Diffusion of Lipids and Proteins in Complex Membranes

Integral membrane proteins are tiny factories with big responsibilities in signaling and transport. These proteins are constantly looking for oligomerization partners and favorable lipid environments to perform their functions that are critical for our health. The search processes are driven by thermally-agitated lateral diffusion. Cellular membranes are crowded and highly heterogeneous entities. Their structure is assumed to couple to the dynamics of molecules within the membrane, rendering diffusion therein complex too. Clarifying this connection can help us to grasp how cells regulate dynamic processes by locally varying their membrane properties, and how this further affects protein function. Unfortunately, despite persistent experimental work, our understanding of this structure–dynamics–function coupling remains poor.In this Thesis, we present our findings on how protein crowding and lipid packing affect the lateral dynamics of lipids and proteins in membranes and monolayers. We have employed molecular dynamics simulations using both atomistic and coarsegrained models to resolve how the rate and nature of diffusion are affected by these two factors. We also advanced the related methodology, which turned out to be beneficial for studying lipid membranes that are crowded with proteins.We find that crowding and packing slow down lipid and protein diffusion and extend the anomalous diffusion regime. We demonstrate that models used to predict diffusion coefficients of lipids and proteins struggle in such conditions. Finally, we observe that protein crowding effects non-Gaussian diffusion that does not follow the diffusion mechanism observed for protein-free bilayers, nor any other known mechanism.Our observations help us understand the dynamics in crowded membranes, and hence shed light on the kinetics of numerous membrane-mediated phenomena. The findings suggest that normal diffusion is likely absent in the membranes of living cells, where the motion of each lipid and protein is heavily affected by its heterogeneous surroundings. The results also pave the way towards understanding central processes in the utterly complex plasma membranes of living cells. Here, the possible future applications lie in pharmaceuticals that affect protein function by disturbing the formation of functional protein–protein or protein–lipid units by perturbing the dynamic properties of the membranes and monolayers

Thermodynamics of a multicomponent-atom sample in a tightly compressed atom trap

We use classical statistical mechanics and thermodynamics to describe the response of a trapped multi-species atomic sample to a local deformation in the confining potential. An adiabatic deformation may not only increase the peak phase-space density, but also lower the temperature and spin-polarize the atoms.Peer reviewe

Spin-degenerate two-level atoms in on-resonance partially polarized light

We present a theoretical model describing the magnetic-state population dynamics of spin-degenerate two-level atoms interacting with a narrowband, on-resonance, partially polarized electromagnetic field. The field is allowed to have three uncorrelated orthogonal vector components. The model is applied to a four-magnetic-state atom system with a single excited and three ground states. Even if the field is narrowband, the population dynamics may be completely predicated by the fluctuating polarization of light. In our examples, the fluctuation effects are mainly governed by a single parameter, the degree of polarization of the field.Peer reviewe

Collision effects in velocity-selective optical pumping of sodium

We report on a quantitative experimental investigation of velocity-changing collisions by means of velocity-selective optical pumping (VSOP). We have calculated the VSOP line shape for an atom with hyperfine structure with the use of two phenomenological kernels for the collision effects: the Keilson-Storer kernel, and a two-term kernel consisting of a broad Keilson-Storer part and a narrower Gaussian component. Corrections were included to account for the finite absorption in the sample and the backward reflection of the pumping beam. The experiments were carried out in sodium vapor with neon as the perturber gas. The D1 line of sodium was used for optical pumping, and the orientation of the ground state was detected. Free parameters of the theory were determined by fitting the predicted line shapes to experimental curves. The Keilson-Storer kernel proved unsatisfactory, but the two-term kernel reproduced well the observed line shapes over the entire collision profiles in the neon pressure range 0-57 mtorr. In an independent experiment using rapidly modulated VSOP we also measured directly the cross section of velocity-changing collisions: σ=(1.13±0.10)×10exp−14 cm2. The large weight obtained for the narrow Gaussian from the fits, as well as the collision cross section which is three times as large as the cross section deduced from tabulated gas kinetic radii, may indicate the presence of collisions with relatively small velocity changes in addition to hard-sphere encounters.Peer reviewe

Nanoscale Membrane Domain Formation Driven by Cholesterol

Biological membranes generate specific functions through compartmentalized regions such as cholesterol-enriched membrane nanodomains that host selected proteins. Despite the biological significance of nanodomains, details on their structure remain elusive. They cannot be observed via microscopic experimental techniques due to their small size, yet there is also a lack of atomistic simulation models able to describe spontaneous nanodomain formation in sufficiently simple but biologically relevant complex membranes. Here we use atomistic simulations to consider a binary mixture of saturated dipalmitoylphosphatidylcholine and cholesterol - the "minimal standard" for nanodomain formation. The simulations reveal how cholesterol drives the formation of fluid cholesterol-rich nanodomains hosting hexagonally packed cholesterol-poor lipid nanoclusters, both of which show registration between the membrane leaflets. The complex nanodomain substructure forms when cholesterol positions itself in the domain boundary region. Here cholesterol can also readily flip-flop across the membrane. Most importantly, replacing cholesterol with a sterol characterized by a less asymmetric ring region impairs the emergence of nanodomains. The model considered explains a plethora of controversial experimental results and provides an excellent basis for further computational studies on nanodomains. Furthermore, the results highlight the role of cholesterol as a key player in the modulation of nanodomains for membrane protein function.Peer reviewe

Excessive aggregation of membrane proteins in the Martini model

The coarse-grained Martini model is employed extensively to study membrane protein oligomerization. While this approach is exceptionally promising given its computational efficiency, it is alarming that a significant fraction of these studies demonstrate unrealistic protein clusters, whose formation is essentially an irreversible process. This suggests that the protein-protein interactions are exaggerated in the Martini model. If this held true, then it would limit the applicability of Martini to study multi-protein complexes, as the rapidly clustering proteins would not be able to properly sample the correct dimerization conformations. In this work we first demonstrate the excessive protein aggregation by comparing the dimerization free energies of helical transmembrane peptides obtained with the Martini model to those determined from FRET experiments. Second, we show that the predictions provided by the Martini model for the structures of transmembrane domain dimers are in poor agreement with the corresponding structures resolved using NMR. Next, we demonstrate that the first issue can be overcome by slightly scaling down the Martini protein-protein interactions in a manner, which does not interfere with the other Martini interaction parameters. By preventing excessive, irreversible, and non-selective aggregation of membrane proteins, this approach renders the consideration of lateral dynamics and protein-lipid interactions in crowded membranes by the Martini model more realistic. However, this adjusted model does not lead to an improvement in the predicted dimer structures. This implicates that the poor agreement between the Martini model and NMR structures cannot be cured by simply uniformly reducing the interactions between all protein beads. Instead, a careful amino-acid specific adjustment of the protein-protein interactions is likely required.Peer reviewe

Accurate Simulations of Lipid Monolayers Require a Water Model with Correct Surface Tension

Lipid monolayers provide our lungs and eyes their functionality and serve as proxy systems in biomembrane research. Therefore, lipid monolayers have been studied intensively including using molecular dynamics simulations, which are able to probe their lateral structure and interactions with, e.g., pharmaceuticals or nanoparticles. However, such simulations have struggled in describing the forces at the air-water interface. Particularly, the surface tension of water and long-range van der Waals interactions have been considered critical, but their importance in monolayer simulations has been evaluated only separately. Here, we combine the recent C36/LJ-PME lipid force field that includes long-range van der Waals forces with water models that reproduce experimental surface tensions to elucidate the importance of these contributions in monolayer simulations. Our results suggest that a water model with correct surface tension is necessary to reproduce experimental surface pressure-area isotherms and monolayer phase behavior. The latter includes the liquid expanded and liquid condensed phases, their coexistence, and the opening of pores at the correct area per lipid upon expansion. Despite these improvements of the C36/LJ-PME with certain water models, the standard cutoff-based CHARMM36 lipid model with the 4-point OPC water model still provides the best agreement with experiments. Our results emphasize the importance of using high-quality water models in applications and parameter development in molecular dynamics simulations of biomolecules.Peer reviewe

The Devil Is in the Details : What Do We Really Track in Single-Particle Tracking Experiments of Diffusion in Biological Membranes?

Single-particle tracking (SPT) is an experimental technique that allows one to follow the dynamics of individual molecules in biological membranes with unprecedented precision. Given the importance of lipid and membrane protein diffusion in the formation of nanoscale functional complexes, it is critical to understand what exactly is measured in SPT experiments. To clarify this issue, we employed nanoscale computer simulations designed to match SPT experiments that exploit streptavidin-functionalized Au nanoparticles (AuNPs). The results show that lipid labeling interferes critically with the diffusion process; thus, the diffusion measured in SPT is a far more complex process than what has been assumed. It turns out that the influence of AuNP-based labels on the dynamics of probe lipids includes not only the AuNP-induced viscous drag that is the more significant the larger the NP but, more importantly, also the effects related to the interactions of the streptavidin linker with membrane lipids. Due to these effects, the probe lipid moves in a concerted manner as a complex with the linker protein and numerous unlabeled lipids, which can slow down the motion of the probe by almost an order of magnitude. Furthermore, our simulations show that nonlinker streptavidin tetramers on the AuNP surface are able to interact with the membrane lipids, which could potentially lead to multivalent labeling of the NPs by the probe lipids. Our results further demonstrate that in the submicrosecond time domain the motion of the probe lipid is uncorrelated with the motion of the AuNP, showing that there is a 1 mu s limit for the temporal resolution of the SPT technique. However, this limit for the temporal resolution depends on the nanoparticle size and increases rapidly with growing AuNPs. Overall, the results provide a molecular-scale framework to accurately interpret SPT data and to design protocols that minimize label-induced artifacts.Peer reviewe