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.

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.

Heterotrimeric G proteins are key signal transducers in all eukaryotic cells. They are responsible for unification and amplification of perceived extracellular chemical and physical stimuli. Heterotrimeric G proteins are peripheral membrane proteins attached to the inner leaflet of the plasma membrane. Despite numerous available studies, many biophysical aspects regulating G protein signaling, including mobility in the membrane, are insufficiently understood. Here, using single-molecule imaging, we show that different subtypes of heterotrimeric G proteins show high diversity in their mobility in the membrane. We demonstrate that the nature of the G subunit defines the mobility of a heterotrimer. Our results indicate that heterotrimers containing G12 and G13 subunits have remarkably reduced mobility compared to those with Gi/o, Gs, and Gq subunits. These findings identify subtype-specific lateral membrane mobility of G proteins as a factor affecting their signaling dynamics in living cells.

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.

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.

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 plasma membrane is a laterally heterogeneous environment in which lipid organization plays a central role in regulating protein function. In model systems, this heterogeneity is often described in terms of coexisting liquid-ordered (Lo) and liquid-disordered (Ld) phases, commonly associated with the lipid raft concept. Despite extensive experimental and computational efforts, the molecular determinants governing protein partitioning between these domains remain poorly understood, largely due to the limited number of systems studied. Here, we address this challenge using a high-throughput computational approach, systematically analyzing the partitioning behavior of almost 5,000 helical transmembrane peptides in phase-separating lipid membranes. Across all simulations, we find that none of the peptides exhibit a clear preference for the Lo phase, while the vast majority partition into the Ld phase. This observation is consistent with experimental results in simplified membrane systems and suggests that commonly used ternary lipid mixtures may not fully capture the physicochemical environment governing protein sorting in biological membranes. In addition, we identify a subset of peptides that preferentially localize at the Lo/Ld interface. These interfacial peptides display distinct sequence characteristics, indicating that boundary localization is governed by specific combinations of residue composition and spatial arrangement rather than a single dominant feature. Overall, our results reveal that transmembrane helix partitioning in model membranes is dominated by a preference for disordered environments, with interfacial localization emerging as a distinct and potentially functional behavior.

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.

-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.

Although organelles are often studied one at a time, whole-cell imaging studies show that organelles take up a large part of the cell volume such that they are crowded together. Here we use whole cell soft X-ray tomography imaging to investigate how such crowding affects organelle size scaling, position, and shape, focusing on the nucleus and vacuole of budding yeast. We find that as the vacuole becomes larger, the nucleus loses its normal scaling relation with respect to cell volume, becomes displaced from its normal position near the cell center, and becomes progressively deformed from a sphere into a pancake shape. Using a whole-cell integrated modeling framework, we find that these changes are statistically correlated and give rise to distinct modes in cell organization space. Using a simplified mechanical model for two initially spherical compartments contained inside a confined intracellular space, we are able to recapitulate the effects seen in the experimental data, indicating that these observations are consistent with a purely mechanical interaction. Taken together, our work indicates that, in addition to the well-known protein-based organelle-organelle interactions, physical steric packing of organelles inside a limited cellular volume also plays a large role in the inter-organelle relationships and the overall geometry of the cell.

Glycosaminoglycans (GAGs) are extracellular matrix polysaccharides whose sequence variability and chemical modifications, particularly sulfation, generate substantial structural diversity. However, how sulfation patterns and monosaccharide composition encode secondary structure in GAGs is not systematically resolved, and quantitative metrics for classifying these structures are largely lacking. Here, we employ large-scale all-atom molecular dynamics simulations to investigate the molecular origin of secondary structure in sulfated GAGs. We systematically vary sulfation patterns and monosaccharide composition to isolate the factors that promote changes in three-dimensional structure. We show that GAG helical conformations arise from recurrent local shortening motifs caused primarily by stabilization of O_SCPLOWLC_SCPLOW-iduronic acid in the 1C4 puckering conformation, promoted by 2-O-sulfation or by densely sulfated regions. We also introduce a two-parameter structural metric that objectively classifies GAG secondary structures and distinguishes heparin helices from related conformations. Together, our results establish a quantitative link between monosaccharide identity, sulfation pattern, and three-dimensional organization of polysaccharide chains, providing a framework for future studies of sequence-structure relationships in GAGs.

Membrane-proximal (MP) actin represents the subset of cortical f-actin localized within 10 nm of the plasma membrane. Here, we describe a family of single-molecule MP actin (SM-MPAct) probes that diffuse within the plasma membrane and are transiently immobilized through binding to f-actin, enabling the localization of MP actin in both time and space. These probes quantify aspects of MP actin structure, dynamics, and remodeling by analyzing probe positions using a combined single-particle tracking and correlation-function approach. This is demonstrated using chemical and physical perturbations of actin and actin-binding proteins, and by interrogating MP actin organization and dynamics in early B cell receptor (BCR) activation. Upon crosslinking of the IgM BCR, MP actin transiently remodels to increase the size of actin corals, facilitating the efficient assembly of BCR clusters and the local accumulation of MP actin. Notably, analogous remodeling is not detected in measurements using total f-actin probes, indicating that SM-MPAct is uniquely sensitive to the f-actin pool that regulates signaling processes at the plasma membrane. STATEMENT OF SIGNIFICANCEThe actin cortex provides mechanical stability to the plasma membrane and contributes to the organization and dynamics of plasma membrane components. This report presents single-molecule probes and analytical methods to characterize the density, mesh size, motion, and turnover dynamics of the portion of the actin mesh in direct contact with the plasma membrane, enabling quantitative studies of actin remodeling in plasma membrane processes. This general framework is demonstrated through quantification of actin remodeling during early B cell receptor signaling and could be applied to a broad range of cell processes.

Fluorescent reporters such as fluorescent proteins or chemigenetic indicators are indispensable tools for studying biological processes using light microscopy. Choosing an appropriate fluorescent tag is a crucial step in experimental design not only for imaging but also for quantitative measurements such as fluorescence fluctuation spectroscopy. Two key parameters should be considered: Fluorescent brightness and photo-bleaching. Change to fluorescence intensity due to photobleaching is relatively easy to assess in different biological environments, while brightness is more elusive. Here, we develop and employ a fluorescence correlation spectroscopy (FCS) based excitation scan assay that determines fluorescent protein performance and validate it in tissue culture and zebrafish embryos. We employ our FCS pipeline to compare a set of 10 established fluorescent proteins as well as HALO and SNAP tags for both cellular imaging and measurements of diffusion dynamics with FCS. We show that mNeonGreen outperforms mEGFP in tissue culture and zebrafish embryos. We also compare StayGold variants against other green fluorescent proteins and chemigenetic reporters in tissue culture. Overall, we present a broadly applicable approach for determining fluorescent reporter brightness in the living system of interest.

A major challenge in neuroscience is to predict how currents in nanodomains affect voltage and ionic concentrations. Cable and Rall theory provide analytic current-voltage relations by neglecting concentration gradients, and the impact of concentration gradients is usually studied numerically with the Poisson-Nernst-Planck (PNP) model. A precise quantitative understanding of the combined dynamics remains limited because analytic current-voltage-concentration relations are missing. In this work we derive such relations using a novel approach based on cross-diffusion equations. For narrow cylindrical domains, we derive time-dependent and steady-state expressions that explicitly show how currents affect voltage and ionic concentrations. We find that the influx of only one ion can significantly change the concentrations of all the other ions even if no channels for these ions are present. After a current injection we compute a biphasic voltage transient where the small-time asymptotic corresponds to the steady-state solution of the cable equation. We show that the accuracy of cable theory prediction for the voltage depends on how the current is distributed among the various ions. Finally, we develop an iterative method to accurately compute steady-state profiles for voltage and concentrations using first-order results by subdividing a cylinder into small segments.

Cells must maintain stable protein levels despite the inherently stochastic nature of gene expression, as excessive fluctuations can disrupt cellular function and impair the reliability of decision-making. Regulatory mechanisms, such as negative feedback, buffer protein fluctuations. Yet, it remains unclear how fluctuations are affected by delays that depend on a molecules specific state. Here, we develop a stochastic model in which proteins are produced in bursts as inactive molecules and pass through a series of intermediate steps before becoming active. The duration of such activation delays depends on the current level of active protein, creating a state-dependent feedback loop. Our model provides explicit analytical expressions relating the delay structure and feedback strength to the variability of active protein levels, quantified using the Fano factor, and shows that state-dependent delays can reduce fluctuations below the baseline expected from simple bursty production. Stochastic simulations confirm these predictions, and incorporating negative feedback in burst production further decreases variability while keeping system behavior predictable. These results reveal how temporal and state-dependent regulation stabilizes protein expression, offering guidance for understanding natural cellular control and designing robust synthetic gene circuits.

The interactions of droplets and filaments can lead to mutual deformations and complex combined behavior. Such interactions also occur within the cell, where biomolecular condensates, distinct liquid phases often composed of proteins, have been observed to structure and affect the organization of the cytoskeleton. In particular, biomolecular condensates have been shown to undergo characteristic deformations when cytoskeletal filaments are fully embedded within them. However, a full understanding of the underlying physical mechanisms is still missing. Here, we combine experiments with coarse-grained molecular dynamics simulations and analytical models to uncover the physical mechanisms that define emerging shapes of droplets containing filaments. We find that the surface tension of the liquid phase and the bending energy of the filament(s) suffice to accurately capture emerging shapes if the length of the filament is small compared to the liquid volume. As the volume fraction of filament(s) increases, wetting effects become increasingly important, setting physical constraints within which surface and bending energies compete to define the droplet shapes. We find that mutual deformations of condensate and filament extend accessible shapes beyond classical stability considerations, leading to structuring and entrapment of contained filaments. Shape deformations may further affect ripening dynamics that favor certain geometries. Our findings provide a physical framework for a better understanding of the possible roles of biomolecular condensates in cytoskeletal organization.

The nucleotide state and rates of transitions between states regulate the dynamics of ATPases. Slow inorganic phosphate (Pi) release following ATP hydrolysis is often rate-limiting and associated with key conformational changes. Actin filaments offer a unique opportunity to understand the fundamentals of phosphate release, because identical subunits at filament ends and the interior release Pi at markedly different rates. The molecular origin of this difference is debated, so we employed extensive all-atom molecular dynamics simulations to characterize Pi release from different subunits within an actin filament. The dissociation rates of Pi from ADP-Mg2+ in the active site correlate with biochemically measured Pi release rates and scale inversely with the numbers of water molecules in the cavity surrounding the {gamma}-phosphate. Simulations show that egress of Pi through protein channels, including through the N111-R177 backdoor, is not rate-limiting and, importantly, that subunits at the filament ends use alternative egress pathways. TeaserMolecular dynamics simulations show that dissociation of phosphate from Mg2+ limits release from all parts of actin filaments

Interactions between cytosolic biomolecules and the bacterial inner membrane are fundamental to many cellular processes, yet directly measuring their binding kinetics in living cells remains challenging. Conventional two-dimensional single-molecule tracking analyses can be insufficient, particularly when membrane association does not markedly alter the diffusion rate. Here, we present a method to recover membrane interaction kinetics from three-dimensional single-molecule trajectories in rod-shaped bacteria. Using simulated 3D tracking data, we identify membrane-associated motion by quantifying how well short trajectory segments follow the circular curvature of the cell membrane. The resulting measure is further analyzed using a hidden Markov modeling framework, enabling robust discrimination between cytosolic and membrane-bound states and capturing the dynamics of state transitions without requiring diffusion-rate changes or direct colocalization with membrane markers. This work establishes a general framework for extracting membrane interaction kinetics from 3D single-molecule tracking data in live bacteria, and highlights the value of realistic microscopy simulations for quantitative interpretation and systematic bias assessment.

Peptidase-containing ATP-binding cassette transporters (PCATs) couple ATP hydrolysis with proteolytic processing and export of cargo peptides across cellular membranes. Despite their importance in bacterial secretion systems, the molecular determinants governing nucleotide binding and stabilization in PCAT transporters remain incompletely understood. In particular, recent experimental observations suggest that PCAT1 may display altered nucleotide preferences compared with canonical ABC transporters. Here, we employed microsecond-scale all-atom molecular dynamics simulations combined with free energy perturbation (FEP) calculations to characterize nucleotide binding, protein stability, and conformational dynamics of PCAT1 across multiple biochemical conditions. Simulations were performed for inward-facing (IF) and outward-facing (OF) conformations in the presence or absence of Mg2+ and substrate peptides. Structural analyses reveal that substrate and Mg2+ jointly stabilize the IF conformation, reducing global structural fluctuations and enhancing nucleotide retention in the binding pockets. In contrast, systems lacking Mg2+ exhibit increased nucleotide mobility and partial dissociation events. Thermodynamic analysis using FEP calculations further demonstrates that ATP binding is strongly stabilized in the IF state, particularly in the presence of Mg2+, whereas nucleotide stability is reduced when Mg2+ coordination is absent. To identify the molecular origins of nucleotide stabilization, we introduce a residue-level free energy decomposition approach that quantifies the contribution of individual residues to nucleotide binding energetics. This analysis reveals that the Walker A residue Lys525 provides the dominant stabilizing interaction with ATP, while neighboring residues within the Walker A motif contribute additional stabilization. In contrast, acidic residues of the Walker B motif primarily participate in catalytic organization rather than direct nucleotide stabilization. Together, these results provide a comprehensive molecular description of nucleotide stabilization and conformational regulation in PCAT1. The combined structural and energetic analyses support a model in which Mg2+ coordination and substrate binding cooperatively stabilize the inward-facing state and organize the nucleotide-binding site for productive ATP hydrolysis. More broadly, this work demonstrates how residue-level free energy analysis can reveal the energetic architecture of nucleotide recognition in ABC transporters.

Protein function often involves multiple conformational states. Several multiple sequence alignment-perturbing strategies, including stochastic subsampling, clustering, and column masking, have been shown to enhance AlphaFold2 (AF2) sampling of alternative protein states. Here, we evaluate these strategies on AlphaFold3 (AF3) and compare their performance with the BioEmu Boltzmann sampling model on 107 proteins with multiple experimentally solved conformational states. We find that unperturbed AF3 samples alternative states with significantly higher TM-scores compared to AF2 and comparable to BioEmu. In particular, all MSA perturbation methods improve AF3 sampling at a statistically significant level, improving the top 1% TM-score by at least 0.05 in approximately 20% of cases each, while rarely worsening the performance. Furthermore, we find that different choices of amino acid masks can improve column-masked AF3 sampling for specific targets. Our results highlight how MSA perturbations remain relevant in AF3, providing a useful tool for understanding dynamic biological processes.