Biomembranes are built up from lipid bilayers with two leaflets that typically differ in their lipid composition. Each lipid molecule stays within one leaflet of the bilayer before it undergoes a ...transition, or flip-flop, to the other leaflet. The corresponding flip-flop times are very different for different lipid species and vary over several orders of magnitude. Here, we use molecular dynamics simulations to elucidate the consequences of this separation of time scales for compositionally asymmetric bilayers. We first study bilayers with two lipid components that do not undergo flip-flops on the accessible time scales. In such a situation, one must distinguish a bilayer state in which both leaflets have the same preferred area from another state in which each leaflet is tensionless. However, when we add a third lipid component that undergoes frequent flip-flops, the bilayer relaxes toward the state with tensionless leaflets, not to the state with equal preferred leaflet areas. Furthermore, we show that bilayers with compositional asymmetry acquire a significant spontaneous curvature even if both leaflets are tensionless. Our results can be extended to lipid bilayers with a large number of lipid components provided at least one of these components undergoes frequent flip-flops. For cellular membranes containing lipid pumps, the leaflet tensions also depend on the rates of protein-induced flip-flops.
The ganglioside GM1 is present in neuronal membranes at elevated concentrations with an asymmetric spatial distribution. It is known to generate curvature and can be expected to strongly influence ...the neuron morphology. To elucidate these effects, we prepared giant vesicles with GM1 predominantly present in one leaflet of the membrane, mimicking the asymmetric GM1 distribution in neuronal membranes. Based on pulling inward and outward tubes, we developed a technique that allowed the direct measurement of the membrane spontaneous curvature. Using vesicle electroporation and fluorescence intensity analysis, we were able to quantify the GM1 asymmetry across the membrane and to subsequently estimate the local curvature generated by the molecule in the bilayer. Molecular-dynamics simulations confirm the experimentally determined dependence of the membrane spontaneous curvature as a function of GM1 asymmetry. GM1 plays a crucial role in connection with receptor proteins. Our results on curvature generation of GM1 point to an additional important role of this ganglioside, namely in shaping neuronal membranes.
IoT devices are being widely deployed. But the huge variance among them in the level of security and requirements for network resources makes it unfeasible to manage IoT networks using a common ...generic policy. One solution to this challenge is to define policies for classes of devices based on device type . In this paper, we present AuDI, a system for quickly and effectively identifying the type of a device in an IoT network by analyzing their network communications. AuDI models the periodic communication traffic of IoT devices using an unsupervised learning method to perform identification. In contrast to prior work, AuDI operates autonomously after initial setup, learning, without human intervention nor labeled data, to identify previously unseen device types. AuDI can identify the type of a device in any mode of operation or stage of lifecycle of the device. Via systematic experiments using 33 off-the-shelf IoT devices, we show that AuDI is effective (98.2% accuracy).
It is crucial for molecular dynamics simulations of biomembranes that the force field parameters give a realistic model of the membrane behavior. In this study, we examined the OPLS3e force field for ...the carbon–hydrogen order parameters S CH of POPC (1-palmitoyl-2-oleoylphosphatidylcholine) lipid bilayers at varying hydration conditions and ion concentrations. The results show that OPLS3e behaves similarly to the CHARMM36 force field and relatively accurately follows the experimentally measured S CH for the lipid headgroup, the glycerol backbone, and the acyl tails. Thus, OPLS3e is a good choice for POPC bilayer simulations under many biologically relevant conditions. The exception are systems with an abundancy of ions, as similarly to most other force fields OPLS3e strongly overestimates the membrane-binding of cations, especially Ca2+. This leads to undesirable positive charge of the membrane surface and drastically lowers the concentration of Ca2+ in the surrounding solvent, which might cause issues in systems sensitive to correct charge distribution profiles across the membrane.
With the rapid growth of the Internet-of-Things (IoT), concerns about the security of IoT devices have become prominent. Several vendors are producing IP-connected devices for home and small office ...networks that often suffer from flawed security designs and implementations. They also tend to lack mechanisms for firmware updates or patches that can help eliminate security vulnerabilities. Securing networks where the presence of such vulnerable devices is given, requires a brownfield approach: applying necessary protection measures within the network so that potentially vulnerable devices can coexist without endangering the security of other devices in the same network. In this paper, we present IoT Sentinel, a system capable of automatically identifying the types of devices being connected to an IoT network and enabling enforcement of rules for constraining the communications of vulnerable devices so as to minimize damage resulting from their compromise. We show that IoT Sentinel is effective in identifying device types and has minimal performance overhead.
Phospholipids are essential building blocks of biological membranes. Despite a vast amount of very accurate experimental data, the atomistic resolution structures sampled by the glycerol backbone and ...choline headgroup in phoshatidylcholine bilayers are not known. Atomistic resolution molecular dynamics simulations have the potential to resolve the structures, and to give an arrestingly intuitive interpretation of the experimental data, but only if the simulations reproduce the data within experimental accuracy. In the present work, we simulated phosphatidylcholine (PC) lipid bilayers with 13 different atomistic models, and compared simulations with NMR experiments in terms of the highly structurally sensitive C–H bond vector order parameters. Focusing on the glycerol backbone and choline headgroups, we showed that the order parameter comparison can be used to judge the atomistic resolution structural accuracy of the models. Accurate models, in turn, allow molecular dynamics simulations to be used as an interpretation tool that translates these NMR data into a dynamic three-dimensional representation of biomolecules in biologically relevant conditions. In addition to lipid bilayers in fully hydrated conditions, we reviewed previous experimental data for dehydrated bilayers and cholesterol-containing bilayers, and interpreted them with simulations. Although none of the existing models reached experimental accuracy, by critically comparing them we were able to distill relevant chemical information: (1) increase of choline order parameters indicates the P–N vector tilting more parallel to the membrane, and (2) cholesterol induces only minor changes to the PC (glycerol backbone) structure. This work has been done as a fully open collaboration, using nmrlipids.blogspot.fi as a communication platform; all the scientific contributions were made publicly on this blog. During the open research process, the repository holding our simulation trajectories and files (https://zenodo.org/collection/user-nmrlipids) has become the most extensive publicly available collection of molecular dynamics simulation trajectories of lipid bilayers.
Phosphatidylserine (PS) is a negatively charged lipid type commonly found in eukaryotic membranes, where it interacts with proteins via nonspecific electrostatic interactions as well as via specific ...binding. Moreover, in the presence of calcium ions, PS lipids can induce membrane fusion and phase separation. Molecular details of these phenomena remain poorly understood, partly because accurate models to interpret the experimental data have not been available. Here we gather a set of previously published experimental NMR data of C–H bond order parameter magnitudes, |S CH|, for pure PS and mixed PS:PC (phosphatidylcholine) lipid bilayers and augment this data set by measuring the signs of S CH in the PS headgroup using S-DROSS solid-state NMR spectroscopy. The augmented data set is then used to assess the accuracy of the PS headgroup structures in, and the cation binding to, PS-containing membranes in the most commonly used classical molecular dynamics (MD) force fields including CHARMM36, Lipid17, MacRog, Slipids, GROMOS-CKP, Berger, and variants. We show large discrepancies between different force fields and that none of them reproduces the NMR data within experimental accuracy. However, the best MD models can detect the most essential differences between PC and PS headgroup structures. The cation binding affinity is not captured correctly by any of the PS force fieldsan observation that is in line with our previous results for PC lipids. Moreover, the simulated response of the PS headgroup to bound ions can differ from experiments even qualitatively. The collected experimental data set and simulation results will pave the way for development of lipid force fields that correctly describe the biologically relevant negatively charged membranes and their interactions with ions. This work is part of the NMRlipids open collaboration project (nmrlipids.blogspot.fi).
Lateral diffusion plays a crucial role in numerous processes that take place in cell membranes, yet it is quite poorly understood in native membranes characterized by, e.g., domain formation and ...large concentration of proteins. In this article, we use atomistic and coarse-grained simulations to consider how packing of membranes and crowding with proteins affect the lateral dynamics of lipids and membrane proteins. We find that both packing and protein crowding have a profound effect on lateral diffusion, slowing it down. Anomalous diffusion is observed to be an inherent property in both protein-free and protein-rich membranes, and the time scales of anomalous diffusion and the exponent associated with anomalous diffusion are found to strongly depend on packing and crowding. Crowding with proteins also has a striking effect on the decay rate of dynamical correlations associated with lateral single-particle motion, as the transition from anomalous to normal diffusion is found to take place at macroscopic time scales: while in protein-poor conditions normal diffusion is typically observed in hundreds of nanoseconds, in protein-rich conditions the onset of normal diffusion is tens of microseconds, and in the most crowded systems as large as milliseconds. The computational challenge which results from these time scales is not easy to deal with, not even in coarse-grained simulations. We also briefly discuss the physical limits of protein motion. Our results suggest that protein concentration is anything but constant in the plane of cell membranes. Instead, it is strongly dependent on proteins' preference for aggregation.
Molecular dynamics (MD) simulations are widely used to monitor time-resolved motions of biomacromolecules, although it often remains unknown how closely the conformational dynamics correspond to ...those occurring in real life. Here, we used a large set of open-access MD trajectories of phosphatidylcholine (PC) lipid bilayers to benchmark the conformational dynamics in several contemporary MD models (force fields) against nuclear magnetic resonance (NMR) data available in the literature: effective correlation times and spin–lattice relaxation rates. We found none of the tested MD models to fully reproduce the conformational dynamics. That said, the dynamics in CHARMM36 and Slipids are more realistic than in the Amber Lipid14, OPLS-based MacRog, and GROMOS-based Berger force fields, whose sampling of the glycerol backbone conformations is too slow. The performance of CHARMM36 persists when cholesterol is added to the bilayer, and when the hydration level is reduced. However, for conformational dynamics of the PC headgroup, both with and without cholesterol, Slipids provides the most realistic description because CHARMM36 overestimates the relative weight of ∼1 ns processes in the headgroup dynamics. We stress that not a single new simulation was run for the present work. This demonstrates the worth of open-access MD trajectory databanks for the indispensable step of any serious MD study: benchmarking the available force fields. We believe this proof of principle will inspire other novel applications of MD trajectory databanks and thus aid in developing biomolecular MD simulations into a true computational microscopenot only for lipid membranes but for all biomacromolecular systems.
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