Capturing Phase Behavior of Ternary Lipid Mixtures with a Refined Martini Coarse-Grained Force Field

Lateral Organization and Dynamics of the Realistic Plasma Membrane

Large-scale simulations of realistic crowded cell membranes can bridge the gap between the simulations and experiments. However, the compositional complexity and structural asymmetry of cell membranes continue to pose significant challenges in computational biology. Recent advances in understanding native membranes, including their composition and protein structures, enable us to construct a highly realistic model of the mammalian plasma membrane. Using this model, we explore the organization and dynamics of biological cell membranes at the molecular level. We found that the interaction preferences of protein-lipid mediate the formation of dynamic clusters of nonrandomly distributed proteins, accompanied by heterogeneous structural properties and anomalous diffusion. These evolving dynamic clusters intertwine to form a highly complex and continuously changing protein network. Our study provides significant insights into the intricate lateral dynamic organization of cell membranes.

Kinetics and Mechanism of Phase Separation in Ternary Lipid Mixtures Containing APP C99: Atomistic vs Coarse-Grained MD Simulations

The phase separation of lipid bilayers, composed of mixtures of saturated and unsaturated lipids and cholesterol, is a topic of fundamental importance in membrane biophysics and cell biology. The formation of lipid domains, including liquid-disordered domains enriched in unsaturated lipids and liquid-ordered domains enriched in saturated lipids and cholesterol, is believed to be essential to the function of many membrane proteins. Experiment, theory, and simulation have been used to develop a general understanding of the thermodynamic driving forces underlying phase separation in ternary and quaternary lipid mixtures. However, the kinetics of early events in lipid phase separation in the presence of transmembrane proteins remain relatively understudied. Using large-scale all-atom and coarse-grained simulations, we explore the kinetics and phase separation of ternary lipid mixtures of saturated lipid, unsaturated lipid, and cholesterol in the presence of transmembrane proteins. Order parameters employed in the Cahn-Hilliard theory provide insight into the kinetics and mechanism of lipid phase separation. We observe three distinct time regimes in the phase separation process: a shorter exponential time phase, followed by a power-law phase, and then a longer plateau phase. Comparison of lipid, protein, and lipid-protein dynamics between all-atom and coarse-grained models identifies both quantitative and qualitative differences and similarities in the phase separation kinetics. Moreover, timescaling of the dynamics of the AA and CG simulations yields a similar kinetic mechanism of phase separation. The findings of this study elucidate fundamental aspects of membrane biophysics and contribute to ongoing efforts to define the role of lipid rafts in the structure and function of the cellular membrane.

ART-SM: Boosting Fragment-Based Backmapping by Machine Learning

In sequential multiscale molecular dynamics simulations, which advantageously combine the increased sampling and dynamics at coarse-grained resolution with the higher accuracy of atomistic simulations, the resolution is altered over time. While coarse-graining is straightforward once the mapping between atomistic and coarse-grained resolution is defined, reintroducing the atomistic details is still a nontrivial process called backmapping. Here, we present ART-SM, a fragment-based backmapping framework that learns from atomistic simulation data to seamlessly switch from coarse-grained to atomistic resolution. ART-SM requires minimal user input and goes beyond state-of-the-art fragment-based approaches by selecting from multiple conformations per fragment via machine learning to simultaneously reflect the coarse-grained structure and the Boltzmann distribution. Additionally, we introduce a novel refinement step to connect individual fragments by optimizing specific bonds, angles, and dihedral angles in the backmapping process. We demonstrate that our algorithm accurately restores the atomistic bond length, angle, and dihedral angle distributions for various small and linear molecules from Martini coarse-grained beads and that the resulting high-resolution structures are representative of the input coarse-grained conformations. Moreover, the reconstruction of the TIP3P water model is fast and robust, and we demonstrate that ART-SM can be applied to larger linear molecules as well. To illustrate the efficiency of the local and autoregressive approach of ART-SM, we simulated a large realistic system containing the surfactants TAPB and SDS in solution using the Martini3 force field. The self-assembled micelles of various shapes were backmapped with ART-SM after training on only short atomistic simulations of a single water-solvated SDS or TAPB molecule. Together, these results indicate the potential for the method to be extended to more complex molecules such as lipids, proteins, macromolecules, and materials in the future.

Computational Methods for Modeling Lipid-Mediated Active Pharmaceutical Ingredient Delivery

Lipid-mediated delivery of active pharmaceutical ingredients (API) opened new possibilities in advanced therapies. By encapsulating an API into a lipid nanocarrier (LNC), one can safely deliver APIs not soluble in water, those with otherwise strong adverse effects, or very fragile ones such as nucleic acids. However, for the rational design of LNCs, a detailed understanding of the composition-structure-function relationships is missing. This review presents currently available computational methods for LNC investigation, screening, and design. The state-of-the-art physics-based approaches are described, with the focus on molecular dynamics simulations in all-atom and coarse-grained resolution. Their strengths and weaknesses are discussed, highlighting the aspects necessary for obtaining reliable results in the simulations. Furthermore, a machine learning, i.e., data-based learning, approach to the design of lipid-mediated API delivery is introduced. The data produced by the experimental and theoretical approaches provide valuable insights. Processing these data can help optimize the design of LNCs for better performance. In the final section of this Review, state-of-the-art of computer simulations of LNCs are reviewed, specifically addressing the compatibility of experimental and computational insights.

A macroscopically homogeneous lipid phase exhibits leaflet-specific lipid diffusion in a glass-supported lipid bilayer

Lipid bilayer is a building block of cellular membranes. Understanding the physicochemical properties of a lipid bilayer and their composition dependence is thus inevitable to infer the biological functions of lipids in cellular membranes. Here, we performed leaflet-specific lipid diffusion analysis to study the structural and dynamical properties of lipids on glass-supported lipid bilayers composed of dioleoyl phosphatidylcholine, dipalmitoyl phosphatidylcholine and cholesterol, especially focusing on the regions where a macroscopically homogeneous phase was observed in the ternary phase diagram. The data showed that the interleaflet coupling and the effect of the solid support were highly dependent on the lipid/cholesterol compositions. We also found a distinctive feature of leaflet-specific lipid diffusion in the region near the critical point. This observation was discussed in terms of the nanoscale heterogeneity.

Regulate PD-L1's membrane orientation thermodynamics with hydrophobic nanoparticles

Tumor cells can escape from immune killing by binding their programmed death ligand-1 (PD-L1) to the programmed cell death protein 1 (PD-1) of T cells. These immune checkpoint proteins (PD-L1/PD-1) have become very important drug targets, since blocking PD-L1 or PD-1 can recover the killing capability of T cells against tumor cells. Instead of targeting the binding interface between PD-L1 and PD-1, we explored the possibility of regulating the membrane orientation thermodynamics of PD-L1 with ligand-modified ultra-small hydrophobic nanoparticles (NPs) using μs-scale coarse-grained molecular dynamics (MD) simulations in this work. Our MD results indicate that embedded hydrophobic NPs can significantly change the membrane orientation thermodynamics of the extracellular domain of PD-L1, enhancing the probability in the "stand up" state for better binding to PD-1. Meanwhile, embedded hydrophobic NPs promote the tilt of the transmembrane domain of PD-L1. Besides, effects on both extracellular and transmembrane domains are determined by the ligand length and NP concentration. Our study may provide an alternative strategy to achieve PD-L1-related immunotherapy with nanomedicine.

Mixing small proteins with lipids and cholesterol

Many ternary mixtures composed of saturated and unsaturated lipids with cholesterol (Chol) exhibit a region of coexistence between liquid-disordered (Ld) and liquid-ordered (Lo) domains, bearing some similarities to lipid rafts in biological membranes. However, biological rafts also contain many proteins that interact with the lipids and modify the distribution of lipids. Here, we extend a previously published lattice model of ternary DPPC/DOPC/Chol mixtures by introducing a small amount of small proteins (peptides). We use Monte Carlo simulations to explore the mixing phase behavior of the components as a function of the interaction parameter representing the affinity between the proteins and the saturated DPPC chains and for different mixture compositions. At moderate fractions of DPPC, the system is in a two-phase Ld + Lo coexistence, and the proteins exhibit a simple partition behavior between the phases that depends on the protein-lipid affinity parameter. At low DPPC compositions, the mixture is in Ld phase with local nanoscopic ordered domains. The addition of proteins with sufficiently strong attraction to the saturated lipids can induce the separation of a distinct Lo large domain with tightly packed gel-like clusters of proteins and saturated lipids. Consistent with the theory of phase transitions, we observe that the domain sizes grow when the mixture composition is in the vicinity of the critical point. Our simulations show that the addition of a small amount of proteins to such mixtures can cause their size to grow even further and lead to the formation of metastable dynamic Lo domains with sizes comparable to biological rafts.

Investigating the Influence of Photoswitchable Lipids on the Structure and Dynamics of Lipid Membranes: Fundamentals and Potential Applications

In this work, we delve into the impact of photoisomerization of photoswitchable lipids (PSLs) on the membrane structure and dynamics at a molecular level. Through all-atom molecular dynamics simulations, we explore how UV irradiation-induced trans-to-cis isomerization of these lipids, particularly the azobenzene-derivatized phosphatidylcholine (AzoPC) lipid, influences the structure and dynamics of a simplified lipid membrane, mimicking those of E. coli bacteria across different temperatures. Our findings align with previous experimental observations regarding membrane properties and offer insights into localized effects and microscopic heterogeneity. Additionally, we estimate the relaxation time scale of the lipid membrane following AzoPC photoisomerization. Moreover, we demonstrate the feasibility of photoactivated drug release, exemplified by the controlled liberation of doxorubicin, an anticancer agent, through the membrane, suggesting the potential of PSLs in engineering photoactivated liposomes, coined as photoazosomes, for precise targeted drug delivery applications.

A Review on Investigating the Interactions between Nanoparticles and the Pulmonary Surfactant Monolayer with Coarse-Grained Molecular Dynamics Method

Pulmonary drug delivery has garnered significant attention due to its targeted local lung action, minimal toxic side effects, and high drug utilization. However, the physicochemical properties of inhaled nanoparticles (NPs) used as drug carriers can influence their interactions with the pulmonary surfactant (PS) monolayer, potentially altering the fate of the NPs and impairing the biophysical function of the PS monolayer. Thus, the objective of this review is to summarize how the physicochemical properties of NPs affect their interactions with the PS monolayer. Initially, the definition and properties of NPs, as well as the composition and characteristics of the PS monolayer, are introduced. Subsequently, the coarse-grained molecular dynamics (CGMD) simulation method for studying the interactions between NPs and the PS monolayer is presented. Finally, the implications of the hydrophobicity, size, shape, surface charge, surface modification, and aggregation of NPs on their interactions with the PS monolayer and on the composition of biomolecular corona are discussed. In conclusion, gaining a deeper understanding of the effects of the physicochemical properties of NPs on their interactions with the PS monolayer will contribute to the development of safer and more effective nanomedicines for pulmonary drug delivery.

Hydrophobic mismatch drives self-organization of designer proteins into synthetic membranes

The organization of membrane proteins between and within membrane-bound compartments is critical to cellular function. Yet we lack approaches to regulate this organization in a range of membrane-based materials, such as engineered cells, exosomes, and liposomes. Uncovering and leveraging biophysical drivers of membrane protein organization to design membrane systems could greatly enhance the functionality of these materials. Towards this goal, we use de novo protein design, molecular dynamic simulations, and cell-free systems to explore how membrane-protein hydrophobic mismatch could be used to tune protein cotranslational integration and organization in synthetic lipid membranes. We find that membranes must deform to accommodate membrane-protein hydrophobic mismatch, which reduces the expression and co-translational insertion of membrane proteins into synthetic membranes. We use this principle to sort proteins both between and within membranes, thereby achieving one-pot assembly of vesicles with distinct functions and controlled split-protein assembly, respectively. Our results shed light on protein organization in biological membranes and provide a framework to design self-organizing membrane-based materials with applications such as artificial cells, biosensors, and therapeutic nanoparticles.

Building complex membranes with Martini 3

The Martini model is a popular force field for coarse-grained simulations. Membranes have always been at the center of its development, with the latest version, Martini 3, showing great promise in capturing more and more realistic behavior. In this chapter we provide a step-by-step tutorial on how to construct starting configurations, run initial simulations and perform dedicated analysis for membrane-based systems of increasing complexity, including leaflet asymmetry, curvature gradients and embedding of membrane proteins.

Characterization of domain formation in complex membranes

A widely known property of lipid membranes is their tendency to undergo a separation into disordered (Ld) and ordered (Lo) domains. This impacts the local structure of the membrane relevant for the physical (e.g., enhanced electroporation) and biological (e.g., protein sorting) significance of these regions. The increase in computing power, advancements in simulation software, and more detailed information about the composition of biological membranes shifts the study of these domains into the focus of classical molecular dynamics simulations. In this chapter, we present a versatile yet robust analysis pipeline that can be easily implemented and adapted for a wide range of lipid compositions. It employs Gaussian-based Hidden Markov Models to predict the hidden order states of individual lipids by describing their structure through the area per lipid and the average SCC order parameters per acyl chain. Regions of the membrane with a high correlation between ordered lipids are identified by employing the Getis-Ord local spatial autocorrelation statistic on a Voronoi tessellation of the lipids. As an example, the approach is applied to two distinct systems at a coarse-grained resolution, demonstrating either a strong tendency towards phase separation (1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), 1,2-dilinoleoyl-sn-glycero-3-phosphocholine (DIPC), cholesterol) or a weak tendency toward phase separation (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), 1-palmitoyl-2-docosahexaenoyl-sn-glycero-3-phosphocholine (PUPC), cholesterol). Explanations of the steps are complemented by coding examples written in Python, providing both a comprehensive understanding and practical guidance for a seamless integration of the workflow into individual projects.

Particle Deformability Enables Control of Interactions between Membrane-Anchored Nanoparticles

Nanoparticles adsorbed on a membrane can induce deformations of the membrane that give rise to effective interactions between the particles. Previous studies have focused primarily on rigid nanoparticles with fixed shapes. However, DNA origami technology has enabled the creation of deformable nanostructures with controllable shapes and mechanical properties, presenting new opportunities to modulate interactions between particles adsorbed on deformable surfaces. Here we use coarse-grained molecular dynamics simulations to investigate deformable, hinge-like nanostructures anchored to lipid membranes via cholesterol anchors. We characterize deformations of the particles and membrane as a function of the hinge stiffness. Flexible particles adopt open configurations to conform to a flat membrane, whereas stiffer particles induce deformations of the membrane. We further show that particles spontaneously aggregate and that cooperative effects lead to changes in their shape when they are close together. Using umbrella sampling methods, we quantify the effective interaction between two particles and show that stiffer hinge-like particles experience stronger and longer-ranged attraction. Our results demonstrate that interactions between deformable, membrane-anchored nanoparticles can be controlled by modifying mechanical properties of the particles, suggesting new ways to modulate the self-assembly of particles on deformable surfaces.

Anomalous lateral diffusion of lipids during the fluid/gel phase transition of a lipid membrane

A lipid membrane undergoes a phase transition from fluid to gel phase upon changing external thermodynamic conditions, such as decreasing temperature and increasing pressure. Extremophilic organisms face the challenge of preventing this deleterious phase transition. The main focus of their adaptive strategy is to facilitate effective temperature sensing through sensor proteins, relying on the drastic changes in packing density and membrane fluidity during the phase transition. Although the changes in packing density parameters due to the fluid/gel phase transition are studied in detail, the impact on membrane fluidity is less explored in the literature. Understanding the lateral diffusive dynamics of lipids in response to temperature, particularly during the fluid/gel phase transition, is albeit crucial. Here we have simulated the phase transition of a single component lipid membrane composed of dipalmitoylphosphatidylcholine (DPPC) lipids using a coarse-grained (CG) model and studied the changes of the structural and dynamical properties. It is observed that near the phase transition point, both fluid and gel phase domains coexist together. The dynamics remains highly non-Gaussian for a long time even when the mean square displacement reaches the Fickian regime at a much earlier time. This Fickian yet non-Gaussian diffusion (FnGD) is a characteristic of a highly heterogeneous system, previously observed for the lateral diffusion of lipids in raft mimetic membranes having liquid-ordered and liquid-disordered phases co-existing together. We have analyzed the molecular trajectories and calculated the jump-diffusion of the lipids, stemming from sudden jump translations, using a translational jump-diffusion (TJD) approach. An overwhelming contribution of the jump-diffusion of the lipids is observed suggesting anomalous diffusion of lipids during fluid/gel phase transition of the membrane. These results are important in unravelling the intricate nature of lipid diffusion during the phase transition of the membrane and open up a new possibility of investigating the most significant change of membrane properties during phase transition, which can be effectively sensed by proteins.

Martini 3 Coarse-Grained Force Field for Cholesterol

Cholesterol plays a crucial role in biomembranes by regulating various properties, such as fluidity, rigidity, permeability, and organization of lipid bilayers. The latest version of the Martini model, Martini 3, offers significant improvements in interaction balance, molecular packing, and inclusion of new bead types and sizes. However, the release of the new model resulted in the need to reparameterize many core molecules, including cholesterol. Here, we describe the development and validation of a Martini 3 cholesterol model, addressing issues related to its bonded setup, shape, volume, and hydrophobicity. The proposed model mitigates some limitations of its Martini 2 predecessor while maintaining or improving the overall behavior.

Computational investigation on lipid bilayer disruption induced by amphiphilic Janus nanoparticles: combined effect of Janus balance and charged lipid concentration

Janus nanoparticles (NPs) with charged/hydrophobic compartments have garnered attention for their potential antimicrobial activity. These NPs have been shown to disrupt lipid bilayers in experimental studies, yet the underlying mechanisms of this disruption at the particle-membrane interface remain unclear. To address this knowledge gap, the present study conducts a computational investigation to systematically examine the disruption of lipid bilayers induced by amphiphilic Janus NPs. The focus of this study is on the combined effects of the hydrophobicity of the Janus NP, referred to as the Janus balance, defined as the ratio of hydrophilic to hydrophobic surface coverage, and the concentration of charged phospholipids on the interactions between Janus NPs and lipid bilayers. Computational simulations were conducted using a coarse-grained molecular dynamics (MD) approach. The results of these MD simulations reveal that while the area change of the bilayer increases monotonically with the Janus balance, the effect of charged lipid concentration in the membrane is not easy to be predicted. Specifically, it was found that the concentration of negatively charged lipids is directly proportional to the intensity of membrane disruption. Conversely, positively charged lipids have a negligible effect on membrane defects. This study provides molecular insights into the significant role of Janus balance in the disruption of lipid bilayers by Janus NPs and supports the selectivity of Janus NPs for negatively charged lipid membranes. Furthermore, the anisotropic properties of Janus NPs were found to play a crucial role in their ability to disrupt the membrane via the combination of hydrophobic and electrostatic interactions. This finding is validated by testing the current Janus NP design on a bacterial membrane-mimicking model. This computational study may serve as a foundation for further studies aimed at optimizing the properties of Janus NPs for specific antimicrobial applications.

Effects of lipid saturation on bicelle to vesicle transition of a binary phospholipid mixture: a molecular dynamics simulation study

Controlling the transition from lipid bicelles to vesicles is essential for producing engineered vesicles. We perform coarse-grained molecular dynamics (CGMD) simulations of unsaturated/saturated lipid mixtures to clarify the effects of lipid unsaturation on vesiculation at the molecular scale. The results demonstrate that vesiculation depends on the concentration of unsaturated lipids and the degree of unsaturation. The probability of vesiculation increases linearly with the apparent unsaturated lipid concentration at a low degree of unsaturation. Higher degrees of unsaturation lead to phase segregation within the binary bicelles, reducing the probability of vesiculation. A comparison between CGMD simulations and the conventional theory of vesiculation shows that the theoretical predictions of binary lipid systems must explicitly include phase segregation effects. Furthermore, simulations with biased lipid distributions reveal that vesiculation is facilitated by the preconcentration of unsaturated lipids in the core region of the bicelle but is then temporally limited as the unsaturated lipids move to the bicelle edges. These findings advance theoretical and experimental studies on binary lipid systems and promote the development of tailor-made vesicles.

Automatic Optimization of Lipid Models in the Martini Force Field Using SwarmCG

After two decades of continued development of the Martini coarse-grained force field (CG FF), further refinment of the already rather accurate Martini lipid models has become a demanding task that could benefit from integrative data-driven methods. Automatic approaches are increasingly used in the development of accurate molecular models, but they typically make use of specifically designed interaction potentials that transfer poorly to molecular systems or conditions different than those used for model calibration. As a proof of concept, here, we employ SwarmCG, an automatic multiobjective optimization approach facilitating the development of lipid force fields, to refine specifically the bonded interaction parameters in building blocks of lipid models within the framework of the general Martini CG FF. As targets of the optimization procedure, we employ both experimental observables (top-down references: area per lipid and bilayer thickness) and all-atom molecular dynamics simulations (bottom-up reference), which respectively inform on the supra-molecular structure of the lipid bilayer systems and on their submolecular dynamics. In our training sets, we simulate at different temperatures in the liquid and gel phases up to 11 homogeneous lamellar bilayers composed of phosphatidylcholine lipids spanning various tail lengths and degrees of (un)saturation. We explore different CG representations of the molecules and evaluate improvements a posteriori using additional simulation temperatures and a portion of the phase diagram of a DOPC/DPPC mixture. Successfully optimizing up to ∼80 model parameters within still limited computational budgets, we show that this protocol allows the obtainment of improved transferable Martini lipid models. In particular, the results of this study demonstrate how a fine-tuning of the representation and parameters of the models may improve their accuracy and how automatic approaches, such as SwarmCG, may be very useful to this end.

Efficient calculation of the free energy for protein partitioning using restraining potentials

An approach for the efficient simulation of phase-separated lipid bilayers, for use in the calculation of equilibrium free energies of partitioning between lipid domains, is proposed. The methodology exploits restraint potentials and rectangular aspect ratios that enforce lipid phase separation, allowing for the simulation of smaller systems that approximately reproduce bulk behavior. The utility of this approach is demonstrated through the calculation of potentials of mean force for the translation of a transmembrane protein between lipid domains. The impact of the imposed restraints on lipid tail ordering and lipid packing are explored, providing insight into how restraints can best be employed to compute accurate free-energy surfaces. This approach should be useful in the accurate calculation of equilibrium partition coefficients for transmembrane protein partitioning in heterogeneous membranes, providing insight into the thermodynamic driving forces that control this fundamental biophysical phenomenon.

Asymmetric Lipid Vesicles: Techniques, Applications, and Future Perspectives as an Innovative Drug Delivery System

Novel lipid-based nanosystems have been of interest in improving conventional drug release methods. Liposomes are the most studied nanostructures, consisting of lipid bilayers ideal for drug delivery, thanks to their resemblance to the cell plasma membrane. Asymmetric liposomes are vesicles with different lipids in their inner and outer layers; because of this, they can be configured to be compatible with the therapeutic drug while achieving biocompatibility and stability. Throughout this review, topics such as the applications, advantages, and synthesis techniques of asymmetric liposomes will be discussed. Further, an in silico analysis by computational tools will be examined as a helpful tool for designing and understanding asymmetric liposome mechanisms in pharmaceutical applications. The dual-engineered design of asymmetric liposomes makes them an ideal alternative for transdermal drug delivery because of the improved protection of pharmaceuticals without lowering adsorption rates and system biocompatibility.

CHARMM-GUI Membrane Builder: Past, Current, and Future Developments and Applications

Molecular dynamics simulations of membranes and membrane proteins serve as computational microscopes, revealing coordinated events at the membrane interface. As G protein-coupled receptors, ion channels, transporters, and membrane-bound enzymes are important drug targets, understanding their drug binding and action mechanisms in a realistic membrane becomes critical. Advances in materials science and physical chemistry further demand an atomistic understanding of lipid domains and interactions between materials and membranes. Despite a wide range of membrane simulation studies, generating a complex membrane assembly remains challenging. Here, we review the capability of CHARMM-GUI Membrane Builder in the context of emerging research demands, as well as the application examples from the CHARMM-GUI user community, including membrane biophysics, membrane protein drug-binding and dynamics, protein-lipid interactions, and nano-bio interface. We also provide our perspective on future Membrane Builder development.

Fluorescent Probes cis- and trans-Parinaric Acids in Fluid and Gel Lipid Bilayers: A Molecular Dynamics Study

Fluorescence probes are indispensable tools in biochemical and biophysical membrane studies. Most of them possess extrinsic fluorophores, which often constitute a source of uncertainty and potential perturbation to the host system. In this regard, the few available intrinsically fluorescent membrane probes acquire increased importance. Among them, cis- and trans-parinaric acids (c-PnA and t-PnA, respectively) stand out as probes of membrane order and dynamics. These two compounds are long-chained fatty acids, differing solely in the configurations of two double bonds of their conjugated tetraene fluorophore. In this work, we employed all-atom and coarse-grained molecular dynamics simulations to study the behavior of c-PnA and t-PnA in lipid bilayers of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), representative of the liquid disordered and solid ordered lipid phases, respectively. All-atom simulations indicate that the two probes show similar location and orientation in the simulated systems, with the carboxylate facing the water/lipid interface and the tail spanning the membrane leaflet. The two probes establish interactions with the solvent and lipids to a similar degree in POPC. However, the almost linear t-PnA molecules have tighter lipid packing around them, especially in DPPC, where they also interact more with positively charged lipid choline groups. Probably for these reasons, while both probes show similar partition (assessed from computed free energy profiles across bilayers) to POPC, t-PnA clearly partitions more extensively than c-PnA to the gel phase. t-PnA also displays more hindered fluorophore rotation, especially in DPPC. Our results agree very well with experimental fluorescence data from the literature and allow deeper understanding of the behavior of these two reporters of membrane organization.

Potential binding modes of the gut bacterial metabolite, 5-hydroxyindole, to the intestinal L-type calcium channels and its impact on the microbiota in rats

Intestinal microbiota and microbiota-derived metabolites play a key role in regulating the host physiology. Recently, we have identified a gut-bacterial metabolite, namely 5-hydroxyindole, as a potent stimulant of intestinal motility via its modulation of L-type voltage-gated calcium channels located on the intestinal smooth muscle cells. Dysregulation of L-type voltage-gated calcium channels is associated with various gastrointestinal motility disorders, including constipation, making L-type voltage-gated calcium channels an important target for drug development. Nonetheless, the majority of currently available drugs are associated with alteration of the gut microbiota. Using 16S rRNA sequencing this study shows that, when administered orally, 5-hydroxyindole has only marginal effects on the rat cecal microbiota. Molecular dynamics simulations propose potential-binding pockets of 5-hydroxyindole in the α1 subunit of the L-type voltage-gated calcium channels and when its stimulatory effect on the rat colonic contractility was compared to 16 different analogues, ex-vivo, 5-hydroxyindole stood as the most potent enhancer of the intestinal contractility. Overall, the present findings imply a potential role of microbiota-derived metabolites as candidate therapeutics for targeted treatment of slow intestinal motility-related disorders including constipation.

Phase separation in polymer-based biomimetic structures containing planar membranes

Phase separation in biological membranes is crucial for proper cellular functions, such as signaling and trafficking, as it mediates the interactions of condensates on membrane-bound organelles and transmembrane transport to targeted destination compartments. The separation of a lipid bilayer into phases and the formation of lipid rafts involve the restructuring of molecular localization, their immobilization, and local accumulation. By understanding the processes underlying the formation of lipid rafts in a cellular membrane, it is possible to reconstitute this phenomenon in synthetic biomimetic membranes, such as hybrids of lipids and polymers or membranes composed solely of polymers, which offer an increased physicochemical stability and unlimited possibilities of chemical modification and functionalization. In this article, we relate the main lipid bilayer phase transition phenomenon with respect to hybrid biomimetic membranes, composed of lipids mixed with polymers, and fully synthetic membranes. Following, we review the occurrence of phase separation in biomimetic hybrid membranes based on lipids and/or direct lipid analogs, amphiphilic block copolymers. We further exemplify the phase separation and the resulting properties and applications in planar membranes, free-standing and solid-supported. We briefly list methods leading to the formation of such biomimetic membranes and reflect on their improved overall stability and influence on the separation into different phases within the membranes. Due to the importance of phase separation and compartmentalization in cellular membranes, we are convinced that this compiled overview of this phenomenon will be helpful for any researcher in the biomimicry area.

Fluid-gel coexistence in lipid membranes under differential stress

A widely conserved property of many biological lipid bilayers is their asymmetry. In addition to having distinct compositions on its two sides, a membrane can also exhibit different tensions in its two leaflets, a state known as differential stress. Here, we examine how this stress can influence the phase behavior of the constituent lipid monolayers of a single-component membrane. For temperatures sufficiently close to, but still above, the main transition, molecular dynamics simulations show the emergence of finite gel domains within the compressed leaflet. We describe the thermodynamics of this phenomenon by adding two empirical single-leaflet free energies for the fluid-gel transition, each evaluated at its respective asymmetry-dependent lipid density. Finite size effects arising in simulation are included in the theory through a geometry-dependent interfacial term. Our model reproduces the phase coexistence observed in simulation. It could therefore be used to connect the "hidden variable" of differential stress to experimentally observable properties of the main phase transition. These ideas could be generalized to any first-order bilayer phase transition in the presence of asymmetry, including liquid-ordered/liquid-disordered phase separation.

Asynchronous Reciprocal Coupling of Martini 2.2 Coarse-Grained and CHARMM36 All-Atom Simulations in an Automated Multiscale Framework

The appeal of multiscale modeling approaches is predicated on the promise of combinatorial synergy. However, this promise can only be realized when distinct scales are combined with reciprocal consistency. Here, we consider multiscale molecular dynamics (MD) simulations that combine the accuracy and macromolecular flexibility accessible to fixed-charge all-atom (AA) representations with the sampling speed accessible to reductive, coarse-grained (CG) representations. AA-to-CG conversions are relatively straightforward because deterministic routines with unique outcomes are achievable. Conversely, CG-to-AA conversions have many solutions due to a surge in the number of degrees of freedom. While automated tools for biomolecular CG-to-AA transformation exist, we find that one popular option, called Backward, is prone to stochastic failure and the AA models that it does generate frequently have compromised protein structure and incorrect stereochemistry. Although these shortcomings can likely be circumvented by human intervention in isolated instances, automated multiscale coupling requires reliable and robust scale conversion. Here, we detail an extension to Multiscale Machine-learned Modeling Infrastructure (MuMMI), including an improved CG-to-AA conversion tool called sinceCG. This tool is reliable (∼98% weakly correlated repeat success rate), automatable (no unrecoverable hangs), and yields AA models that generally preserve protein secondary structure and maintain correct stereochemistry. We describe how the MuMMI framework identifies CG system configurations of interest, converts them to AA representations, and simulates them at the AA scale while on-the-fly analyses provide feedback to update CG parameters. Application to systems containing the peripheral membrane protein RAS and proximal components of RAF kinase on complex eight-component lipid bilayers with ∼1.5 million atoms is discussed in the context of MuMMI.

Can Urea and Trimethylamine-N-oxide Prevent the Pressure-Induced Phase Transition of Lipid Membrane?

Organisms dwelling in ocean trenches are exposed to the high hydrostatic pressure of ocean water. Increasing pressure can alter the membrane packing density and fluidity and trigger the fluid-to-gel phase transition. To combat environmental stress, the organisms synthesize small polar solutes, which are known as osmolytes. Urea and trimethylamine-N-oxide (TMAO) are two such solutes found in deep-sea creatures. While TMAO stabilizes protein, urea induces protein denaturation. These solutes strongly influence the packing density and membrane fluidity of the lipid bilayer at different conditions. But can these solutes affect the pressure-induced phase transition of the lipid membrane? In the present work, we have studied the effect of these two solutes on pressure-induced fluid-to-gel phase transition based on the all-atom molecular dynamics (MD) simulation approach. A high-pressure-stimulated fluid-to-gel phase transition of the membrane is seen at 800 bar, which is consistent with previous experiments. We have also observed that in the low-pressure region (1-400 bar), urea slightly increases the membrane fluidity where TMAO decreases the same. However, the phase transition pressure remains almost unchanged on the addition of urea while TMAO shifts the phase transition toward a lower pressure. We have found that the hydrogen (H)-bond interaction between lipid and urea plays an important role in preserving the fluidity of the membrane in the low-pressure zone. However, at a higher pressure, both water and urea are excluded from the membrane surface. TMAO is also excluded from the interfacial region of the membrane at all pressures. Exclusion from the membrane surface further triggers the phase transition of the lipid membrane from the fluid to gel phase at a high pressure.

Automatic multi-objective optimization of coarse-grained lipid force fields using SwarmCG

The development of coarse-grained (CG) molecular models typically requires a time-consuming iterative tuning of parameters in order to have the approximated CG models behave correctly and consistently with, e.g., available higher-resolution simulation data and/or experimental observables. Automatic data-driven approaches are increasingly used to develop accurate models for molecular dynamics simulations. However, the parameters obtained via such automatic methods often make use of specifically designed interaction potentials and are typically poorly transferable to molecular systems or conditions other than those used for training them. Using a multi-objective approach in combination with an automatic optimization engine (SwarmCG), here, we show that it is possible to optimize CG models that are also transferable, obtaining optimized CG force fields (FFs). As a proof of concept, here, we use lipids for which we can avail reference experimental data (area per lipid and bilayer thickness) and reliable atomistic simulations to guide the optimization. Once the resolution of the CG models (mapping) is set as an input, SwarmCG optimizes the parameters of the CG lipid models iteratively and simultaneously against higher-resolution simulations (bottom-up) and experimental data (top-down references). Including different types of lipid bilayers in the training set in a parallel optimization guarantees the transferability of the optimized lipid FF parameters. We demonstrate that SwarmCG can reach satisfactory agreement with experimental data for different resolution CG FFs. We also obtain stimulating insights into the precision-resolution balance of the FFs. The approach is general and can be effectively used to develop new FFs and to improve the existing ones.

Acyl-chain saturation regulates the order of phosphatidylinositol 4,5-bisphosphate nanodomains

Phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) plays a critical role in the regulation of various plasma membrane processes and signaling pathways in eukaryotes. A significant amount of cellular resources are spent on maintaining the dominant 1-stearoyl-2-arachidonyl PI(4,5)P2 acyl-chain composition, while less abundant and more saturated species become more prevalent in response to specific stimuli, stress or aging. Here, we report the impact of acyl-chain structure on the biophysical properties of cation-induced PI(4,5)P2 nanodomains. PI(4,5)P2 species with increasing levels of acyl-chain saturation cluster in progressively more ordered nanodomains, culminating in the formation of gel-like nanodomains for fully saturated species. The formation of these gel-like domains was largely abrogated in the presence of 1-stearoyl-2-arachidonyl PI(4,5)P2. This is, to the best of our knowledge, the first report of the impact of PI(4,5)P2 acyl-chain composition on cation-dependent nanodomain ordering, and provides important clues to the motives behind the enrichment of PI(4,5)P2 with polyunsaturated acyl-chains. We also show how Ca2+-induced PI(4,5)P2 nanodomains are able to generate local negative curvature, a phenomenon likely to play a role in membrane remodeling events.

Asymmetric Lipid Membranes under Shear Flows: A Dissipative Particle Dynamics Study

We investigate the phase behavior of the asymmetric lipid membranes under shear flows, using the dissipative particle dynamics simulation. Two cases, the weak and strong shear flows, are considered for the asymmetric lipid microstructures. Three typical asymmetric structures, the membranes, tubes, and vesicle, are included in the phase diagrams, where the effect of two different types of lipid chain length on the formation of asymmetric membranes is evaluated. The dynamic processes are demonstrated for the asymmetric membranes by calculating the average radius of gyration and shape factor. The result indicates that different shear flows will affect the shape of the second type of lipid molecules; the shape of the first type of lipid molecules is more stable than that of the second type of lipid molecules. The mechanical properties are investigated for the asymmetric membranes by analyzing the interface tension. The results reveal an absolute pressure at the junctions of different types of particles under the weak shear flow; the other positions are almost in a state of no pressure; there is almost no pressure inside the asymmetric lipid membrane structure under the strong shear flow. The findings will help us to understand the potential applications of asymmetric lipid microstructures in the biological and medical fields.

Nonconverged Constraints Cause Artificial Temperature Gradients in Lipid Bilayer Simulations

Molecular dynamics (MD) simulations have become an indispensable tool to investigate phase separation in model membrane systems. In particular, simulations based on coarse-grained (CG) models have found widespread use due to their increased computational efficiency, allowing for simulations of multicomponent lipid bilayers undergoing phase separation into liquid-ordered and liquid-disordered domains. Here, we show that a significant temperature difference between molecule types can artificially arise in CG MD membrane simulations with the standard Martini simulation parameters in GROMACS. In particular, the linear constraint solver (LINCS) algorithm does not converge with its default settings, resulting in serious temperature differences between molecules in a time step-dependent manner. We demonstrate that the underlying reason for this behavior is the presence of highly constrained moieties, such as cholesterol. Their presence can critically impact numerous structural and dynamic membrane properties obtained from such simulations. Furthermore, any preference of these molecules toward a certain membrane phase can lead to spatial temperature gradients, which can amplify the degree of phase separation or even induce it in compositions that would otherwise mix well. We systematically investigated the effect of the integration time step and LINCS settings on membrane properties. Our data show that for cholesterol-containing membranes, a time step of 20 fs should be combined with at least lincs_iter = 2 and lincs_order = 12, while using a time step of 30 fs requires at least lincs_iter = 3 and lincs_order = 12 to bring the temperature differences to a level where they do not perturb central membrane properties. Moreover, we show that in cases where stricter LINCS settings are computationally too demanding, coupling the lipids in multiple groups to the temperature bath offers a practical workaround to the problem, although the validity of this approach should be further verified. Finally, we show that similar temperature gradients can also emerge in atomistic simulations using the CHARMM force field in combination with settings that allow for a 5 fs integration step.

Structure of the human signal peptidase complex reveals the determinants for signal peptide cleavage

The signal peptidase complex (SPC) is an essential membrane complex in the endoplasmic reticulum (ER), where it removes signal peptides (SPs) from a large variety of secretory pre-proteins with exquisite specificity. Although the determinants of this process have been established empirically, the molecular details of SP recognition and removal remain elusive. Here, we show that the human SPC exists in two functional paralogs with distinct proteolytic subunits. We determined the atomic structures of both paralogs using electron cryo-microscopy and structural proteomics. The active site is formed by a catalytic triad and abuts the ER membrane, where a transmembrane window collectively formed by all subunits locally thins the bilayer. Molecular dynamics simulations indicate that this unique architecture generates specificity for SPs based on the length of their hydrophobic segments.

Lipid Oxidation: Role of Membrane Phase-Separated Domains

Lipid oxidation is associated with several inflammatory and neurodegenerative diseases, but many questions to unravel its effects on biomembranes are still open due to the complexity of the topic. For instance, recent studies indicated that phase-separated domains can have a significant effect on membrane function. It is reported that domain interfaces are "hot spots" for pore formation, but the underlying mechanisms and the effect of oxidation-induced phase separation on membranes remain elusive. Thus, to evaluate the permeability of the membrane coexisting of liquid-ordered (Lo) and liquid-disordered (Ld) domains, we performed atomistic molecular dynamics simulations. Specifically, we studied the membrane permeability of nonoxidized or oxidized homogeneous membranes (single-phase) and at the Lo/Ld domain interfaces of heterogeneous membranes, where the Ld domain is composed of either oxidized or nonoxidized lipids. Our simulation results reveal that the addition of only 1.5% of lipid aldehyde molecules at the Lo/Ld domain interfaces of heterogeneous membranes increases the membrane permeability, whereas their addition at homogeneous membranes does not have any effect. This study is of interest for a better understanding of cancer treatment methods based on oxidative stress (causing among others lipid oxidation), such as plasma medicine and photodynamic therapy.

Surface ligand rigidity modulates lipid raft affinity of ultra-small hydrophobic nanoparticles: insights from molecular dynamics simulations

Differential preferences between lipids and proteins drive the formation of dynamical nanoscale membrane domains (lipid rafts), which play key roles in the proper functioning of cells. On the other hand, due to the potent physicochemical properties of nanoparticles (NPs), they have been widely used in drug delivery, bio-imaging and regulating various essential biological processes of the cells. Hence, in this work, we aim to design ultra-small hydrophobic NPs with tunable raft affinity, which is supposed to partition into the hydrophobic region of lipid membranes and be able to regulate the dynamics of the lipid raft domains. A series of μs-scale coarse-grained molecular dynamics simulations and umbrella sampling free energy calculations were performed to investigate the role of surface ligand rigidity of ultra-small hydrophobicNPs in their raft affinity. Our results indicated that the preferred localization of NPs can be tuned by adjusting their surface ligand rigidity. Generally, rigid NPs tended to target the raft domain, while soft NPs preferred the interface of the raft and non-raft domains. The free energy analysis further indicated that the surface ligand rigidity of NPs can enhance their targeting to lipid raft domains. Besides, we found that these ultra-small NPs had no significant effects on the phase separation of the lipid membrane although they might cause some local interference to surrounding lipids. These results indicate that the targeting to the lipid raft domain can be achieved by the surface ligand rigidity of NPs, which provides helpful insights for further regulations of lipid raft-mediated biological processes.

Evaluating Coarse-Grained MARTINI Force-Fields for Capturing the Ripple Phase of Lipid Membranes

Phospholipids, which are an integral component of cell membranes, exhibit a rich variety of lamellar phases modulated by temperature and composition. Molecular dynamics (MD) simulations have greatly enhanced our understanding of phospholipid membranes by capturing experimentally observed phases and phase transitions at molecular resolution. However, the ripple (P_β') membrane phase, observed as an intermediate phase below the main gel-to-liquid crystalline transition with some lipids, has been challenging to capture with MD simulations, both at all-atom and coarse-grained (CG) resolutions. Here, with an aggregate ∼2.5 μs all-atom and ∼122 μs CGMD simulations, we systematically assess the ability of six CG MARTINI 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) lipid and water force-field (FF) variants, parametrized to capture the DPPC gel and fluid phases, for their ability to capture the P_β' phase, and compared observations with those from an all-atom FF. Upon cooling from the fluid phase to below the phase transition temperature with smaller (380-lipid) and larger (>2200-lipid) MARTINI and all-atom (CHARMM36 FF) DPPC lipid bilayers, we observed that smaller bilayers with both all-atom and MARTINI FFs sampled interdigitated P_β' and ripple-like states, respectively. However, while all-atom simulations of the larger DPPC membranes exhibited the formation of the P_β' phase, MARTINI membranes did not sample interdigitated ripple-like states at larger system sizes. We then demonstrated that the ripple-like states in smaller MARTINI membranes were kinetically trapped structures caused by finite size effects rather than being representative of true P_β' phases. We showed that a MARTINI FF variant that could capture the tilted L_β' gel phase, a prerequisite for stabilizing the P_β' phase, was unable to capture the rippled phase upon cooling. Our study reveals that the current MARTINI FFs (including MARTINI3) may require specific reparametrization of the interaction potentials to stabilize lipid interdigitation, a characteristic of the ripple phase.

Spontaneous lipid binding to the nicotinic acetylcholine receptor in a native membrane

The nicotinic acetylcholine receptor (nAChR) and other pentameric ligand-gated ion channels are native to neuronal membranes with an unusual lipid composition. While it is well-established that these receptors can be significantly modulated by lipids, the underlying mechanisms have been primarily studied in model membranes with few lipid species. Here, we use coarse-grained molecular dynamics simulation to probe specific binding of lipids in a complex quasi-neuronal membrane. We ran a total of 50 μs of simulations of a single nAChR in a membrane composed of 36 species of lipids. Competition between multiple lipid species produces a complex distribution. We find that overall, cholesterol selects for concave inter-subunit sites and polyunsaturated fatty acids select for convex M4 sites, while monounsaturated and saturated lipids are unenriched in the nAChR boundary. We propose the "density-threshold affinity" as a metric calculated from continuous density distributions, which reduces to a standard affinity in two-state binding. We find that the density-threshold affinity for M4 weakens with chain rigidity, which suggests that flexible chains may help relax packing defects caused by the conical protein shape. For any site, PE headgroups have the strongest affinity of all phospholipid headgroups, but anionic lipids still yield moderately high affinities for the M4 sites as expected. We observe cooperative effects between anionic headgroups and saturated chains at the M4 site in the inner leaflet. We also analyze affinities for individual anionic headgroups. When combined, these insights may reconcile several apparently contradictory experiments on the role of anionic phospholipids in modulating nAChR.

Finite-size transitions in complex membranes

The lipid-raft hypothesis postulates that cell membranes possess some degree of lateral organization. The hypothesis has attracted much attention while remaining controversial, with an underlying mechanism that remains elusive. One idea that supports rafts relies on the membrane lying near a critical point. Although supported by experimental evidence, holding a many-component membrane at criticality requires a delicate tuning of all components-a daunting task. Here, we propose a coherent framework to reconcile critical behavior and lipid regulation. Using a lattice model, we show that lipid regulation of a complex membrane, i.e., allowing composition to fluctuate based on relative chemical potentials, can lead to critical behavior. The results are robust against specific values of the chemical potentials. Instead of a conventional transition point, criticality is observed over a large temperature range. This surprising behavior arises from finite-size effects, causing nonequivalent time and space averages. The instantaneous lipid distribution effectively develops a translational symmetry, which we relate to long-wavelength Goldstone modes. The framework is robust and reproduces important experimental trends; membrane-demixing temperature closely follows cell-growth temperature. It also ensures criticality of fixed-composition extracts, such as giant plasma membrane vesicles. Our clear picture provides a strong argument in favor of the critical-membrane hypothesis, without the need for specific sensing mechanisms.

Unveiling the Dynamics of KRAS4b on Lipid Model Membranes

Small GTPase proteins are ubiquitous and responsible for regulating several processes related to cell growth and differentiation. Mutations that stabilize their active state can lead to uncontrolled cell proliferation and cancer. Although these proteins are well characterized at the cellular scale, the molecular mechanisms governing their functions are still poorly understood. In addition, there is limited information about the regulatory function of the cell membrane which supports their activity. Thus, we have studied the dynamics and conformations of the farnesylated KRAS4b in various membrane model systems, ranging from binary fluid mixtures to heterogeneous raft mimics. Our approach combines long time-scale coarse-grained (CG) simulations and Markov state models to dissect the membrane-supported dynamics of KRAS4b. Our simulations reveal that protein dynamics is mainly modulated by the presence of anionic lipids and to some extent by the nucleotide state (activation) of the protein. In addition, our results suggest that both the farnesyl and the polybasic hypervariable region (HVR) are responsible for its preferential partitioning within the liquid-disordered (Ld) domains in membranes, potentially enhancing the formation of membrane-driven signaling platforms.

Martini 3: a general purpose force field for coarse-grained molecular dynamics

The coarse-grained Martini force field is widely used in biomolecular simulations. Here we present the refined model, Martini 3 ( http://cgmartini.nl ), with an improved interaction balance, new bead types and expanded ability to include specific interactions representing, for example, hydrogen bonding and electronic polarizability. The updated model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.

Investigation on drug entrapment location in liposomes and transfersomes based on molecular dynamics simulation

In this study, liposome and transfersome were successfully constructed using molecular dynamics simulation. Three drugs with different polarity, including 5-fluorouracil, ligustrazine, and osthole, were selected as model drugs to study the distribution of drugs in lipid vesicles by calculating the radial distribution function and the potential of mean force. The solubility parameters between drugs and different regions in lipid vesicles were calculated to characterize the compatibility of drugs in different regions in lipid vesicles, which provided the basis for the conclusion of this paper. It showed that the radial distribution function and the potential of mean force were consistent in the characterization of drug distribution in vesicles, and the drug distribution in vesicles was closely related to the compatibility between drugs and vesicles. Therefore, the radial distribution function and the potential of mean force can be used to characterize the distribution of drugs in vesicles, and molecular simulation technology has a great potential in studying the characteristics of vesicles. Graphical abstract.

Not only in silico drug discovery: Molecular modeling towards in silico drug delivery formulations

The use of methods at molecular scale for the discovery of new potential active ligands, as well as previously unknown binding sites for target proteins, is now an established reality. Literature offers many successful stories of active compounds developed starting from insights obtained in silico and approved by Food and Drug Administration (FDA). One of the most famous examples is raltegravir, a HIV integrase inhibitor, which was developed after the discovery of a previously unknown transient binding area thanks to molecular dynamics simulations. Molecular simulations have the potential to also improve the design and engineering of drug delivery devices, which are still largely based on fundamental conservation equations. Although they can highlight the dominant release mechanism and quantitatively link the release rate to design parameters (size, drug loading, et cetera), their spatial resolution does not allow to fully capture how phenomena at molecular scale influence system behavior. In this scenario, the "computational microscope" offered by simulations at atomic scale can shed light on the impact of molecular interactions on crucial parameters such as release rate and the response of the drug delivery device to external stimuli, providing insights that are difficult or impossible to obtain experimentally. Moreover, the new paradigm brought by nanomedicine further underlined the importance of such computational microscope to study the interactions between nanoparticles and biological components with an unprecedented level of detail. Such knowledge is a fundamental pillar to perform device engineering and to achieve efficient and safe formulations. After a brief theoretical background, this review aims at discussing the potential of molecular simulations for the rational design of drug delivery systems.

Native-like membrane models of E. coli polar lipid extract shed light on the importance of lipid composition complexity

BACKGROUND

Lipid-protein interactions stabilize protein oligomers, shape their structure, and modulate their function. Whereas in vitro experiments already account for the functional importance of lipids by using natural lipid extracts, in silico methods lack behind by embedding proteins in single component lipid bilayers. However, to accurately complement in vitro experiments with molecular details at very high spatio-temporal resolution, molecular dynamics simulations have to be performed in natural(-like) lipid environments.

RESULTS

To enable more accurate MD simulations, we have prepared four membrane models of E. coli polar lipid extract, a typical model organism, each at all-atom (CHARMM36) and coarse-grained (Martini3) representations. These models contain all main lipid headgroup types of the E. coli inner membrane, i.e., phosphatidylethanolamines, phosphatidylglycerols, and cardiolipins, symmetrically distributed between the membrane leaflets. The lipid tail (un)saturation and propanylation stereochemistry represent the bacterial lipid tail composition of E. coli grown at 37∘C until 3/4 of the log growth phase. The comparison of the Simple three lipid component models to the complex 14-lipid component model Avanti over a broad range of physiologically relevant temperatures revealed that the balance of lipid tail unsaturation and propanylation in different positions and inclusion of lipid tails of various length maintain realistic values for lipid mobility, membrane area compressibility, lipid ordering, lipid volume and area, and the bilayer thickness. The only Simple model that was able to satisfactory reproduce most of the structural properties of the complex Avanti model showed worse agreement of the activation energy of basal water permeation with the here performed measurements. The Martini3 models reflect extremely well both experimental and atomistic behavior of the E. coli polar lipid extract membranes. Aquaporin-1 embedded in our native(-like) membranes causes partial lipid ordering and membrane thinning in its vicinity. Moreover, aquaporin-1 attracts and temporarily binds negatively charged lipids, mainly cardiolipins, with a distinct cardiolipin binding site in the crevice at the contact site between two monomers, most probably stabilizing the tetrameric protein assembly.

CONCLUSIONS

The here prepared and validated membrane models of E. coli polar lipids extract revealed that lipid tail complexity, in terms of double bond and cyclopropane location and varying lipid tail length, is key to stabilize membrane properties over a broad temperature range. In addition, they build a solid basis for manifold future simulation studies on more realistic lipid membranes bridging the gap between simulations and experiments.

Role of polyunsaturated phospholipids in liquid-ordered and liquid-disordered phases

Polyunsaturated phospholipids play a strong repulsive role in the liquid-disordered phase but a weak role in the liquid-ordered phase.

Interleaflet Decoupling in a Lipid Bilayer at Excess Cholesterol Probed by Spectroscopic Ellipsometry and Simulations

Artificial lipid membranes are often investigated as a replica of the cell membrane in the form of supported lipid bilayers (SLBs). In SLBs, the phase state of a lipid bilayer strongly depends on the presence of molecules such as cholesterol, ceramide, and physical parameters such as temperature. Cholesterol is a key molecule of biological membranes and it exerts condensing effect on lipid bilayers. In this paper, we demonstrate the influence of excess cholesterol content on a supported lipid bilayer of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) (fluid-phase) using spectroscopic ellipsometry (SE) and coarse-grained (CG) molecular dynamics (MD) simulations. The results show the condensation effect due to cholesterol addition up to 30% and interleaflet decoupling at excess cholesterol beyond 30%. SE results show the separation of individual leaflets of the bilayer and influence of cholesterol on the biophysical properties such as thickness and optical index. CG simulations were performed at different ratios of DOPC:cholesterol mixtures to explore cholesterol-driven bilayer properties and stability. The simulations displayed the accumulation of cholesterol molecules at the interface of the lower and upper leaflets of the bilayer, thus leading to undulations in the bilayer. This work reports the successful application of SE technique to study lipid-cholesterol interactions for the first time.

Nano-mechanical characterization of asymmetric DLPC/DSPC supported lipid bilayers

Asymmetric distribution of lipid molecules in the inner and outer leaflets of the plasma membrane is a common occurrence in the membrane formation. Such asymmetric arrangement is a crucial parameter to manipulate the properties of the cell membrane. It controls signal transduction, endocytosis, exocytosis in the cells. The artificial membrane is often used to study the lateral and transverse arrangement of the lipid molecules in place of the cell membrane. Nano-mechanical characterization of the model membrane helps to understand the mechanical stability of the lipid bilayer. The stability is sensitive to the variations in the lipid composition and their local organization. In this article, we present both topographical and nano-mechanical properties of lipid bilayer characterized by atomic force microscopy (AFM). The results show that the asymmetric lipid bilayer formation is an intrinsic character. We have selected a bi-component fluid-gel phase 1,2-dilauroyl-sn-glycero-3-phosphocholine:1,2-disteroyl-sn-glycero-3-phosphocholine (DLPC: DSPC) system for our studies. We have observed domain formation and phase separation in the bilayer by increasing the composition of the gel phase DSPC. In force spectroscopy studies, we determine the mechanical strength of the bilayer for unique mixtures of DLPC: DSPC by measuring the breakthrough force. These results also show the effect of asymmetry in the lipid bilayer. Besides AFM studies, we have implemented a coarse-grained (CG) molecular dynamics (MD) simulation using the gromacs package at room temperature and 1 bar pressure. The results from the simulation study have been compared with AFM study. It was found that the simulation studies corroborated the findings from AFM such as an increase in the bilayer thickness, change in the phase state, asymmetric and symmetric domain formation in the lipid bilayer.

Oxidation degree of a cell membrane model and its response to structural changes, a coarse-grained molecular dynamics approach

Oxidative stress plays an essential role in the regulation of vital processes in living organisms. Reactive oxygen species can react chemically with the constituents of the cells leading to irreversible damage. The first structure of the cell in contact with the environment that surrounds it is the membrane, which protects it and allows the exchange of substances. Some signals manifest when the components of a bilayer are undergoing oxidation, like an increase in the lipid area, decrease in the thickness of the bilayer, and exchange of the oxidized groups toward the bilayer surface. In this investigation, a molecular dynamics simulation was done on a set of Dioleoylphosphatidylcholine membranes with different percentage of oxidized lipids, in order to observe the effect of the oxidation degree on the membrane structure. It was found that, as higher the concentration of oxidized lipids is, the larger the damage of the membrane. This is reflected in the increase in the lipid area and the decrease in the thickness and membrane packing. Also, it was observed that hydrophobicity inside the membrane decreases as the oxidation percentage increases.Communicated by Ramaswamy H. Sarma.

Cryostabilization of the Cell Membrane of a Psychrotolerant Bacteria via Homeoviscous Adaptation

Homeoviscous adaptation (maintenance of a critical balance between the saturated and unsaturated lipids) of the cell membrane of psychrotolerant bacteria is essential to protect them against freeze-thaw cycle. But how does the homeoviscous adaptation protect the cell membrane during cold stress? In this Letter, we answer this question using a coarse-grained molecular dynamics simulation technique. On the basis of the reported fatty acid profiles of psychrotolerant bacteria at different temperatures, multiple lipid membranes are simulated at a wide range of temperatures between 250 and 300 K. We explicate how the homeoviscous adaptation minimizes the effect of cold stress on the structure and fluidity of the membrane. Partial freezing of the saturated lipid domain occurs with the self-aggregation of saturated and unsaturated lipids near the melting temperature of the unadapted lipid membrane. The gel-like phase provides necessary local packing density that can be sensed by sensor proteins responsible for the homeoviscous adaptation.

Principal component analysis highlights the influence of temperature, curvature and cholesterol on conformational dynamics of lipids

Membrane lipids are inherently highly dynamic molecules. Currently, it is difficult to probe the structures of individual lipids experimentally at the timescales corresponding to atomic motions, and consequently molecular dynamics simulations are used widely. In our previous work, we have introduced the principal component analysis (PCA) as a convenient framework for comprehensive quantitative description of lipid motions. Here, we present a newly developed open source script, PCAlipids, which automates the analysis and allows us to refine the approach and test its limitations. We use PCAlipids to determine the influence of temperature, cholesterol and curvature on individual lipids, and show that the most prominent lipid tail scissoring motion is strongly affected by these factors and allows tracking of phase transition. Addition of cholesterol affects the conformations and selectively changes the dynamics of lipid molecules, impacting the large-amplitude motions. Introduction of curvature biases the conformational ensembles towards more extended structures. We hope that the developed approach will be useful for understanding the molecular basis of different processes occurring in lipid membrane systems and will stimulate development of complementary experimental techniques probing the conformations of individual lipid molecules.