains face the raft environment, thus minimizing perturbations therein. Our findings suggest that the reduction of GPCR partitioning to their native ordered environments due to PUFA depletion might affect the function of these receptors in numerous neurodegenerative diseases, where the membrane PUFA levels in the brain are decreased. We hope that this work inspires experimental studies on the connection between membrane PUFA levels and GPCR signaling.
Folding and packing of membrane proteins are highly influenced by the lipidic component of the membrane. Here, we explore how the hydrophobic mismatch (the difference between the hydrophobic span of a transmembrane protein region and the hydrophobic thickness of the lipid membrane around the protein) influences transmembrane helix packing in a cellular environment. Using a ToxRED assay in Escherichia coli and a Bimolecular Fluorescent Complementation approach in human-derived cells complemented by atomistic molecular dynamics simulations we analyzed the dimerization of Glycophorin A derived transmembrane segments. We concluded that, biological membranes can accommodate transmembrane homo-dimers with a wide range of hydrophobic lengths. Hydrophobic mismatch and its effects on dimerization are found to be considerably weaker than those previously observed in model membranes, or under in vitro conditions, indicating that biological membranes (particularly eukaryotic membranes) can adapt to structural deformations through compensatory mechanisms that emerge from their complex structure and composition to alleviate membrane stress. Results based on atomistic simulations support this view, as they revealed that Glycophorin A dimers remain stable, despite of poor hydrophobic match, using mechanisms based on dimer tilting or local membrane thickness perturbations. Furthermore, hetero-dimers with large length disparity between their monomers are also tolerated in cells, and the conclusions that one can draw are essentially similar to those found with homo-dimers. However, large differences between transmembrane helices length hinder the monomer/dimer equilibrium, confirming that, the hydrophobic mismatch has, nonetheless, biologically relevant effects on helix packing in vivo.
There is evidence that lipids can be allosteric regulators of membrane protein structure and activation. However, there are no data showing how exactly the regulation emerges from specific lipid-protein interactions. Here we show in atomistic detail how the human β2-adrenergic receptor (β2AR) - a prototypical G protein-coupled receptor - is modulated by cholesterol in an allosteric fashion. Extensive atomistic simulations show that cholesterol regulates β2AR by limiting its conformational variability. The mechanism of action is based on the binding of cholesterol at specific high-affinity sites located near the transmembrane helices 5-7 of the receptor. The alternative mechanism, where the β2AR conformation would be modulated by membrane-mediated interactions, plays only a minor role. Cholesterol analogues also bind to cholesterol binding sites and impede the structural flexibility of β2AR, however cholesterol generates the strongest effect. The results highlight the capacity of lipids to regulate the conformation of membrane receptors through specific interactions.
We report on a quantitative experimental investigation of velocity-changing collisions by means of velocity-selective optical pumping (VSOP). We have calculated the VSOP line shape for an atom with hyperfine structure with the use of two phenomenological kernels for the collision effects: the Keilson-Storer kernel, and a two-term kernel consisting of a broad Keilson-Storer part and a narrower Gaussian component. Corrections were included to account for the finite absorption in the sample and the backward reflection of the pumping beam. The experiments were carried out in sodium vapor with neon as the perturber gas. The D1 line of sodium was used for optical pumping, and the orientation of the ground state was detected. Free parameters of the theory were determined by fitting the predicted line shapes to experimental curves. The Keilson-Storer kernel proved unsatisfactory, but the two-term kernel reproduced well the observed line shapes over the entire collision profiles in the neon pressure range 0-57 mtorr. In an independent experiment using rapidly modulated VSOP we also measured directly the cross section of velocity-changing collisions: σ=(1.13±0.10)×10exp−14 cm2. The large weight obtained for the narrow Gaussian from the fits, as well as the collision cross section which is three times as large as the cross section deduced from tabulated gas kinetic radii, may indicate the presence of collisions with relatively small velocity changes in addition to hard-sphere encounters.
Organic dye-tagged lipid analogs are essential for many fluorescence-based investigations of complex membrane structures, especially when using advanced microscopy approaches. However, lipid analogs may interfere with membrane structure and dynamics, and it is not obvious that the properties of lipid analogs would match those of non-labeled host lipids. In this work, we bridged atomistic simulations with super-resolution imaging experiments and biomimetic membranes to assess the performance of commonly used sphingomyelin-based lipid analogs. The objective was to compare, on equal footing, the relative strengths and weaknesses of acyl chain labeling, headgroup labeling, and labeling based on poly-ethyl-glycol (PEG) linkers in determining biomembrane properties. We observed that the most appropriate strategy to minimize dye-induced membrane perturbations and to allow consideration of Brownian-like diffusion in liquid-ordered membrane environments is to decouple the dye from a membrane by a PEG linker attached to a lipid headgroup. Yet, while the use of PEG linkers may sound a rational and even an obvious approach to explore membrane dynamics, the results also suggest that the dyes exploiting PEG linkers interfere with molecular interactions and their dynamics. Overall, the results highlight the great care needed when using fluorescent lipid analogs, in particular accurate controls.
Accurately calculating rate constants of macroscopic chemical processes from molecular dynamics simulations is a long-sought but elusive goal. The problem is particularly relevant for processes occurring in biological systems, as is the case for ligand-protein and ligand-membrane interactions. Several formalisms to determine rate constants from easily accessible free-energy profiles [Δ Go( z)] of a molecule along a coordinate of interest have been proposed. However, their applicability for molecular interactions in condensed media has not been critically evaluated or validated. This work presents such evaluation and validation and introduces improved methodology. As a case study, we have characterized quantitatively the rate of translocation of cholesterol across 1-palmitoyl-2-oleoyl- sn-glycero-3-phosphocholine bilayers. Translocation across lipid bilayers is the rate-limiting step in the permeation of most drugs through biomembranes. We use coarse-grained molecular dynamics simulations and different kinetic formalisms to calculate this rate constant. A self-consistent test of the applicability of various available formalisms is provided by comparing their predictions with the translocation rates obtained from actual events observed in long unrestrained simulations. To this effect, a novel procedure was used to obtain the effective rate constant, based on an analysis of time intervals between transitions among different states along the reaction coordinate. While most tested formalisms lead to results in reasonable agreement (within a factor of 5) with this effective rate constant, the most adequate one is based on the explicit relaxation frequencies from the transition state in the forward and backward directions along the reaction coordinate.
Pulmonary surfactant is a complex mixture of lipids and proteins lining the interior of the alveoli, and constitutes the first barrier to both oxygen and pathogens as they progress toward blood circulation. Despite decades of study, the behavior of the pulmonary surfactant at the molecular scale is poorly understood, which hinders the development of effective surfactant replacement therapies, useful in the treatment of several lung-related diseases. In this work, we combined all-atom molecular dynamics simulations, Langmuir trough measurements, and AFM imaging to study synthetic four-component lipid monolayers designed to model protein-free pulmonary surfactant. We characterized the structural and dynamic properties of the monolayers with a special focus on lateral heterogeneity. Remarkably, simulations reproduce almost quantitatively the experimental data on pressure-area isotherms and the presence of lateral heterogeneities highlighted by AFM. Quite surprisingly, the pressure-area isotherms do not show a plateau region, despite the presence of liquid-condensed nanometer-sized domains at surface pressures larger than 20 mN/m. In the simulations, the liquid-condensed domains were small and transient, but they did not coalesce to yield a separate phase. They were only slightly enriched in DPPC and cholesterol, and their chemical composition remained very similar to the overall composition of the monolayer membrane. Instead, they differed from liquid-expanded regions in terms of membrane thickness (in agreement with AFM data), diffusion rates, as well as acyl chain packing and orientation. We hypothesize that such lateral heterogeneities are crucial for lung surfactant function, as they allow both efficient packing, to achieve low surface tension, and sufficient fluidity, critical for rapid adsorption to the air–liquid interface during the breathing cycle.
Membrane levels of docosahexaenoic acid (DHA), an essential omega-3 polyunsaturated fatty acid (ω-3 PUFA), are decreased in common neuropsychiatric disorders. DHA modulates key cell membrane properties like fluidity, thereby affecting the behaviour of transmembrane proteins like G protein-coupled receptors (GPCRs). These receptors, which have special relevance for major neuropsychiatric disorders have recently been shown to form dimers or higher order oligomers, and evidence suggests that DHA levels affect GPCR function by modulating oligomerisation. In this study, we assessed the effect of membrane DHA content on the formation of a class of protein complexes with particular relevance for brain disease: adenosine A2A and dopamine D2 receptor oligomers. Using extensive multiscale computer modelling, we find a marked propensity of DHA for interaction with both A2A and D2 receptors, which leads to an increased rate of receptor oligomerisation. Bioluminescence resonance energy transfer (BRET) experiments performed on living cells suggest that this DHA effect on the oligomerisation of A2A and D2 receptors is purely kinetic. This work reveals for the first time that membrane ω-3 PUFAs play a key role in GPCR oligomerisation kinetics, which may have important implications for neuropsychiatric conditions like schizophrenia or Parkinson's disease.
Phosphatidylinositol-transfer proteins (PITPs) regulate phosphoinositide signaling in eukaryotic cells. The defining feature of PITPs is their ability to exchange phosphatidylinositol (PtdIns) molecules between membranes, and this property is central to PITP-mediated regulation of lipid signaling. However, the details of the PITP-mediated lipid exchange cycle remain entirely obscure. Here, all-atom molecular dynamics simulations of the mammalian StART-like PtdIns/phosphatidylcholine (PtdCho) transfer protein PITP, both on membrane bilayers and in solvated systems, informed downstream biochemical analyses that tested key aspects of the hypotheses generated by the molecular dynamics simulations. These studies provided five key insights into the PITP lipid exchange cycle: (i) interaction of PITP with the membrane is spontaneous and mediated by four specific protein substructures; (ii) the ability of PITP to initiate closure around the PtdCho ligand is accompanied by loss of flexibility of two helix/loop regions, as well as of the C-terminal helix; (iii) the energy barrier of phospholipid extraction from the membrane is lowered by a network of hydrogen bonds between the lipid molecule and PITP; (iv) the trajectory of PtdIns or PtdCho into and through the lipid-binding pocket is chaperoned by sets of PITP residues conserved throughout the StART-like PITP family; and (v) conformational transitions in the C-terminal helix have specific functional involvements in PtdIns transfer activity. Taken together, these findings provide the first mechanistic description of key aspects of the PITP PtdIns/PtdCho exchange cycle and offer a rationale for the high conservation of particular sets of residues across evolutionarily distant members of the meta-zoan StART-like PITP family.
Despite the vast amount of experimental and theoretical studies on the binding affinity of cations - especially the biologically relevant Na(+) and Ca(2+) - for phospholipid bilayers, there is no consensus in the literature. Here we show that by interpreting changes in the choline headgroup order parameters according to the 'molecular electrometer' concept [Seelig et al., Biochemistry, 1987, 26, 7535], one can directly compare the ion binding affinities between simulations and experiments. Our findings strongly support the view that in contrast to Ca(2+) and other multivalent ions, Na(+) and other monovalent ions (except Li(+)) do not specifically bind to phosphatidylcholine lipid bilayers at sub-molar concentrations. However, the Na(+) binding affinity was overestimated by several molecular dynamics simulation models, resulting in artificially positively charged bilayers and exaggerated structural effects in the lipid headgroups. While qualitatively correct headgroup order parameter response was observed with Ca(2+) binding in all the tested models, no model had sufficient quantitative accuracy to interpret the Ca(2+):lipid stoichiometry or the induced atomistic resolution structural changes. All scientific contributions to this open collaboration work were made publicly, using nmrlipids.blogspot.fi as the main communication platform.
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.
Transbilayer phospholipid transfer (flip–flop) is a vital process for all cellular life. This intrinsically slow process is facilitated by integral membrane proteins called flippases and scramblases, which lower the free energy barrier to such a level that phospholipid flip–flop can rapidly occur either with help of external energy sources such as ATP or by thermal fluctuations alone. The existence of flippases has been known for some time, but the identities of the phospholipid translocators are still unknown. The existence of scramblases is less clear, since only related gene sequences have been identified so far. Also, the mechanisms by which phospholipids carry out flip–flops are yet to be identified. Further knowledge on scramblase activities could be helpful in understanding and preventing many diseases. For instance, programmed cell death begins when phosphatidylserine flips in an uncontrollable manner from the cytosolic leaflet to the extracellular side and this process is assumed to take place due to certain membrane proteins. This event in turn creates a signal for extracellular phagocytes by marking the cell for apoptosis. Apoptotic cells are often linked to tumor progression in which it is suggested that mutations in the scramblase genes can facilitate cancer growth. Proper scramblase activation during cancer progression could be used to remove harmful cells. Recent experimental studies have suggested that opsin, one of the G protein- coupled receptors found in photoreceptor cells of the retina, is a phospholipid flip- pase and its counterpart rhodopsin could be a possible scramblase. The purpose of this thesis is to use atomistic molecular dynamics simulations to examine the phos- pholipid scrambling properties of rhodopsin. The results can be used as a basis for further research regarding the subject. The possible flipping routes are investigated using steered MD simulations, and the free energy differences along the translocation paths are calculated by the umbrella sampling method. The results show that rhodopsin significantly lowers the free energy barrier of the membrane, thus functioning as a flippase. The observed flip–flop route taken by the phospholipids is located near the surface of rhodopsin.
Pulmonary surfactant is a surface active lipid-protein complex covering the air-liquid interface at the surface of the alveoli in the lungs. Its main function is to reduce the surface tension at the interface, and thus to minimize the work of breathing and prevent the alveoli from collapsing at the end of the breathing cycle. Pulmonary surfactant protein B (SP-B) is an essential protein, necessary for the formation and maintaining of the film at the interface. Despite its importance, there has been no structural model for SP-B, or information about its molecular mechanism of function. In this thesis, we study the specific lipid interactions and membrane binding conformations of our new refined model for the SP-B hexamer of dimers. We use molecular dynamics simulations with the coarse-grained MARTINI force field for spontaneous lipid self-assembly and monolayer studies with SP-B. We concentrate on specific protein-lipid interactions, lateral lipid reorganization, and perturbations caused by SP-B in membranes. The results show specific lipid interaction sites in the structure of SP-B. We found that the protein causes lateral reorganization of lipids in monolayers and shows specificity towards phosphatidylglycerol and cholesterol. We further found that SP-B as a hexamer of dimers has specific membrane binding residues that orient the protein parallel to the surface of the membrane. SP-B causes lipid protrusions in monolayers and membranes. These results imply a molecular mechanism for lipid transfer through a SP-B oligomer ring in the surfactant.