Methodologies for the analysis of instantaneous lipid diffusion in MD simulations of large membrane systems

Electron videography of a lipid-protein tango

Biological phenomena, from enzymatic catalysis to synaptic transmission, originate in the structural transformations of biomolecules and biomolecular assemblies in liquid water. However, directly imaging these nanoscopic dynamics without probes or labels has been a fundamental methodological challenge. Here, we developed an approach for "electron videography"-combining liquid phase electron microscopy with molecular modeling-with which we filmed the nanoscale structural fluctuations of individual, suspended, and unlabeled membrane protein nanodiscs in liquid. Systematic comparisons with biochemical data and simulation indicate the graphene encapsulation involved can afford sufficiently reduced effects of the illuminating electron beam for these observations to yield quantitative fingerprints of nanoscale lipid-protein interactions. Our results suggest that lipid-protein interactions delineate dynamically modified membrane domains across unexpectedly long ranges. Moreover, they contribute to the molecular mechanics of the nanodisc as a whole in a manner specific to the protein within. Overall, this work illustrates an experimental approach to film, quantify, and understand biomolecular dynamics at the nanometer scale.

From complex data to clear insights: visualizing molecular dynamics trajectories

Advances in simulations, combined with technological developments in high-performance computing, have made it possible to produce a physically accurate dynamic representation of complex biological systems involving millions to billions of atoms over increasingly long simulation times. The analysis of these computed simulations is crucial, involving the interpretation of structural and dynamic data to gain insights into the underlying biological processes. However, this analysis becomes increasingly challenging due to the complexity of the generated systems with a large number of individual runs, ranging from hundreds to thousands of trajectories. This massive increase in raw simulation data creates additional processing and visualization challenges. Effective visualization techniques play a vital role in facilitating the analysis and interpretation of molecular dynamics simulations. In this paper, we focus mainly on the techniques and tools that can be used for visualization of molecular dynamics simulations, among which we highlight the few approaches used specifically for this purpose, discussing their advantages and limitations, and addressing the future challenges of molecular dynamics visualization.

The intricate link between membrane lipid structure and composition and membrane structural properties in bacterial membranes

It is now evident that the cell manipulates lipid composition to regulate different processes such as membrane protein insertion, assembly and function. Moreover, changes in membrane structure and properties, lipid homeostasis during growth and differentiation with associated changes in cell size and shape, and responses to external stress have been related to drug resistance across mammalian species and a range of microorganisms. While it is well known that the biomembrane is a fluid self-assembled nanostructure, the link between the lipid components and the structural properties of the lipid bilayer are not well understood. This perspective aims to address this topic with a view to a more detailed understanding of the factors that regulate bilayer structure and flexibility. We describe a selection of recent studies that address the dynamic nature of bacterial lipid diversity and membrane properties in response to stress conditions. This emerging area has important implications for a broad range of cellular processes and may open new avenues of drug design for selective cell targeting.

Multimillion Atom Simulations of Di-8-ANEPPS Chromophores Embedded in a Model Plasma Membrane: Toward the Investigation of Realistic Dyed Cell Membranes

A multistep computational approach has been employed to study a multimillion all-atom dyed plasma membrane, with no less than 42 different lipid species spanning the major head groups and a variety of fatty acids, as well as cholesterol, with the objective of investigating its structure and dynamics, as well as its impact on the embedded di-8-ANEPPS dyes. The latter are commonly used as bioimaging probes and serve as local microscopes. So, they provide information on membrane morphology via their second harmonic nonlinear optical (NLO) responses, which have the advantage of being specific to interface regions and sensitive to the chromophore environment. In previous studies, this chromophore has only been studied in simpler membrane models, far from the complexity of real lipid bilayers, while, owing to the ever-increasing computational resources, multimillion lipid bilayers have been studied, giving access to the effects of its heterogeneity. First, using molecular dynamics (MD) simulations, it is found that the combination of lipids produces a more ordered and denser membrane compared to its homogeneous model counterparts, while the local environment of the embedded dyes becomes enriched in phosphatidylcholine. Subsequently, the second harmonic first hyperpolarizability of the probes was calculated at the TDDFT level on selected frames of MD, highlighting the influence of the lipid environment. Due to the complexity of the system, machine learning (ML) tools have been employed to establish relationships between the membrane structural parameters, the orientation of the probes, and their NLO responses. These ML approaches have revealed influential features, including the presence of diacylglycerol lipids close to the dye. On the whole, this work provides a first step toward understanding the cooperation, synergy, and interactions that occur in such complex guest-host environments, which have emerged as new targets for drug design and membrane lipid therapy.

Distinct roles of graphene and graphene oxide nanosheets in regulating phospholipid flip-flop

Two-dimensional (2D) nanomaterials, such as graphene nanosheets (GNs) and graphene oxide nanosheets (GOs), could adhere onto or insert into a biological membrane, leading to a change in membrane properties and biological activities. Consequently, GN and GO become potential candidates for mediating interleaflet phospholipid transfer. In this work, molecular dynamics (MD) simulations were employed to investigate the effects of GN and GO on lipid flip-flop behavior and the underlying molecular mechanisms. Of great interest is that GN and GO work in opposite directions. The inserted GN can induce the formation of an ordered nanodomain, which dramatically elevates the free energy barrier of flipping phospholipids from one leaflet to the other, thus leading to a decreased lipid flip-flop rate. In contrast, the embedded GO can catalyze the transport of phospholipids between membrane leaflets by facilitating the formation of water pores. These results suggest that GN may work as an inhibitor of the interleaflet lipid translocation, while GO may play the role of scramblases. These findings are expected to expand promising biomedical applications of 2D nanomaterials.

A brief history of visualizing membrane systems in molecular dynamics simulations

Understanding lipid dynamics and function, from the level of single, isolated molecules to large assemblies, is more than ever an intensive area of research. The interactions of lipids with other molecules, particularly membrane proteins, are now extensively studied. With advances in the development of force fields for molecular dynamics simulations (MD) and increases in computational resources, the creation of realistic and complex membrane systems is now common. In this perspective, we will review four decades of the history of molecular dynamics simulations applied to membranes and lipids through the prism of molecular graphics.

Adherens junctions organize size-selective proteolytic hotspots critical for Notch signalling

Adherens junctions (AJs) create spatially, chemically and mechanically discrete microdomains at cellular interfaces. Here, using a mechanogenetic platform that generates artificial AJs with controlled protein localization, clustering and mechanical loading, we find that AJs also organize proteolytic hotspots for γ-secretase with a spatially regulated substrate selectivity that is critical in the processing of Notch and other transmembrane proteins. Membrane microdomains outside of AJs exclusively organize Notch ligand-receptor engagement (LRE microdomains) to initiate receptor activation. Conversely, membrane microdomains within AJs exclusively serve to coordinate regulated intramembrane proteolysis (RIP microdomains). They do so by concentrating γ-secretase and primed receptors while excluding full-length Notch. AJs induce these functionally distinct microdomains by means of lipid-dependent γ-secretase recruitment and size-dependent protein segregation. By excluding full-length Notch from RIP microdomains, AJs prevent inappropriate enzyme-substrate interactions and suppress spurious Notch activation. Ligand-induced ectodomain shedding eliminates size-dependent segregation, releasing Notch to translocate into AJs for processing by γ-secretase. This mechanism directs radial differentiation of ventricular zone-neural progenitor cells in vivo and more broadly regulates the proteolysis of other large cell-surface receptors such as amyloid precursor protein. These findings suggest an unprecedented role of AJs in creating size-selective spatial switches that choreograph γ-secretase processing of multiple transmembrane proteins regulating development, homeostasis and disease.

Design - a new way to look at old molecules

We discuss how design enriches molecular science, particularly structural biology and bioinformatics. We present two use cases, one in academic practice and the other to design for outreach. The first case targets the representation of ion channels and their dynamic properties. In the second, we document a transition process from a research environment to general-purpose designs. Several testimonials from practitioners are given. By describing the design process of abstracted shapes, exploded views of molecular structures, motion-averaged slices, 360-degree panoramic projections, and experiments with lit sphere shading, we document how designers help make scientific data accessible without betraying its meaning, and how a creative mind adds value over purely data-driven visualizations. A similar conclusion was drawn for public outreach, as we found that comic-book-style drawings are better suited for communicating science to a broad audience.

The stressed life of a lipid in the Zika virus membrane

Protein-lipid interactions modulate a plethora of physiopathologic processes and have been the subject of countless studies. However, these kinds of interactions in the context of viral envelopes have remained relatively unexplored, partially because the intrinsically small dimensions of the molecular systems escape to the current resolution of experimental techniques. However, coarse-grained and multiscale simulations may fill that niche, providing nearly atomistic resolution at an affordable computational price. Here we use multiscale simulations to characterize the lipid-protein interactions in the envelope of the Zika Virus, a prominent member of the Flavivirus genus. Comparisons between the viral envelope and simpler molecular systems indicate that the viral membrane is under extreme pressures and asymmetric forces. Furthermore, the dense net of protein-protein contacts established by the envelope proteins creates poorly solvated regions that destabilize the external leaflet leading to a decoupled dynamics between both membrane layers. These findings lead to the idea that the Flaviviral membrane may store a significant amount of elastic energy, playing an active role in the membrane fusion process.

Interactions between polymyxin B and various bacterial membrane mimics: A molecular dynamics study

Polymyxin B (PMB) is clinically used as a last-line therapy against life-threatening Gram-negative "superbugs". However, thorough understanding of the membrane actions of PMB at a molecular level is still lacking. In this work, a variety of bacterial membrane mimics with varying lipid compositions were built, and their interactions with PMB were systematically investigated using coarse-grained molecular dynamics simulation. PMB demonstrated characteristic preference to specific lipid species during its interaction with different membrane systems, such as the rough mutant lipipolysacchrides (Re LPS) preference in an outer membrane (OM) or the cardiolipin and POPG affinity in an inner membrane (IM). As a result of the lipid-specific actions, complicated membrane interaction states of PMB were observed, including adsorption on the OM surface. In contrast, for the IM or a mutative OM containing "impurity lipids" like POPE, POPG or lipid A, it could insert into the membrane via its acyl chain. Such actions of PMB influence the structure and lipid mobility of the membrane. In particular, the OM-bound PMB breaks the synchronous movement of Re LPS molecules in the outer leaflet and makes them diffuse more randomly, while its insertion into IM blocks the phospholipid diffusion and makes the membrane more homogeneous in the trajectory space. Our results provide insight into the action mechanism of PMB at a membrane level and a foundation for developing novel and safer polymyxin strategies for better clinical use.

High spatio-temporal resolution measurement of A1 R and A2A R interactions combined with Iem-spFRET and E-FRET methods

A₁ R-A_2A R heterodimers regulate striatal glutamatergic neurotransmission. However, few researches about kinetics have been reported. Here, we combined Iem-spFRET and E-FRET to investigate the kinetics of A₁ R and A_2A R interaction. Iem-spFRET obtains the energy transfer efficiency of the whole cell. E-FRET gets energy transfer efficiency with high spatial resolution, whereas, it was prone to biases because background was easily selected due to manual operation. To study the interaction with high spatio-temporal resolution, Iem-spFRET was used to correct the deviation of E-FRET. In this paper, A₁ R and A_2A R interaction was monitored, and the changes of FRET efficiency of the whole or/and partial cell membrane were described. The results showed that activation of A₁ R or A_2A R leads to rapid aggregation, inhibition of A₁ R or A_2A R leads to slow segregation, and the interaction is reversible. These results demonstrated that combination of Iem-spFRET and E-FRET could measure A₁ R and A_2A R interaction with high spatio-temporal resolution.

Atomistic and coarse-grained simulations of membrane proteins: A practical guide

Membrane proteins are amphipathic macromolecules whose exposed hydrophobic surfaces promote interactions with lipid membranes. Membrane proteins are remarkably diverse in terms of chemical composition and correspondingly, their biological functions and general biophysical behavior. Conventional experimental techniques provide an approach to study specific properties of membrane proteins e.g. their surface features, the nature and abundance of stabilizing intramolecular forces, preferred bilayer orientation, and the characteristics of their annular lipid shells. Molecular modeling software-and in particular, the suite of molecular dynamics algorithms-enables a more comprehensive exploration of dynamic membrane protein behavior. Molecular dynamics methods enable users to produce stepwise trajectories of proteins on arbitrary spatiotemporal scales that enable the easy identification of dynamic interactions that are beyond the scope of conventional analytical techniques. This article explains the molecular dynamics theoretical framework and popular step-by-step approaches for simulating membrane proteins in planar, and to a lesser extent, nonplanar lipid geometries. We detail popular procedures and computational tools that produce well-packed configurations of lipids and proteins and additionally, the efficient molecular dynamics simulation algorithms that reproduce their dynamic interactions.

Modelling lipid systems in fluid with Lattice Boltzmann Molecular Dynamics simulations and hydrodynamics

In this work we present the coupling between Dry Martini, an efficient implicit solvent coarse-grained model for lipids, and the Lattice Boltzmann Molecular Dynamics (LBMD) simulation technique in order to include naturally hydrodynamic interactions in implicit solvent simulations of lipid systems. After validating the implementation of the model, we explored several systems where the action of a perturbing fluid plays an important role. Namely, we investigated the role of an external shear flow on the dynamics of a vesicle, the dynamics of substrate release under shear, and inquired the dynamics of proteins and substrates confined inside the core of a vesicle. Our methodology enables future exploration of a large variety of biological entities and processes involving lipid systems at the mesoscopic scale where hydrodynamics plays an essential role, e.g. by modulating the migration of proteins in the proximity of membranes, the dynamics of vesicle-based drug delivery systems, or, more generally, the behaviour of proteins in cellular compartments.

Contrasting Assemblies of Oppositely Charged Proteins

Oppositely charged proteins can form soluble assemblies that under specific physical chemical conditions lead to liquid-liquid phase separation, also called heteroprotein coacervation. Increasing evidence suggests that surface charge anisotropy plays a key role in heteroprotein complexation, and coacervation. Here, we investigated complexation of an acidic protein, β-lactoglobulin (BLG), with two basic proteins, rapeseed napin (NAP) and lysozyme (LYS), of similar net charge and size but differing in surface charge distribution. Using turbidity measurements and isothermal titration calorimetry, we confirmed that LYS binds BLG as expected from previous studies. This interaction leads to two types of phase separation phenomena, depending on pH: liquid-solid phase separation in the case of strong electrostatic attraction and liquid-liquid phase separation for weaker attraction. More interestingly, we showed using dynamic light scattering that NAP interacts with BLG, resulting in formation of assemblies in the nanometer size range. The formation of assemblies was also evident when modeling the interactions using Brownian dynamics for both BLG + NAP and BLG + LYS. Similarly, to DLS, BLG and NAP formed smaller assemblies than BLG with LYS. The molecular details rather than the net charge of BLG and NAP may therefore play a role in their assembly. Furthermore, simulated BLG + NAP assemblies were larger than those experimentally detected by DLS. We discuss the discrepancy between experiments and simulations in relation to the limitations of modelling precisely the molecular characteristics of proteins.

Multiscale Simulations of Biological Membranes: The Challenge To Understand Biological Phenomena in a Living Substance

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.

Emerging Diversity in Lipid-Protein Interactions

Membrane lipids interact with proteins in a variety of ways, ranging from providing a stable membrane environment for proteins to being embedded in to detailed roles in complicated and well-regulated protein functions. Experimental and computational advances are converging in a rapidly expanding research area of lipid–protein interactions. Experimentally, the database of high-resolution membrane protein structures is growing, as are capabilities to identify the complex lipid composition of different membranes, to probe the challenging time and length scales of lipid–protein interactions, and to link lipid–protein interactions to protein function in a variety of proteins. Computationally, more accurate membrane models and more powerful computers now enable a detailed look at lipid–protein interactions and increasing overlap with experimental observations for validation and joint interpretation of simulation and experiment. Here we review papers that use computational approaches to study detailed lipid–protein interactions, together with brief experimental and physiological contexts, aiming at comprehensive coverage of simulation papers in the last five years. Overall, a complex picture of lipid–protein interactions emerges, through a range of mechanisms including modulation of the physical properties of the lipid environment, detailed chemical interactions between lipids and proteins, and key functional roles of very specific lipids binding to well-defined binding sites on proteins. Computationally, despite important limitations, molecular dynamics simulations with current computer power and theoretical models are now in an excellent position to answer detailed questions about lipid–protein interactions.

Theoretical Insights into the Interactions between Star-Shaped Antimicrobial Polypeptides and Bacterial Membranes

A structurally nanoengineered antimicrobial polypeptide consisting of lysine and valine residues is a new class of antimicrobial agent with superior antibacterial activity against multidrug-resistant bacteria and low toxicity toward mammalian cells. Utilizing coarse-grained models, we studied the interactions of microbial cytoplasmic membranes with polypeptides of either (K₂V₁)₅ (star-KV) or CM15 (star-CM15). Our computational results verify the low toxicity of polypeptides of (K₂V₁)₅ toward the dipalmitoyl phosphatidylcholine bilayer. This low toxicity is demonstrated to originate from weakened hydrophobicity combined with its random coil conformation for (K₂V₁)₅ because of the highly abundant valine residues, compared with the typical antimicrobial peptides, such as CM15. In the interactions with a palmitoyl-oleoyl-phosphatidylethanolamine/palmitoyl-oleoyl-phosphatidylglycerol bilayer, star-KV has greater ability in phase separation and generation of phase boundary defects not only in lipid redistribution but also in lateral dynamic movements, although both star-KV and star-CM15 can extract the phosphatidylglycerol lipids and purify the phosphatidylethanolamine lipids into continuum domains. We suggest that the polypeptide of (K₂V₁)₅ can nondisruptively kill bacteria by hampering bacterial metabolism through reorganizing lipid domain distribution and simultaneously "freezing" lipid movement.

Influence of membrane lipid composition on the structure and activity of γ-secretase

Insight into the effect of bilayer lipid composition on the GS structural ensemble and function using multiscale computational modeling approaches.

Molecular Modeling of Multidrug Properties of Resistance Nodulation Division (RND) Transporters

Efflux pumps of the resistance nodulation division (RND) superfamily are among the major contributors to intrinsic and acquired multidrug resistance in Gram-negative bacteria. Structural information on AcrAB-TolC and MexAB-OprM, major efflux pumps of Escherichia coli and Pseudomonas aeruginosa respectively, boosted intensive research aimed at understanding the molecular mechanisms ruling the active extrusion processes. In particular, several studies were devoted to the understanding of the determinants behind the extraordinary broad specificity of the RND transporters AcrB and MexB. In this chapter, we discuss the ever-growing role computational methods have been playing in deciphering key structural and dynamical features of these transporters and of their interaction with substrates and inhibitors. We further discuss and illustrate examples from our lab of how molecular docking, homology modeling, all-atom molecular dynamics simulations and in silico free energy estimations can all together give precious insights into the processes of recognition and extrusion of substrates, as well as on the possible inhibition strategies.

It Is Complicated: Curvature, Diffusion, and Lipid Sorting within the Two Membranes of Escherichia coli

The cell envelope of Gram-negative bacteria is composed of two membranes separated by a soluble region. Here, we report microsecond time scale coarse-grained molecular dynamics simulations of models of the Escherichia coli cell envelope that incorporate both membranes and various native membrane proteins. Our results predict that both the inner and outer membranes curve in a manner dependent on the size of the embedded proteins. The tightly cross-linked lipopolysaccharide molecules (LPS) of the outer membrane cause a strong coupling between the movement of proteins and lipids. While the flow of phospholipids is more random, their diffusion is nevertheless influenced by nearby proteins. Our results reveal protein-induced lipid sorting, whereby cardiolipin is significantly enriched within the vicinity of the water channel AqpZ and the multidrug efflux pump AcrBZ. In summary, our results provide unprecedented details of the intricate relationship between both membranes of E. coli and the proteins embedded within them.

Excessive aggregation of membrane proteins in the Martini model

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.

Computational Lipidomics of the Neuronal Plasma Membrane

Membrane lipid composition varies greatly within submembrane compartments, different organelle membranes, and also between cells of different cell stage, cell and tissue types, and organisms. Environmental factors (such as diet) also influence membrane composition. The membrane lipid composition is tightly regulated by the cell, maintaining a homeostasis that, if disrupted, can impair cell function and lead to disease. This is especially pronounced in the brain, where defects in lipid regulation are linked to various neurological diseases. The tightly regulated diversity raises questions on how complex changes in composition affect overall bilayer properties, dynamics, and lipid organization of cellular membranes. Here, we utilize recent advances in computational power and molecular dynamics force fields to develop and test a realistically complex human brain plasma membrane (PM) lipid model and extend previous work on an idealized, “average” mammalian PM. The PMs showed both striking similarities, despite significantly different lipid composition, and interesting differences. The main differences in composition (higher cholesterol concentration and increased tail unsaturation in brain PM) appear to have opposite, yet complementary, influences on many bilayer properties. Both mixtures exhibit a range of dynamic lipid lateral inhomogeneities (“domains”). The domains can be small and transient or larger and more persistent and can correlate between the leaflets depending on lipid mixture, Brain or Average, as well as on the extent of bilayer undulations.

Molecular dynamics simulations of membrane proteins and their interactions: from nanoscale to mesoscale

Molecular dynamics simulations provide a computational tool to probe membrane proteins and systems at length scales ranging from nanometers to close to a micrometer, and on microsecond timescales. All atom and coarse-grained simulations may be used to explore in detail the interactions of membrane proteins and specific lipids, yielding predictions of lipid binding sites in good agreement with available structural data. Building on the success of protein-lipid interaction simulations, larger scale simulations reveal crowding and clustering of proteins, resulting in slow and anomalous diffusional dynamics, within realistic models of cell membranes. Current methods allow near atomic resolution simulations of small membrane organelles, and of enveloped viruses to be performed, revealing key aspects of their structure and functionally important dynamics.

Strong influence of periodic boundary conditions on lateral diffusion in lipid bilayer membranes

The Saffman-Delbrück hydrodynamic model for lipid-bilayer membranes is modified to account for the periodic boundary conditions commonly imposed in molecular simulations. Predicted lateral diffusion coefficients for membrane-embedded solid bodies are sensitive to box shape and converge slowly to the limit of infinite box size, raising serious doubts for the prospects of using detailed simulations to accurately predict membrane-protein diffusivities and related transport properties. Estimates for the relative error associated with periodic boundary artifacts are 50% and higher for fully atomistic models in currently feasible simulation boxes. MARTINI simulations of LacY membrane protein diffusion and LacY dimer diffusion in DPPC membranes and lipid diffusion in pure DPPC bilayers support the underlying hydrodynamic model.

Membrane Compartmentalization Reducing the Mobility of Lipids and Proteins within a Model Plasma Membrane

The cytoskeleton underlying cell membranes may influence the dynamic organization of proteins and lipids within the bilayer by immobilizing certain transmembrane (TM) proteins and forming corrals within the membrane. Here, we present coarse-grained resolution simulations of a biologically realistic membrane model of asymmetrically organized lipids and TM proteins. We determine the effects of a model of cytoskeletal immobilization of selected membrane proteins using long time scale coarse-grained molecular dynamics simulations. By introducing compartments with varying degrees of restraints within the membrane models, we are able to reveal how compartmentalization caused by cytoskeletal immobilization leads to reduced and anomalous diffusional mobility of both proteins and lipids. This in turn results in a reduced rate of protein dimerization within the membrane and of hopping of membrane proteins between compartments. These simulations provide a molecular realization of hierarchical models often invoked to explain single-molecule imaging studies of membrane proteins.

Molecular Simulations of Gram-Negative Bacterial Membranes: A Vignette of Some Recent Successes

In the following review we use recent examples from the literature to discuss progress in the area of atomistic and coarse-grained molecular dynamics simulations of selected bacterial membranes and proteins, with a particular focus on Gram-negative bacteria. As structural biology continues to provide increasingly high-resolution data on the proteins that reside within these membranes, simulations have an important role to play in linking these data with the dynamical behavior and function of these proteins. In particular, in the last few years there has been significant progress in addressing the issue of biochemical complexity of bacterial membranes such that the heterogeneity of the lipid and protein components of these membranes are now being incorporated into molecular-level models. Thus, in future we can look forward to complementary data from structural biology and molecular simulations combining to provide key details of structure-dynamics-function relationships in bacterial membranes.

Efficient preparation and analysis of membrane and membrane protein systems

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.

Alchembed: A Computational Method for Incorporating Multiple Proteins into Complex Lipid Geometries

A necessary step prior to starting any membrane protein computer simulation is the creation of a well-packed configuration of protein(s) and lipids. Here, we demonstrate a method, alchembed, that can simultaneously and rapidly embed multiple proteins into arrangements of lipids described using either atomistic or coarse-grained force fields. During a short simulation, the interactions between the protein(s) and lipids are gradually switched on using a soft-core van der Waals potential. We validate the method on a range of membrane proteins and determine the optimal soft-core parameters required to insert membrane proteins. Since all of the major biomolecular codes include soft-core van der Waals potentials, no additional code is required to apply this method. A tutorial is included in the Supporting Information.

NRas slows the rate at which a model lipid bilayer phase separates

The Ras family of small membrane-associated GTP-ases are important components in many different cell signalling cascades. They are thought to cluster on the cell membrane through association with cholesterol-rich nanodomains. This process remains poorly understood. Here we test the effect of adding multiple copies of NRas, one of the canonical Ras proteins, to a three-component lipid bilayer that rapidly undergoes spinodal decomposition (i.e. unmixing), thereby creating ordered and disordered phases. Coarse-grained molecular dynamics simulations of a large bilayer containing 6000 lipids, with and without protein, are compared. NRas preferentially localises to the interface between the domains and slows the rate at which the domains grow. We infer that this doubly-lipidated cell signalling protein is reducing the line tension between the ordered and disordered regions. This analysis is facilitated by our use of techniques borrowed from image-processing. The conclusions above are contingent upon several assumptions, including the use of a model lipid with doubly unsaturated tails and the limited structural data available for the C-terminus of NRas, which is where the lipid anchors are found.