Understanding the Phase Behavior of Coarse-Grained Model Lipid Bilayers through Computational Calorimetry

Machine learning in molecular biophysics: Protein allostery, multi-level free energy simulations, and lipid phase transitions

Machine learning (ML) techniques have been making major impacts on all areas of science and engineering, including biophysics. In this review, we discuss several applications of ML to biophysical problems based on our recent research. The topics include the use of ML techniques to identify hotspot residues in allosteric proteins using deep mutational scanning data and to analyze how mutations of these hotspots perturb co-operativity in the framework of a statistical thermodynamic model, to improve the accuracy of free energy simulations by integrating data from different levels of potential energy functions, and to determine the phase transition temperature of lipid membranes. Through these examples, we illustrate the unique value of ML in extracting patterns or parameters from complex data sets, as well as the remaining limitations. By implementing the ML approaches in the context of physically motivated models or computational frameworks, we are able to gain a deeper mechanistic understanding or better convergence in numerical simulations. We conclude by briefly discussing how the introduced models can be further expanded to tackle more complex problems.

Polarizable atomic multipole-based force field for cholesterol

Cholesterol is one of the essential component of lipid in membrane. We present a polarizable atomic multipole force field (FF) for the molecular dynamic simulation of cholesterol. The FF building process follows the computational framework as the atomic multipole optimized energetics for biomolecular applications (AMOEBA) model. In this framework, the electronics parameters, including atomic monopole moments, dipole moments, and quadrupole moments calculated from ab initio calculations in the gas phase, are applied to represent the charge distribution. Furthermore, the many-body polarization is modeled by following the same pattern of distributed atomic polarizabilities. Then, the bilayers composed of two typical phospholipid molecules, 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), in a range of different cholesterol concentrations are built and implemented by molecular dynamics (MD) simulations based on the proposed polarizable FF. The simulation results are statistically analyzed to validate the feasibility of the proposed FF. The structural properties of the bilayers are calculated to compare with the related experimental values. The MD values show the same trend of experimental values changes.Communicated by Ramaswamy H. Sarma.

Brain Delivery of Protein Therapeutics by Cell Matrix-Inspired Biomimetic Nanocarrier

Protein therapeutics are anticipated to offer significant treatment options for central nervous system (CNS) diseases. However, the majority of proteins are unable to traverse the blood-brain barrier (BBB) and reach their CNS target sites. Inspired by the natural environment of active proteins, the cell matrix components hyaluronic acid (HA) and protamine (PRTM) are used to self-assemble with proteins to form a protein-loaded biomimetic core and then incorporated into ApoE3-reconstituted high-density lipoprotein (rHDL) to form a protein-loaded biomimetic nanocarrier (Protein-HA-PRTM-rHDL). This cell matrix-inspired biomimetic nanocarrier facilitates the penetration of protein therapeutics across the BBB and enables their access to intracellular target sites. Specifically, CAT-HA-PRTM-rHDL facilitates rapid intracellular delivery and release of catalase (CAT) via macropinocytosis-activated membrane fusion, resulting in improved spatial learning and memory in traumatic brain injury (TBI) model mice (significantly reduces the latency of TBI mice and doubles the number of crossing platforms), and enhances motor function and prolongs survival in amyotrophic lateral sclerosis (ALS) model mice (extended the median survival of ALS mice by more than 10 days). Collectively, this cell matrix-inspired nanoplatform enables the efficient CNS delivery of protein therapeutics and provides a novel approach for the treatment of CNS diseases.

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.

Surfactant Proteins SP-B and SP-C in Pulmonary Surfactant Monolayers: Physical Properties Controlled by Specific Protein-Lipid Interactions

The lining of the alveoli is covered by pulmonary surfactant, a complex mixture of surface-active lipids and proteins that enables efficient gas exchange between inhaled air and the circulation. Despite decades of advancements in the study of the pulmonary surfactant, the molecular scale behavior of the surfactant and the inherent role of the number of different lipids and proteins in surfactant behavior are not fully understood. The most important proteins in this complex system are the surfactant proteins SP-B and SP-C. Given this, in this work we performed nonequilibrium all-atom molecular dynamics simulations to study the interplay of SP-B and SP-C with multicomponent lipid monolayers mimicking the pulmonary surfactant in composition. The simulations were complemented by z-scan fluorescence correlation spectroscopy and atomic force microscopy measurements. Our state-of-the-art simulation model reproduces experimental pressure-area isotherms and lateral diffusion coefficients. In agreement with previous research, the inclusion of either SP-B and SP-C increases surface pressure, and our simulations provide a molecular scale explanation for this effect: The proteins display preferential lipid interactions with phosphatidylglycerol, they reside predominantly in the lipid acyl chain region, and they partition into the liquid expanded phase or even induce it in an otherwise packed monolayer. The latter effect is also visible in our atomic force microscopy images. The research done contributes to a better understanding of the roles of specific lipids and proteins in surfactant function, thus helping to develop better synthetic products for surfactant replacement therapy used in the treatment of many fatal lung-related injuries and diseases.

Nucleation and growth of gold nanoparticles in the presence of different surfactants. A dissipative particle dynamics study

Nanoparticles (NPs) show promising applications in biomedicine, catalysis, and energy harvesting. This applicability relies on controlling the material’s features at the nanometer scale. Surfactants, a unique class of surface-active molecules, have a remarkable ability to tune NPs activity; provide specific functions, avoid their aggregation, and create stable colloidal solutions. Surfactants also control nanoparticles’ nucleation and growth processes by modifying nuclei solubility and surface energy. While nucleation seems independent from the surfactant, NP’s growth depends on it. NP`s size is influenced by the type of functional group (C, O, S or N), length of its C chain and NP to surfactant ratio. In this paper, gold nanoparticles (Au NPs) are taken as model systems to study how nucleation and growth processes are affected by the choice of surfactants by Dissipative Particle Dynamics (DPD) simulations. DPD has been mainly used for studying biochemical structures, like lipid bilayer models. However, the study of solid NPs, and their conjugates, needs the introduction of a new metallic component. To represent the collective phenomena of these large systems, their degrees of freedom are reduced by Coarse-Grained (CG) models. DPD behaved as a powerful tool for studying complex systems and shedding some light on some experimental observations, otherwise difficult to explain.

Machine Learning-Assisted Phase Transition Temperatures from Generalized Replica Exchange Simulations of Dry Martini Lipid Bilayers

Accurate estimation of phase transition temperatures has been a longstanding challenge for molecular simulations. Recently, the generalized Replica Exchange technique for estimating phase transition temperatures has allowed for improved sampling of the phase transition; however, it requires a significant number of simultaneous replicas both inside and outside of the transition region leading to costly computational expense. In this work, the recently developed machine learning-assisted lipid phase analysis technique for learning the phase of individual lipids has been combined with generalized Replica Exchange Molecular Dynamics to reduce the overall computational expense of evaluating transition temperatures. This technique is then applied to eight different Dry Martini lipids to demonstrate its ability to describe transition temperatures as a function of chain length and tail saturation.

Interfacial behavior of phospholipid monolayers revealed by mesoscopic simulation

A mesoscopic model with molecular resolution is presented for dipalmitoyl phosphatidylcholine (DPPC) and palmitoyl oleoyl phosphatidylcholine (POPC) monolayer simulations at the air-water interface using many-body dissipative particle dynamics (MDPD). The parameterization scheme is rigorously based on reproducing the physical properties of water and alkane and the interfacial property of the phospholipid monolayer by comparison with experimental results. Using much less computing cost, these MDPD simulations yield a similar surface pressure-area isotherm as well as similar pressure-related morphologies as all-atom simulations and experiments. Moreover, the compressibility modulus, order parameter of lipid tails, and thickness of the phospholipid monolayer are quantitatively in line with the all-atom simulations and experiments. This model also captures the sensitive changes in the pressure-area isotherms of mixed DPPC/POPC monolayers with altered mixing ratios, indicating that the model is promising for applications with complex natural phospholipid monolayers. These results demonstrate a significant improvement of quantitative phospholipid monolayer simulations over previous coarse-grained models.

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.

Carbon nanotube transmembrane channel formation and single-stranded DNA spontaneous internalization: a dissipative particle dynamics study

Single-walled carbon nanotube (SWCNT) transmembrane channel formation in a pure 1,2-dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC) bilayer, and the spontaneous internalization of single-stranded DNA (ssDNA) into the formed pore were simulated. A combination of computational techniques, Dissipative Particle Dynamics-Monte Carlo hybrid simulations and quantum mechanical calculations at the hybrid-DFT level, was used as a new proposal to perform DPD simulations granting specific chemical identity to the model particles. The simulated transmembrane channels showed that, in the case of pristine SWCNTs and upon increasing the nanotube length, a higher tilt angle with respect to the bilayer normal is observed and more time is needed for the nanotube to stabilize. On the other hand, for SWCNTs with polar rims an almost perpendicular orientation is preferred with less than 15° of tilt with respect to the bilayer normal once the nanotubes have pierced both monolayers. These findings are supported by experimental observations where CNTs of average inner diameters of 1.51 ± 0.21 nm and lengths in the 5-15 nm range were inserted in DOPC membranes [J. Geng, et al., Nature, 2014, 514(7524), 612-615]. Moreover, the narrower the SWCNTs, the slower the spontaneous internalization of ssDNA becomes, and ssDNA ends hydrophobically trapped inside the artificial pore. A dependence on the nucleotide content is found indicating that the higher the presence of adenine and thymine in the ssDNA chains the slower the internalization becomes, in agreement with the experimental [A. M. Ababneh, et al., Biophys. J., 2003, 85(2), 1111-1127] and predicted solvation tendency in water for nucleic acid bases.

Stiffening transition in asymmetric lipid bilayers: The role of highly ordered domains and the effect of temperature and size

Cellular membranes consist of a large variety of lipids and proteins, with a composition that generally differs between the two leaflets of the same bilayer. One consequence of this asymmetry is thought to be the emergence of differential stress, i.e., a mismatch in the lateral tension of the two leaflets. This can affect a membrane's mechanical properties; for instance, it can increase the bending rigidity once the differential stress exceeds a critical threshold. Using coarse-grained molecular dynamics simulations based on the MARTINI model, we show that this effect arises due to the formation of more highly ordered domains in the compressed leaflet. The threshold asymmetry increases with temperature, indicating that the transition to a stiffened regime might be restricted to a limited temperature range above the gel transition. We also show that stiffening occurs more readily for larger membranes with smaller typical curvatures, suggesting that the stiffening transition is easier to observe experimentally than in the small-scale systems accessible to simulation.

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.

Martini Coarse-Grained Model of Hyaluronic Acid for the Structural Change of Its Gel in the Presence of Monovalent and Divalent Salts

Hyaluronic acid (HA) has a wide range of biomedical applications including the formation of hydrogels, microspheres, sponges, and films. The modeling of HA to understand its behavior and interaction with other biomolecules at the atomic level is of considerable interest. The atomistic representation of long HA polymers for the study of the macroscopic structural formation and its interactions with other polyelectrolytes is computationally demanding. To overcome this limitation, we developed a coarse grained (CG) model for HA adapting the Martini scheme. A very good agreement was observed between the CG model and all-atom simulations for both local (bonded interactions) and global properties (end-to-end distance, a radius of gyration, RMSD). Our CG model successfully demonstrated the formation of HA gel and its structural changes at high salt concentrations. We found that the main role of CaCl₂ is screening the electrostatic repulsion between chains. HA gel did not collapse even at high CaCl₂ concentrations, and the osmotic pressure decreased, which agrees well with the experimental results. This is a distinct property of HA from other proteins or polynucleic acids which ensures the validity of our CG model. Our HA CG model is compatible with other CG biomolecular models developed under the Martini scheme, which allows for large-scale simulations of various HA-based complex systems.

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.

Simulation Best Practices for Lipid Membranes [Article v1.0]

We establish a reliable and robust standardization of settings for practical molecular dynamics (MD) simulations of pure and mixed (single- and multi-component) lipid bilayer membranes. In lipid membranes research, particle-based molecular simulations are a powerful tool alongside continuum theory, lipidomics, and model, in vitro, and in vivo experiments. Molecular simulations can provide precise and reproducible spatiotemporal (atomic- and femtosecond-level) information about membrane structure, mechanics, thermodynamics, kinetics, and dynamics. Yet the simulation of lipid membranes can be a daunting task, given the uniqueness of lipid membranes relative to conventional liquid-liquid and solid-liquid interfaces, the immense and complex thermodynamic and statistical mechanical theory, the diversity of multiscale lipid models, limitations of modern computing power, the difficulty and ambiguity of simulation controls, finite size effects, competitive continuum simulation alternatives, and the desired application, including vesicle experiments and biological membranes. These issues can complicate an essential understanding of the field of lipid membranes, and create major bottlenecks to simulation advancement. In this article, we clarify these issues and present a consistent, thorough, and user-friendly framework for the design of state-of-the-art lipid membrane MD simulations. We hope to allow early-career researchers to quickly overcome common obstacles in the field of lipid membranes and reach maximal impact in their simulations.

Diblock copolymer bilayers as model for polymersomes: A coarse grain approach

This paper presents a new model for polymersomes developed using a poly(ethylene oxide)-poly(butadiene) diblock copolymer bilayer. The model is based on a coarse-grained approach using the MARTINI force field. Since no MARTINI parameters exist for poly(butadiene), we have refined these parameters using quantum mechanical calculations and molecular dynamics simulations. The model has been validated using extensive molecular dynamics simulations in systems with several hundred polymer units and reaching up to 6 μs. These simulations show that the copolymer coarse grain model self-assemble into bilayers and that NPT and NP_NγT ensemble runs reproduce key structural and mechanical experimental properties for different copolymer length chains with a similar hydrophilic weight fraction.

Immunogene therapy with fusogenic nanoparticles modulates macrophage response to Staphylococcus aureus

The incidence of adverse effects and pathogen resistance encountered with small molecule antibiotics is increasing. As such, there is mounting focus on immunogene therapy to augment the immune system’s response to infection and accelerate healing. A major obstacle to in vivo gene delivery is that the primary uptake pathway, cellular endocytosis, results in extracellular excretion and lysosomal degradation of genetic material. Here we show a nanosystem that bypasses endocytosis and achieves potent gene knockdown efficacy. Porous silicon nanoparticles containing an outer sheath of homing peptides and fusogenic liposome selectively target macrophages and directly introduce an oligonucleotide payload into the cytosol. Highly effective knockdown of the proinflammatory macrophage marker IRF5 enhances the clearance capability of macrophages and improves survival in a mouse model of Staphyloccocus aureus pneumonia.

In the context of increasing bacterial antibiotic-resistance, gene therapy that targets the immune system to clear infection is a major goal. Here the authors show a silicon based nanosystem that modulates the macrophage response in an in vivo model of Staphylococcal pneumonia.

Transferable Coarse-Grained Models of Liquid-Liquid Equilibrium Using Local Density Potentials Optimized with the Relative Entropy

Bottom-up coarse-grained (CG) models are now regularly pursued to enable large length and time scale molecular simulations of complex, often macromolecular systems. However, predicting fluid phase equilibria using such models remains fundamentally challenging. A major problem stems from the typically low transferability of CG models beyond the densities and/or compositions at which they are parametrized, which is necessary if they are to describe distinct structural and thermodynamic properties unique to each phase. CG model transferability is compounded by the representation of the inherently multibody coarse interactions using pair potentials that neglect higher order effects. Here, we propose to construct transferable single site CG models of liquid mixtures by supplementing traditional CG pair interactions with local density potentials, which constitute a computationally inexpensive mean-field approach to describe many-body effects, in that site energies are modulated by the local solution environment. To illustrate the approach, we use intra- and interspecies local density potentials to develop CG models of benzene-water solutions that show impressive transferability in structural metrics (pair correlation functions, density profiles) throughout composition space, in contrast to pair-only CG representations. While further refinement may be necessary to represent more complex thermodynamic properties, like the liquid-liquid interfacial tension, the generality and improvement offered by the local density approach are highly encouraging for enabling complex phase equilibrium modeling using CG models.

Molecular Structuring and Phase Transition of Lipid-Based Formulations upon Water Dispersion: A Coarse-Grained Molecular Dynamics Simulation Approach

The internal molecular structure of lipid-based formulations (LBFs) is poorly understood. In this work we aimed at establishing coarse-grained molecular dynamics simulations as a tool for rapid screening and investigation of the internal environment of these formulations. In order to study complex LBFs composed of different kinds of lipids we simulated a number of systems containing either medium-chain or long-chain lipids with varying proportions of tri-, di-, and monoglycerides. Structural and dynamic measurements and analyses identified that the internal environment in a mixture of lipids was locally ordered even in the absence of water, which might explain some of the previously reported effects on drug solubility in these systems. Further, phase changes occurring upon water dispersion are well captured with coarse-grained simulations. Based on these simulations we conclude that the coarse-grained methodology is a promising in silico approach for rapid screening of structures formed in complex formulations. More importantly it facilitates molecular understanding of interactions between excipients and water at a feasible time scale and, hence, opens up for future virtual drug formulation studies.

The Effects of Alkyl Chain Combinations on the Structural and Mechanical Properties of Biomimetic Ion Pair Amphiphile Bilayers

Ion pair amphiphile (IPA), a lipid-like complex composed of a pair of cationic and anionic surfactants, has great potentials in various pharmaceutical applications. In this work, we utilized molecular dynamics (MD) simulation to systematically examine the structural and mechanical properties of the biomimetic bilayers consist of alkyltrimethyl-ammonium-alkylsulfate (C_mTMA⁺-C_nS⁻) IPAs with various alkyl chain combinations. Our simulations show an intrinsic one-atom offset for the C_mTMA⁺ and C_nS⁻ alignment, leading to the asymmetric index definition of ΔC = m − (n + 1). Larger |ΔC| gives rise to higher conformational fluctuations of the alkyl chains with the reduced packing order and mechanical strength. In contrast, increasing the IPA chain length enhances the van der Waals interactions within the bilayer and thus improves the bilayer packing order and mechanical properties. Further elongating the C_mTMA⁺-C_nS⁻ alkyl chains to m and n ≥ 12 causes the liquid disorder to gel phase transition of the bilayer at 298 K, with the threshold membrane properties of 0.45 nm² molecular area, deuterium order parameter value of 0.31, and effective bending rigidity of 20 k_BT, etc. The combined results provide molecular insights into the design of biomimetic IPA bilayers with wide structural and mechanical characteristics for various applications.

Effects of Coarse Graining and Saturation of Hydrocarbon Chains on Structure and Dynamics of Simulated Lipid Molecules

Molecular dynamics simulations are used extensively to study the processes on biological membranes. The simulations can be conducted at different levels of resolution: all atom (AA), where all atomistic details are provided; united atom (UA), where hydrogen atoms are treated inseparably of corresponding heavy atoms; and coarse grained (CG), where atoms are grouped into larger particles. Here, we study the behavior of model bilayers consisting of saturated and unsaturated lipids DOPC, SOPC, OSPC and DSPC in simulations performed using all atom CHARMM36 and coarse grained Martini force fields. Using principal components analysis, we show that the structural and dynamical properties of the lipids are similar, both in AA and CG simulations, although the unsaturated molecules are more dynamic and favor more extended conformations. We find that CG simulations capture 75 to 100% of the major collective motions, overestimate short range ordering, result in more flexible molecules and 5–7 fold faster sampling. We expect that the results reported here will be useful for comprehensive quantitative comparisons of simulations conducted at different resolution levels and for further development and improvement of CG force fields.

Enhanced Sampling of Phase Transitions in Coarse-Grained Lipid Bilayers

Freezing and melting of dipalmitoylphosphatidylcholine (DPPC) bilayers are simulated in both the explicit (Wet) and implicit solvent (Dry) coarse-grained MARTINI force fields with enhanced sampling, via the isobaric, molecular dynamics version of the generalized replica exchange method (gREM). Phase transitions are described with the entropic viewpoint, based upon the statistical temperature as a function of enthalpy, T_S(H) = 1/(dS(H)/dH), where S is the configurational entropy. Bilayer thickness, area per lipid, and the second-rank order parameter (P2) are calculated vs temperature in the transition range. In a 32-lipid Wet MARTINI system, transitions in the lipid and water subsystems are strongly coupled, giving rise to considerable structure in T_S(H) and the need to specify the state of the water when reporting a lipid transition temperature. For gel lipid + liquid water → fluid lipid + liquid water, we find 292.4 K. The small system is influenced by finite-size effects, but it is argued that the entropic approach is well suited to revealing them, which will be particularly relevant for studies of finite nanosystems where there is no thermodynamic limit. In a 390-lipid Dry MARTINI system, two-dimensional analogues of the topographies of coexisting states ("subphases") seen in pure fluids are found. They are not seen in the 32-lipid Wet or Dry system, but the Dry lipids show a new type of state with gel in one leaflet and tilted gel in the other. Dry bilayer transition temperatures are 333.3 K (390 lipids) and 338 K (32 lipids), indicating that the 32-lipid system is not too small for a qualitative study of the transition. Physical arguments are given for Dry lipid system size dependence and for the difference between Wet and Dry systems.

Hysteresis and the Cholesterol Dependent Phase Transition in Binary Lipid Mixtures with the Martini Model

Extensive Martini simulation data, totaling 5 ms, is presented for binary mixtures of dipalmitoylphosphatidylcholine (DPPC) and cholesterol. Using simulation initiated from both gel (s_o) and liquid-disordered (L_d) phases, significant and strongly cholesterol-dependent hysteresis in the enthalpy as a function of temperature is observed for cholesterol mole fractions from 0 to 20 mol %. Although the precise phase transition temperature cannot be determined due to the hysteresis, the data are consistent with a first order gel to fluid transition, which increases in temperature with cholesterol. At 30 mol % cholesterol, no hysteresis is observed, and there is no evidence for a continuous transition, in either structural parameters like the area per lipid or in the heat capacity as a function of temperature. The results are consistent with a single uniform phase above a critical cholesterol composition between 20 and 30 mol % in Martini, while highlighting the importance and difficulty of obtaining the equilibrium averages to locate phase boundaries precisely in computational models of lipid bilayers.

The Configuration of Copolymer Ligands on Nanoparticles Affects Adhesion and Uptake

Nanoparticles (NPs) are promising carriers for targeted drug delivery, photodynamic therapy, and imaging probes. A fundamental understanding of the dynamics of polymeric NP targeting to bilayer membranes is important to enhance the design of NPs for higher adhesion, binding percentage, and efficiency. In this study, dissipative particle dynamics simulations are applied to investigate the adhesion and uptake processes of the rod, spherical, and striped NPs to cell membranes. It is observed that the striped ligands can prevent NPs from rotating even in active rotation. We further optimize striped NP to a more stabilized structure. Uptake processes of NPs with different configurations are thoroughly investigated in our simulations and among which Janus NP are indicated to improve the penetration rate to 100%. These findings provide better insight into patterned NP design and may help fabricate new NPs for biomedical applications.

DPPC-cholesterol phase diagram using coarse-grained Molecular Dynamics simulations

Cholesterol-phospholipid bilayers continue to be the current state of the art in membrane models and serve as representative systems for studying the effect of cholesterol on the cell membrane. As the mixing of different lipid species requires long spatio-temporal scales, coarse-grained models have gained increasing popularity in modeling such membrane systems. In this paper, a systematic study of the MARTINI coarse-grained model for the DPPC-cholesterol binary system has been performed. We construct the phase diagram of DPPC lipid bilayers in the presence of different cholesterol concentrations and at different temperatures using coarse-grained Molecular Dynamics (MD) simulations with the MARTINI force field. The phase diagram based on the condensation effect is directly comparable to available experimental data and demonstrates qualitative agreement over all cholesterol concentrations. Self-assembled bilayers quantitatively reproduce experimental observables, such as lateral diffusion of lipids, electron density, area per lipid and lipid order parameters. The phase diagram of the DPPC-cholesterol binary system also reveals the profound effect of cholesterol on the physical properties of phospholipid bilayers such lipid order, diffusion, and fluidity. Cholesterol induces the liquid-ordered phase, which increases the fluidity of the phospholipid hydrocarbon chains above the gel to liquid-crystalline phase transition temperature and decreases it below the phase transition. The present study suggests that the MARTINI force field can be successfully used to obtain molecular level insights into cholesterol-DPPC model membranes.

Pre-transition effects mediate forces of assembly between transmembrane proteins

We present a mechanism for a generic, powerful force of assembly and mobility for transmembrane proteins in lipid bilayers. This force is a pre-transition (or pre-melting) effect for the first-order transition between ordered and disordered phases in the membrane. Using large-scale molecular simulation, we show that a protein with hydrophobic thickness equal to that of the disordered phase embedded in an ordered bilayer stabilizes a microscopic order–disorder interface. The stiffness of that interface is finite. When two such proteins approach each other, they assemble because assembly reduces the net interfacial energy. Analogous to the hydrophobic effect, we refer to this phenomenon as the 'orderphobic effect'. The effect is mediated by proximity to the order–disorder phase transition and the size and hydrophobic mismatch of the protein. The strength and range of forces arising from this effect are significantly larger than those that could arise from membrane elasticity for the membranes considered.

DOI:http://dx.doi.org/10.7554/eLife.13150.001

The membrane that surrounds cells provides a selective barrier that allows some molecules through, but blocks the path of others. A cell’s membrane is made up of two layers of molecules with oily tails, and is therefore known as a bilayer. Many proteins are dotted within and on the inner and outer surfaces of the bilayer: some act as channels that control what goes in and out of the cell, while others protrude outside the cell so that they can sense changes in the environment.

Membrane proteins can move and interact within the bilayer, and various models have emerged to try to explain this dynamic system. These models are based on the membrane having some fluidity but also having regions where there is more structure, and typically describe the proteins as ordered clusters floating in an otherwise disordered fluid membrane. However, many researchers now think some proteins that pass through both layers of the bilayer (i.e., transmembrane proteins) make membranes more ordered, with a possibly gel-like state. However, it is not clear how transmembrane proteins can move and assemble together within such a relatively rigid membrane.

To investigate this, Katira, Mandadapu, Vaikuntanathan et al. carried out computer simulations using a model of a simple bilayer membrane. This membrane can exist in an ordered state, where the oily tails are neatly aligned, or a disordered state, where they are irregularly packed. Virtual ‘heating’ of the membrane caused it to shift from an ordered to a disordered state. When a simple transmembrane protein favoring the disordered state was inserted into the ordered state of the modeled membrane, disordered regions formed locally around the protein and the protein was able to diffuse within the membrane.

Modeling what would happen if two transmembrane proteins approached each other revealed that a consequence of the order–disorder transition is a strong attractive force that assembles the proteins together. Katira, Mandadapu, Vaikuntanathan et al. named this new phenomenon the 'orderphobic effect'. The forces arising from this effect were much greater than those currently believed to contribute to the assembly of membrane protein complexes, such as those generated by the elasticity of the membrane. This means that the orderphobic effect may be responsible for generating the protein clusters commonly seen in cell membranes.

Future work should next explore the opposite effect, where proteins favoring the ordered state are inserted into the disordered state of a membrane. This is expected to cause clustering of such proteins and thus large ordered regions in an otherwise disordered membrane.

DOI:http://dx.doi.org/10.7554/eLife.13150.002

Force Field Development for Lipid Membrane Simulations

With the rapid development of computer power and wide availability of modelling software computer simulations of realistic models of lipid membranes, including their interactions with various molecular species, polypeptides and membrane proteins have become feasible for many research groups. The crucial issue of the reliability of such simulations is the quality of the force field, and many efforts, especially in the latest several years, have been devoted to parametrization and optimization of the force fields for biomembrane modelling. In this review, we give account of the recent development in this area, covering different classes of force fields, principles of the force field parametrization, comparison of the force fields, and their experimental validation. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.

Modeling Nanoparticle Targeting to a Vascular Surface in Shear Flow Through Diffusive Particle Dynamics

Nanoparticles are regarded as promising carriers for targeted drug delivery and imaging probes. A fundamental understanding of the dynamics of polymeric nanoparticle targeting to receptor-coated vascular surfaces is therefore of great importance to enhance the design of nanoparticles toward improving binding ability. Although the effects of particle size and shear flow on the binding of nanoparticles to a vessel wall have been studied at the particulate level, a computational model to investigate the details of the binding process at the molecular level has not been developed. In this research, dissipative particle dynamics simulations are used to study nanoparticles with diameters of several nanometers binding to receptors on vascular surfaces under shear flow. Interestingly, shear flow velocities ranging from 0 to 2000 s(-1) had no effect on the attachment process of nanoparticles very close to the capillary wall. Increased binding energy between the ligands and wall caused a corresponding linear increase in bonding ability. Our simulations also indicated that larger nanoparticles and those of rod shape with a higher aspect ratio have better binding ability than those of smaller size or rounder shape.

Emergent properties arising from the assembly of amphiphiles. Artificial vesicle membranes as reaction promoters and regulators

This article deals with artificial vesicles and their membranes as reaction promoters and regulators. Among the various molecular assemblies which can form in an aqueous medium from amphiphilic molecules, vesicle systems are unique. Vesicles compartmentalize the aqueous solution in which they exist, independent on whether the vesicles are biological vesicles (existing in living systems) or whether they are artificial vesicles (formed in vitro from natural or synthetic amphiphiles). After the formation of artificial vesicles, their aqueous interior (the endovesicular volume) may become - or may be made - chemically different from the external medium (the exovesicular solution), depending on how the vesicles are prepared. The existence of differences between endo- and exovesicular composition is one of the features on the basis of which biological vesicles contribute to the complex functioning of living organisms. Furthermore, artificial vesicles can be formed from mixtures of amphiphiles in such a way that the vesicle membranes become molecularly, compositionally and organizationally highly complex, similarly to the lipidic matrix of biological membranes. All the various properties of artificial vesicles as membranous compartment systems emerge from molecular assembly as these properties are not present in the individual molecules the system is composed of. One particular emergent property of vesicle membranes is their possible functioning as promoters and regulators of chemical reactions caused by the localization of reaction components, and possibly catalysts, within or on the surface of the membranes. This specific feature is reviewed and highlighted with a few selected examples which range from the promotion of decarboxylation reactions, the selective binding of DNA or RNA to suitable vesicle membranes, and the reactivation of fragmented enzymes to the regulation of the enzymatic synthesis of polymers. Such type of emergent properties of vesicle membranes may have been important for the prebiological evolution of protocells, the hypothetical compartment systems preceding the first cells in those chemical and physico-chemical processes that led to the origin of life.

PSII-LHCII supercomplex organizations in photosynthetic membrane by coarse-grained simulation

Green plant photosystem II (PSII) and light-harvesting complex II (LHCII) in the stacked grana regions of thylakoid membranes can self-organize into various PSII-LHCII supercomplexes with crystalline or fluid-like supramolecular structures to adjust themselves with external stimuli such as high/low light and temperatures, rendering tunable solar light absorption spectrum and photosynthesis efficiencies. However, the mechanisms controlling the PSII-LHCII supercomplex organizations remain elusive. In this work, we constructed a coarse-grained (CG) model of the thylakoid membrane including lipid molecules and a PSII-LHCII supercomplex considering association/dissociation of moderately bound-LHCIIs. The CG interaction between CG beads were constructed based on electron microscope (EM) experimental results, and we were able to simulate the PSII-LHCII supramolecular organization of a 500 × 500 nm(2) thylakoid membrane, which is compatible with experiments. Our CGMD simulations can successfully reproduce order structures of PSII-LHCII supercomplexes under various protein packing fractions, free-LHCII:PSII ratios, and temperatures, thereby providing insights into mechanisms leading to PSII-LHCII supercomplex organizations in photosynthetic membranes.

Theoretical and computational investigations of nanoparticle-biomembrane interactions in cellular delivery

With the rapid development of nanotechnology, nanoparticles have been widely used in many applications such as phototherapy, cell imaging, and drug/gene delivery. A better understanding of how nanoparticles interact with bio-system (especially cells) is of great importance for their potential biomedical applications. In this review, the current status and perspective of theoretical and computational investigations is presented on the nanoparticle-biomembrane interactions in cellular delivery. In particular, the determining parameters (including the properties of nanoparticles, cell membranes and environments) that govern the cellular uptake of nanoparticles (direct penetration and endocytosis) are discussed. Further, some special attention is paid to their interactions beyond the translocation of nanoparticles across membranes (e.g., nanoparticles escaping from endosome and entering into nucleus). Finally, a summary is given, and the challenging problems of this field in the future are identified.

Coarse-grain simulations of skin ceramide NS with newly derived parameters clarify structure of melted phase

Ceramides are lipids that are involved in numerous biologically important structures (e.g., the stratum corneum and ceramide-rich platforms) and processes (e.g., signal transduction and membrane fusion), but their behavior is not fully understood. We report coarse-grain force field parameters for N-lignocerylsphingosine (ceramide NS, also known as ceramide 2) that are consistent with the Martini force field. These parameters were optimized for simulations in the gel phase and validated against atomistic simulations. Coarse-grained simulations with our parameters provide areas per lipid, membrane thicknesses, and electron density profiles that are in good agreement with atomistic simulations. Properties of the simulated membranes are compared with available experimental data. The obtained parameters were used to model the phase behavior of ceramide NS as a function of temperature and hydration. At low water content and above the main phase transition temperature, the bilayer melts into an irregular phase, which may correspond to the unstructured melted-chain phase observed in X-ray diffraction experiments. The developed parameters also reproduce the extended conformation of ceramide, which may occur in the stratum corneum. The parameters presented herein will facilitate studies on important complex functional structures such as the uppermost layer of the skin and ceramide-rich platforms in phospholipid membranes.

Computer simulations of phase separation in lipid bilayers and monolayers

Studying phase coexistence in lipid bilayers and monolayers is important for understanding lipid-lipid interactions underlying lateral organization in biological membranes. Computer simulations follow experimental approaches and use model lipid mixtures of simplified composition. Atomistic simulations give detailed information on the specificity of intermolecular interactions, while coarse-grained simulations achieve large time and length scales and provide a bridge towards state-of-the-art experimental techniques. Computer simulations allow characterizing the structure and composition of domains during phase transformations at Angstrom and picosecond resolution, and bring new insights into phase behavior of lipid membranes.

Tristearin bilayers: structure of the aqueous interface and stability in the presence of surfactants

Molecular dynamics simulations predict that sodium dodecylbenzene sulphonate surfactant molecules embed themselves in a tristearin bilayer, packing commensurate with the hexagonally packed lattice formed by the acyl tails of tristearin.

Infinitely dilute partial molar properties of proteins from computer simulation

A detailed understanding of temperature and pressure effects on an infinitely dilute protein's conformational equilibrium requires knowledge of the corresponding infinitely dilute partial molar properties. Established molecular dynamics methodologies generally have not provided a way to calculate these properties without either a loss of thermodynamic rigor, the introduction of nonunique parameters, or a loss of information about which solute conformations specifically contributed to the output values. Here we implement a simple method that is thermodynamically rigorous and possesses none of the above disadvantages, and we report on the method's feasibility and computational demands. We calculate infinitely dilute partial molar properties for two proteins and attempt to distinguish the thermodynamic differences between a native and a denatured conformation of a designed miniprotein. We conclude that simple ensemble average properties can be calculated with very reasonable amounts of computational power. In contrast, properties corresponding to fluctuating quantities are computationally demanding to calculate precisely, although they can be obtained more easily by following the temperature and/or pressure dependence of the corresponding ensemble averages.

Laterally structured ripple and square phases with one and two dimensional thickness modulations in a model bilayer system

Molecular dynamics simulations of bilayers in a surfactant/co-surfactant/water system with explicit solvent molecules show formation of topologically distinct gel phases depending upon the bilayer composition. At low temperatures, the bilayers transform from the tilted gel phase, Lβ', to the one dimensional (1D) rippled, Pβ' phase as the surfactant concentration is increased. More interestingly, we observe a two dimensional (2D) square phase at higher surfactant concentration which, upon heating, transforms to the gel Lβ' phase. The thickness modulations in the 1D rippled and square phases are asymmetric in two surfactant leaflets and the bilayer thickness varies by a factor of ∼2 between maximum and minimum. The 1D ripple consists of a thinner interdigitated region of smaller extent alternating with a thicker non-interdigitated region. The 2D ripple phase is made up of two superimposed square lattices of maximum and minimum thicknesses with molecules of high tilt forming a square lattice translated from the lattice formed with the thickness minima. Using Voronoi diagrams we analyze the intricate interplay between the area-per-head-group, height modulations and chain tilt for the different ripple symmetries. Our simulations indicate that composition plays an important role in controlling the formation of low temperature gel phase symmetries and rippling accommodates the increased area-per-head-group of the surfactant molecules.

Modulation of a small two-domain lipid vesicle by linactants

Linactants, molecules that preferentially localize at the boundary of lipid membrane domains, are attracting considerable attention in recent years due to the recognition that they might regulate lipid-phase separation and thereby modulate membrane morphology. Recent studies have also shown that clustering of some line active agents enhances their ability to modulate membrane curvature. However, the molecular origin of this phenomenon, and the degree to which it impacts biological membranes, remains poorly understood. In this work, we have investigated how linactants induce shape change in multidomain small unilamallar vesicles (SUVs) using extensive dissipative particle dynamics simulations. The linactant was modeled as a two-tailed hybrid lipid with the two tails differing in preference for different lipid domains. We found that addition of a small amount of linactants (∼1%) to a two-domain vesicle leads to substantial reduction in the line tension and neck curvature at the domain boundary. Using cross-linking as a surrogate for clustering, we further show that linactant clusters substantially enhance the boundary preference and therefore the reduction in neck curvature. Moreover, on the basis of analyses of the corresponding changes in the membrane energetics, we highlight how linactants might stabilize nanoscale domains. These results have important implications for the potential existence and physical explanations of nanosized domains in biological membranes.

Interactions between fengycin and model bilayers quantified by coarse-grained molecular dynamics

Bacteria, particularly of the genus Bacillus, produce a wide variety of antifungal compounds. They act by affecting the lipid bilayers of fungal membranes, causing curvature-induced strain and eventual permeabilization. One class of these, known as fengycins, has been commercialized for treating agricultural infections and shows some promise as a possible antifungal pharmaceutical. Understanding the mechanism by which fengycins damage lipid bilayers could prove useful to the future development of related antifungal treatments. In this work, we present multi-microsecond-long simulations of fengycin interacting with different lipid bilayer systems. We see fengycin aggregation and uncover a clear aggregation pattern that is partially influenced by bilayer composition. We also quantify some local bilayer perturbations caused by fengycin binding, including curvature of the lipid bilayer and local electrostatic-driven reorganization.

The power of coarse graining in biomolecular simulations

Computational modeling of biological systems is challenging because of the multitude of spatial and temporal scales involved. Replacing atomistic detail with lower resolution, coarse grained (CG), beads has opened the way to simulate large-scale biomolecular processes on time scales inaccessible to all-atom models. We provide an overview of some of the more popular CG models used in biomolecular applications to date, focusing on models that retain chemical specificity. A few state-of-the-art examples of protein folding, membrane protein gating and self-assembly, DNA hybridization, and modeling of carbohydrate fibers are used to illustrate the power and diversity of current CG modeling.