Biophysical Journal

A broad range of cellular functions involve transient or persistent changes in the morphology of lipid membranes, from the organellar to the molecular scale. By and large, the thermodynamics of these remodeling processes remain to be understood. Molecular Dynamics simulations enhanced by advanced sampling methods are uniquely suited to examine and quantitate these phenomena. Here, we focus on the cellular process known as mechanosensation and use the Multi-Map simulation method to quantify how applied lateral tension impacts the energetics of both global and localized membrane perturbations induced extrinsically. We also examine how tension impacts the dynamics of lipid molecules. We find that the conformational energetics of the membrane clearly differs when it is stretched, and that this difference increases with the magnitude of the applied tension. The reason is not that tension alters the mechanical properties of the lipid bilayer, such as its bending modulus, but rather that it opposes any reduction in the projected area of the membrane relative to that at rest, while the opposite is favored. It follows that tension may shift a conformational equilibrium of a protein that deforms the membrane differently in alternative functional states, if that difference also entails a change in the projected membrane area. Conversely, we find that stretch has little to no effect on the dynamics of lipids at the single-molecule level, implying it would also have no bearing on the lifetime of specific protein-lipid interactions. Finally, we show how changes in lipid composition that result in global membrane thinning can mimic the effect of lateral stretch without any applied tension. Statement of SignificanceCells have evolved the ability to sense mechanical forces, such as pressure or stretch, through specialized proteins embedded in their membranes. How exactly the membrane transduces these stimuli to the proteins therein has been unclear. Using state-of-the-art computer simulations, we show that stretching a membrane does not result in forces that pull or push on the individual lipid molecules that constitute the membrane. Instead, lateral tension alters the energetics of reshaping the membrane. This shift in plasticity explains why several well-known force-sensing proteins switch between active and inactive states at specific tension values observed experimentally. We also show that altering the lipid composition of the membrane can produce the same effect as lateral stretch, without any applied force.

Fluorescence recovery after photobleaching (FRAP) is widely used to characterize diffusion in cells, but quantitative interpretation of the data in small prokaryotes requires explicitly accounting for cell geometry. While this has been successfully achieved for spherical and rod-shaped bacteria, analytical approaches developed in these cases are not directly applicable to cells with more complex morphologies. Here, we explore the application of FRAP to helical bacteria using simulations. We show that half-compartment FRAP experiments, where one-half of the cell is photobleached, provide a robust means of characterizing fast protein diffusion. To help with the practical implementation of this technique, we established the relationship between the diffusion coefficient and characteristic fluorescence recovery time as a function of cell length and helical parameters, and for two different ways of estimating the recovery time. As a first application, we report measurements of the diffusion coefficient of the fluorescent protein, mNeonGreen, in the helical bacterium Paramagnetospirillum magneticum AMB-1. We find it to be D = 4.9 {+/-} 2.2 {micro}m2 s-1 in isosmotic conditions, not significantly different from the value measured in Escherichia coli. Although developed for helical bacteria, including spirilla, spirochetes, and vibrios, our framework can readily be extended to cells or compartments with other geometries.

Cell plasma membranes exhibit heterogeneous lateral organization whose dynamic compartmentalization is critical for processes such as viral infection and fertilization. While membrane tension is known to influence crucial cell remodeling processes, its role in regulating membrane heterogeneous organization remains unclear. To reveal the effect of tension on lateral membrane organization, we used supported lipid bilayers on flexible substrates. These were prepared by rupturing ternary-composition giant unilamellar vesicles exhibiting liquid order-disorder phase coexistence. The phase coexistence is observed using a fluorescent probe that preferentially partitions to the disordered phase. Using a motorized equibiaxial stretching device, we observed domain morphology homogenization under membrane stretching. We define an order parameter based on the relative concentration of the dye in the two phases, which is a proxy for the membrane lateral organization. Order parameter analysis revealed power-law scaling near the critical strain with an exponent {beta} = 1.0 {+/-} 0.3, consistent with an elastic theoretical model predicting {beta} = 1. The progressive broadening of the interfacial region width near the critical strain, and continuous transition to a homogeneous phase, is consistent with a second-order phase transition. These findings indicate that membrane tension may serve as a physical regulator of lateral lipid organization, with implications for how cells use mechanical forces to regulate their structure and function.

1Long QT syndrome Type 2 (LQT2) is a genetic disorder caused by missense mutations in the KCNH2 gene that encodes the potassium channel KV11.1. Previous studies have shown that most KV11.1 missense mutations with loss-of-function phenotypes result from impaired trafficking from the endoplasmic reticulum to the plasma membrane. To investigate the molecular basis of these defects, we used molecular dynamics simulations to analyze two sets of disease-associated missense mutations: those that suppress and those that maintain normal channel trafficking. We focused initially on the conformational and dynamics differences between wild-type and several mutants of KV11.1 via molecular dynamics simulations when two K+ were placed in the selectivity filter (SF). Our study reveals that missense mutations in the S4 helix allosterically disrupt the selectivity filter, a critical determinant for proper channel trafficking. Trafficking-competent variants largely retained a wild-type selectivity filter structure, whereas trafficking-deficient mutants exhibited pronounced structural perturbations in this region. These findings suggest that certain LQT2-associated missense mutations in KCNH2 impair channel trafficking by compromising the structural integrity of the selectivity filter. We additionally found that second-site variants Y652C in the drug binding vestibule can correct structural defects associated with some mistrafficking variants.

Model asymmetric lipid bilayers provide a powerful platform for probing how lateral phase behavior in one leaflet is coupled to that of the opposing leaflet. Here, we use calcium-induced hemifusion to generate asymmetric giant unilamellar vesicles (aGUVs) and investigate how lipid composition modulates interleaflet coupling of liquid-liquid phase separation. Symmetric GUVs composed of cholesterol, the high-melting lipid DPPC, and a low-melting phosphatidylcholine (either 14:1-PC or 16:1-PC) were prepared at compositions exhibiting coexisting liquid-ordered (Lo) and liquid-disordered (Ld) phases. Hemifusion with a uniformly mixed supported lipid bilayer composed of the low-melting lipid and cholesterol selectively altered the outer leaflet composition, producing aGUVs with controlled but variable asymmetry. Quantification of outer leaflet exchange using both probe-exit and probe-entry fluorescence measurements revealed substantial vesicle-to-vesicle variability within a given preparation, resulting in overlapping populations of phase-separated and uniformly mixed aGUVs. To account for this variability, we developed a population-based, coupled-distributions framework that enables robust determination of the asymmetric miscibility boundary, defined as the outer leaflet composition at which macroscopic phase separation is suppressed. Independent analyses of probe-exit and probe-entry data yielded consistent boundary locations. Comparing the two lipid systems, we find that aGUVs containing 14:1-PC require significantly greater outer leaflet exchange to abolish phase separation than those containing 16:1-PC. Only in the 14:1-PC system do we observe vesicles exhibiting coexistence of distinct anti-registered phases, a theoretically predicted but rarely observed regime consistent with large hydrophobic mismatch. By expressing both symmetric and asymmetric miscibility boundaries in a common fractional-coordinate framework, we introduce a phenomenological parameter, {Delta}*, that quantifies the direction and strength of interleaflet coupling of phase behavior. Together, these results demonstrate that modest changes in lipid chain length can markedly alter asymmetric miscibility boundaries and provide a quantitative link between experimental observations, leaflet dominance concepts, and coupled-leaflet theories of membrane organization. Statement of SignificanceMembrane asymmetry is a defining feature of eukaryotic cells whose influence on lateral membrane organization remains unclear. Using asymmetric giant vesicles, we find that coexisting liquid-ordered and liquid-disordered domains transition to a uniform appearance as saturated lipid in the outer leaflet is replaced with unsaturated lipid. The extent of exchange required to disrupt phase separation increased with acyl-chain length mismatch, revealing a compositional dependence of interleaflet coupling. In mixtures with greater hydrophobic mismatch, we also observe coexisting anti-registered phases predicted by theory but rarely observed experimentally, providing new constraints for models of coupled-leaflet behavior. By accounting for vesicle-to-vesicle compositional variability, these results provide a framework for measuring asymmetric miscibility boundaries and for connecting asymmetric membrane organization to lipid raft phenomena.

Membrane mimetics such as lipid bicelles and nanodiscs have become indispensable platforms for high-resolution structural, dynamical, and functional studies of membrane-associated systems by NMR spectroscopy, cryo-electron microscopy, and X-ray crystallography. In particular, magnetically aligned bicelles and nanodiscs uniquely enable the measurement of anisotropic NMR interactions, providing direct access to membrane geometry, lipid order, thickness, and molecular dynamics. However, the quantitative interpretation of such anisotropic NMR spectra has been hindered by the absence of physically rigorous dynamic models that properly account for the coupled effects of molecular diffusion, orientational distribution, and membrane deformation. Here, we present a comprehensive theoretical framework for the dynamic simulation of 31P chemical shift anisotropy and 14N quadrupolar NMR lineshapes in bicelles and nanodiscs. The model explicitly incorporates lipid diffusion, orientational distributions on curved membrane geometries, and membrane thinning, enabling physically consistent and quantitatively accurate reproduction of experimentally observed anisotropic lineshapes. Using this framework, we simulate dynamic 31P and 14N NMR spectra of DMPC/DHPC bicelles and nanodiscs and demonstrate how membrane thinning and lipid diffusion govern the apparent reduction of anisotropic interactions commonly observed upon peptide or protein association. This approach establishes a general physical basis for interpreting anisotropic NMR spectra of aligned membrane mimetics and provides a unified platform for quantitative investigation of membrane structure, dynamics, and membrane-active biomolecular interactions.

The transbilayer distribution of plasma membrane cholesterol remains uncertain despite repeated analysis. We propose a new mechanism driving cholesterol sidedness: sterols form simple stoichiometric associations with phospholipids. Our model postulates that the phospholipids in the plasma membrane bilayer are fully complexed with cholesterol. The cholesterol in each leaflet is then the product of the abundance of its phospholipid and its sterol stoichiometry. Notably, lipid affinities are not relevant. Applying literature values for the composition, abundance and sterol stoichiometry of the phospholipid in each leaflet, the model predicts that two-thirds of the cholesterol in the human erythrocyte membrane bilayer is located in its outer leaflet, an exofacial to endofacial ratio of 2:1. The model also predicts that the overall cholesterol content of the bilayer is [~]0.75 mole/mole phospholipid, in agreement with literature values. Furthermore, our analysis suggests that the areas of the two membrane leaflets are about the same. The concordance of prediction with observation validates the model and the values used for the parameters. The sterol in the exofacial leaflet of the plasma membrane of any cell is predicted to exceed that on its contralateral side when its phospholipids have a higher sterol stoichiometry and are fully complexed. SynopsisWe propose that the transbilayer distribution of cholesterol in the plasma membrane bilayer is determined by its complexation with the phospholipids in the two leaflets. Because the complexes are homeostatically filled to stoichiometric equivalence, leaflet cholesterol is given by the abundance of its phospholipids multiplied by its sterol stoichiometry. The model predicts that two-thirds of the cholesterol in the human erythrocyte membrane bilayer resides in the outer leaflet. It also predicts the cholesterol content of the bilayer as a whole.

Molecular dynamics (MD) simulations have yielded important insights into ion conduction in potassium channels, but quantitative comparison with electrophysiological experiments remains challenging. Due to their high computational cost, MD simulations are typically performed at membrane potentials well above physiological values, and at only a limited number of voltages. Since current-voltage relationships are not necessarily linear, this limits direct comparison between simulations and experiments. Here, we introduce a method to estimate the current-voltage characteristics of ion channels from Markov state models (MSMs) constructed from MD simulations performed at only a few membrane potentials. Time-discrete MSMs of ion conduction are converted into continuous-time rate matrices, whose voltage dependence is modelled using a rate theory formulation with free energy barriers depending on membrane potential. This approach enables the prediction of channel currents over a wide voltage range without additional simulations. We validated the method using MD simulations of the potassium channels KcsA and MthK. In both cases, the currents predicted at low membrane potentials are in good agreement with those obtained directly from MD simulations, demonstrating the robustness and efficiency of the approach.

We develop a self-consistent free-energy framework in which membrane shape and osmotic pressure are determined simultaneously in a finite reservoir by minimizing bending elasticity and solute entropy. Solute conservation makes osmotic pressure a thermodynamic variable rather than an externally prescribed parameter, producing a nonlinear coupling between membrane mechanics and solvent entropy. This coupling modifies the classical stability condition for spherical vesicles: instability emerges from global free-energy competition rather than the linear Helfrich stability criterion. The resulting critical pressures differ by orders of magnitude from Helfrich predictions and agree with simulations for small and large unilamellar vesicles. The framework is relevant to cellular environments involving biomolecular condensate confinement as well as synthetic vesicles and the development of osmotic-pressure-driven encapsulation platforms.

Molecular crowding causes the compaction of chromatin fibers, contributing to the formation of the nuclear architecture. However, the molecular mechanism of compaction under crowded conditions is not yet fully understood. In this study, we employed the single-molecule optical tweezer method to investigate the effect of molecular crowding on chromatin structure. Force-extension experiments on a 12-mer polynucleosome in the presence of different sizes and concentrations of polyethylene glycol (PEG) as a crowding agent showed that at low concentrations of low-molecular-weight (MW) PEG, the compaction of the polynucleosome was not significant. In this respect, nucleosomes predominantly remained separated, while DNA-histone interactions within individual nucleosomes were slightly stabilized. In contrast, high concentrations of high-MW PEG significantly promote internucleosomal interactions, leading to highly compact polynucleosome conformations. Under these conditions, approximately 30 pN of force was required to disrupt the internucleosomal interactions and release DNA; this force was 36% higher than that required for DNA unwrapping in the absence of PEG. These findings suggest that molecular crowding impacts cellular processes by mechanically regulating chromatin accessibility for regulatory proteins and the passage of motor molecules such as RNA polymerase. Significance StatementChromatin condensation is closely related to biological processes such as transcription and replication. Molecular crowding has recently attracted attention as a factor regulating chromatin condensation. In this study, we used the optical tweezer method to analyze the molecular mechanisms underlying chromatin condensation. We found that high-molecular weight and high-concentration crowders (polyethylene glycol) induced significant compaction, which involved internucleosomal interactions that markedly reduced DNA accessibility. Our results suggest that molecular crowding not only alters the condensation state, but also mechanically regulates chromatin accessibility.

Optical coherence tomography (OCT) has allowed in vivo recording of sound-induced vibrations of different regions within the organ of Corti complex (OCC), including the basilar membrane (BM), outer hair cell/Deiters cell (OHC/DC) region, and reticular lamina (RL). In the hook region of the gerbil cochlea, where measurements can be made with a substantially transverse optical axis, the three regions have different and characteristic motion responses: The OHC/DC region has greater motions than the other two regions at frequencies below the best frequency (sub-BF); the RL region typically has the greatest BF peak and smallest sub-BF motion. The phase of the OHC/DC-region motion increasingly lags BM motion phase as frequency increases; the RL-region motion phase leads BM, but with a relatively small value. All three regions are compressively nonlinear in the BF peak, but only the OHC/DC region shows sub-BF compressive nonlinearity. In this paper, we describe the strain that exists within the RL and OHC-body regions. These strains are large where the motion varies over short distances, and a region of large strain can be as short as a single 2.7 {micro}m measurement pixel, or extend over several pixels, with the extensive strains appearing more often at 70 than at 50 dB SPL. Beyond the region of large strain, over a distance that can exceed 20 m, the OHC/DC region displays nearly unvarying motion spatially -- this region appears to vibrate as a body. Statement of SignificanceThe sensory tissue of the cochlea responds actively to a sound stimulus: cell-based forces amplify and enhance the vibration of the sensory tissue. Measurements employing optical coherence tomography have identified major vibration patterns along a sensory-tissue-spanning line that includes the active outer hair cells. In this article, we describe the transitional motion between these major vibration regions and the motion strains that exist as vibration morphs from one region to the next. The findings are presented in frequency response curves to convey the frequency tuning and its stimulus-level dependence, and in one-dimensional heat maps to convey the extent of regional motions and strains. These findings fuel and constrain conceptual and physics-based models of cochlear amplification.

Protein condensates that form via phase separation typically become more viscous over time and can harden in a process referred to as "molecular aging". Several mechanisms have been identified for this phenomenon. Of these, the ones involving enhanced {beta}-sheet or -strand interactions are of pathological relevance since they have been associated with neurodegeneration. Although there is much understanding of biopolymer phase behavior, an inclusive thermodynamic framework that unifies phase separation and {beta}-sheet-based aging is lacking. We present a time-dependent, multi-component extension of associating polymer theory that describes phase separation and aging of an intrinsically disordered protein (IDP) capable of associating through local, reversible folding. The model shows how the Second Law of Thermodynamics applies throughout, whether phase separation precedes and encourages aging or, vice versa, whether the increase in "stickiness" during aging drives phase separation. Our calculations show how the time-dependence of the average valency of associating sites determines the aging kinetics and the development of viscoelastic properties of a biocondensate. The agreement between our calculations and the change in dynamics of condensates of perfect repeat analogues of nucleoporin-98 not only validates the theory but also identifies these Nup98 variants as model systems for studying aging.

The synaptic cleft between neighboring neurons is the site of neurotransmitter-mediated communication that underlies normal brain function, including learning and memory. When an action potential reaches the presynaptic terminal, released neurotransmitters cross the cleft under the combined influence of diffusion and electrical forces to activate postsynaptic receptors. Despite this, synaptic-cleft transport is commonly modeled using a pure diffusion model, neglecting electrical drift. Here, we quantify the relative contributions of diffusion and electrical terms in the Poisson-Nernst-Planck (PNP) framework and assess whether the pure diffusion approximation is adequate. We solve the full PNP system in a three-dimensional computational model of the synaptic cleft at nanometer-scale resolution, tracking five ionic species (Na+, K+, Ca2+, Cl-, Glu-) with full spatial and temporal detail. Solutions are compared directly with those of the pure diffusion (D) model. The D and PNP models produce markedly different ionic concentration fields. Analysis of ionic fluxes confirms that diffusive and electrical contributions are of comparable magnitude across all species. These discrepancies are robust across parameter variations, including the number of AMPA receptors, the amount of released glutamate, the cleft height, and the cleft diffusion coefficient, and are amplified as the number of AMPA receptors increases, the cleft becomes narrower or diffusion more restricted. The quantitative and qualitative differences between the pure D model and the full PNP model demonstrate that neglecting electrical forces in the synaptic cleft has consequences. These discrepancies are large enough to alter the predicted dynamics and biological interpretation of synaptic transmission, establishing that accurate computation of ionic concentrations in the synaptic cleft requires the full PNP equations.

Disordered proteins can form biomolecular condensates by demixing from their environment, enabling reversible compartmentalisation of cellular components in the form of membraneless organelles. Multivalent interactions are essential for this type of phase separation behaviour, and for disordered proteins, the potential for multivalent interactions is encoded in the sequence composition and patterning. Mutational studies have been instrumental in helping elucidate this sequence grammar by perturbing the amino acid sequence and quantifying the resulting changes in the driving force for phase separation. While such studies have provided a detailed and predictive understanding of the driving forces for phase separation, they strictly do not inform on the nature of the interactions that drive phase separation. Here, we propose using double mutant cycles to explore molecular interactions and their contributions to condensate properties more directly. We explore the applicability of double mutant cycles for different types of interactions in condensates formed by the low-complexity domain of hnRNPA1 using coarse-grained molecular dynamics simulations. We find that the interactions between arginine and tyrosine residues, as well as between aromatic residues, contribute mostly additively to the propensity for phase separation. However, for the interactions between charged residues, we find that--in an interplay with the net charge of the protein--there is a measurable non-additive contribution to the phase separation propensity. Based on our results, we envisage that double mutant cycles could provide additional insights into protein phase separation, thus expanding the understanding of the sequence grammar and the underlying molecular interactions.

Biomolecular condensates formed by complex coacervation of highly charged proteins provide a powerful framework to understand how microscopic interactions give rise to macroscopic material properties. Atomistic molecular dynamics simulations provide detailed insights but remain limited in accesing the spatio-temporal scales relevant for condensate behavior. Here, we use the residue-level coarse-grained Mpipi-Recharged model to investigate condensates formed by ProT and positively charged partners, including histone H1, protamine, poly-lysine, and poly-arginine. Material properties, in this context, provide a stringent experimental benchamark for coarse-grained models. Our model reproduces salt-dependent phase behavior, protein binding affinities, and sequence-specific stability trends in agreement with in vitro experiments, despite the fact that material properties were not included in the model parametrization. We then establish a direct link between protein dynamics and macroscopic material properties by quantifying monomeric diffusion, conformational reconfiguration, and translational mobility within the dense phase, and relating these to condensate viscosity. By comparing dynamics across dense and dilute phases, we uncover a pronounced length scale-dependent behavior. While residue-level binding and unbinding events remain equally fast in both phases, protein reconfiguration time and self-diffusion are significantly slowed down within the condensates. This decoupling reveals how fast intermolecular interactions coexist with slow mesoscale condensate dynamics depending on the molecular length scale. Together, our results establish a predictive framework that links encoded sequence intermolecular forces and multiscale dynamics to the emergent material properties of complex biomolecular condensates.

The apparent pKa of ionizable lipids in lipid nanoparticles (LNPs) is a key determinant of RNA encapsulation during formulation and endosomal release after cellular uptake. However, it is difficult to predict the effective pKa of a given ionizable lipid solely from its solution pKa, because it is sensitive to the membranes composition, as well as solution conditions such as the salt concentration. We developed a simple continuum electrostatics model, based on Gouy-Chapman theory, to predict the shift in effective pKa for ionizable lipids in lipid bilayers as a function of salt concentration and membrane composition. We derive equations for the surface potential and fraction of lipids charged, which are solved self-consistently as a function of solution pH to extract the titration curve and effective pKa. The model shows that the shift in effective pKa is largest when the concentration of titratable lipid is high, and the effect is diminished by increasing salt concentration. We provide a python implementation of the model and an interactive notebook that will allow users to further easily explore the predicted pKa shifts as a function of formulation variables.

The NBAR-domain containing protein endophilin, as a major player in many endocytic pathways, has offered considerable insight into BAR-domain driven membrane remodeling. However, understanding the interaction of the different subdomains of endophilin and their abilities to sense and generate negative Gaussian curvature are yet unanswered questions, with significant implications for the mechanisms and regulation of unconventional endocytic pathways. Using coarse-grained molecular dynamics simulation, we demonstrate the synergistic remodeling capabilities of the NBAR remodeling unit, as well as its ability to sort to and generate membrane regions with negative Gaussian curvature. We find that the assembly of NBAR scaffolds at regions of negative Gaussian curvature facilitate membrane hemifission in dynamic bud formation. These insights provide an additional role for endophilin scaffolds in endocytosis, as well as emphasizing the importance of developing new ways to study negative Gaussian curvature. STATEMENT OF SIGNIFICANCEThis work provides deeper insight into the composite membrane remodeling abilities of NBAR domains in peripheral membrane proteins and their sorting to negative Gaussian curvature. Theis work also explicitly models at the molecular level the {Omega}-shaped membrane geometry, connecting endophilin mechanics to its physiological function in endocytosis.

Phagocytosis is a fundamental process of the innate immune system, yet the physical determinants that govern the engulfment of soft, deformable targets remain poorly understood. Existing theoretical models typically approximate targets as rigid particles, overlooking the fact that both immune cells and many biological targets undergo significant membrane deformation during contact. Here, we develop a Monte Carlo-based membrane simulation framework to model the interactions of multiple vesicles, enabling us to explore phagocytosis-like processes in systems where both the phagocyte and the target possess flexible, thermally fluctuating membranes. We first validate our approach against established observations for the engulfment of rigid objects. We then investigate how the mechanical properties of a soft target--specifically membrane bending rigidity govern the outcome of phagocytic interactions. Our simulations reveal three distinct mechanical regimes: (i) biting or trogocytosis, in which the phagocyte extracts a portion of the target vesicle; (ii) pushing, where the target is displaced rather than engulfed; and (iii) full engulfment, in which the target is completely internalized. Increasing membrane tension via internal pressure produces analogous transitions, demonstrating a unified mechanical origin for these behaviours. Qualitative comparison with experiments involving Giant Unilamellar Vesicles (GUVs, deformable microparticles) and lymphoma cells supports the relevance of these regimes to biological phagocytosis. Together, these results highlight how target deformability fundamentally shapes phagocytic success and suggest that immune cells may exploit mechanical cues to recognize among different classes of soft targets. Significance statementPhagocytosis is essential for immune defence, yet the physical principles governing the engulfment of soft, deformable targets remain poorly understood. Most theoretical models assume rigid particles, even though real cells undergo substantial shape changes during contact. Here, we develop a theoretical membrane model to simulate interactions between multiple vesicles, enabling a mechanistic exploration of phagocytosis of soft targets. We show that target membrane rigidity dictates whether it is fully engulfed, pushed away, or partially bitten. These mechanically driven regimes explain experimental observations of immune cells engaging with both artificial GUVs and lymphoma cells.

DNA-nano/microparticle motors are burnt-bridge Brownian ratchets (BBR) moving on an RNA-modified two-dimensional surface driven by Ribonuclease H (RNase H), and are one of the fastest artificial molecular motors. Interestingly, these motors show a maximum speed of [~]30 nm s-{superscript 1} irrespective of the particle size ranging from 100 to 5000 nm, whereas the run-length increases with the particle size. Here we performed geometry-based kinetic simulations of DNA-nano/microparticle motors with the sizes of 100, 500, 1000, and 5000 nm to identify the factors governing speed, run-length, and unidirectionality. The simulations reproduced the experiments quantitatively, and the speed remained constant while the run-length and the unidirectionality increased with the particle size. The constant speed was caused by a trade-off between the step size and the pause length, both of which increased with the particle size. In contrast, the run-length and the unidirectionality increased with the particle size because large particles had high multivalency which suppresses stochastic detachment of the motor, high RNA hydrolysis efficiency under the motor trajectory which realizes almost perfect BBR motion, and stepping direction highly biased to forward. For the smaller motors with 100, 500, and 1000 nm particles, the speed increased from 20 to 200 nm s-{superscript 1} by 10-fold increases in DNA/RNA hybridization, RNase H binding, and RNA hydrolysis rates (from 0.8 to 8.0, 7.2 to 72, and 3.0 to 30 s-{superscript 1}, respectively), even when considering the rotational diffusion of these particles. On the other hand, the speed for the largest motor with 5000 nm particle was limited to 100 nm s-{superscript 1}, because the time required for rolling motion ([~]0.3 s) became comparable to the pause length. Our results indicate that DNA-particle motors must possess a nanoscale body to achieve a speed exceeding 100 nm s-{superscript 1}. SignificanceAutonomous artificial molecular motors have a potential to power nano- and micron-scale actuators and devices, but their performances such as speed, run-length, and unidirectionality are inferior to natural motor proteins. Using geometry-based kinetic simulations, we quantitatively analyzed performance metrics of artificial DNA-nano/microparticle motors which autonomously move on RNA-modified two-dimensional surfaces by a burnt-bridge Brownian ratchet mechanism. Our study revealed the mechanism why their speed is almost independent of the particle size, while the run-length and unidirectionality increases with the particle size. We also identified how multivalent binding, mode of detachment, and rotational diffusion set fundamental limits of the speed, run-length, and unidirectionality. Our results provide a general design strategy for engineering high-performance artificial molecular motors.

-Synuclein (Syn) remodels cellular membranes through interactions that involve both its structured, membrane-binding N-terminal domain (NTD) and intrinsically disordered C-terminal domain (CTD). While the amphipathic NTD helix is known to insert into lipid bilayers and generate curvature, the contribution of the acidic CTD remains unclear. Here, we dissect the individual and cooperative roles of these domains using Supported Bilayers with Excess Membrane Reservoir (SUPER) templates to quantify membrane remodeling via membrane fission and membrane morphological deformations (i.e., membrane budding and tubulation). We show that both the NTD and CTD independently remodel membranes, while full-length Syn exhibits greater remodeling ability than either the NTD or CTD in isolation. This result demonstrates a synergistic amplification between helix insertion of the NTD and the tethered, disordered CTD. To further probe the mechanism of membrane remodeling by the CTD, we modulated the chain length of the protein, the bulk ionic strength of the solution (i.e., charge screening), and applied relevant polymer scaling laws for disordered proteins. Our results suggest that the membrane remodeling mechanism for the disordered CTD is electrostatic in nature, stemming from protein-protein repulsion at elevated binding densities. Together, our findings reveal a cooperative energetic mechanism in which N-terminal helix insertion biases membrane curvature and the disordered, C-terminal domain adds an additional electrostatic component that helps to overcome the free energy barrier for membrane bending.