Biophysical Journal

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.

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.

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.

-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.

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.

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.

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.

The sodium-potassium ATPase (NKA) consumes 19-28% of cellular ATP and is critical for maintaining ion homeostasis. Understanding its energetic efficiency is essential for comprehending cellular physiology and pathophysiology. We develop bond graph models of the NKA that ensure thermodynamic consistency by enforcing conservation of mass, charge, and energy. A simplified 6-state model captures biophysics comparable to a 15-state model while remaining computationally tractable. Through detailed energetic analysis, we demonstrate that under physiological conditions, approximately 65% of the energy from ATP hydrolysis is stored as chemical energy in ion gradients, 10% as electrical energy in the membrane potential, and 25% is dissipated as heat, yielding an overall efficiency of [~]75%. We investigate how the free energy of ATP hydrolysis ({Delta}GATP), intracellular Na+, and extracellular K+ affect NKA efficiency and activity. A critical threshold exists at {Delta}GATP {approx} - 48 kJ/mol below which chemoelectrical transduction drops dramatically, consistent with NKA inhibition under ischemic conditions. The bond graph framework enables quantitative comparison of different NKA models and provides a systematic approach for analyzing ion pumps. SIGNIFICANCEThe sodium-potassium ATPase is one of the bodys most energy-consuming enzymes, yet its energetic efficiency and mechanisms remain incompletely understood. This study presents the first comprehensive energetic analysis using bond graph modeling, guaranteeing thermodynamic consistency. By demonstrating that simplified 6-state models capture essential energetic behaviors of complex 15-state models, we establish bond graphs as a powerful, tractable tool for energetic analysis, model comparison, model selection and validation. The bond graph approach can be applied to other transporters, offering a powerful tool for systems physiology and drug discovery.

It is an essential element of mechanobiology to measure the forces of biological cells. In microparticle traction force microscopy, they are inferred from the deformation of elastic microparticles. Two complementary variants have been introduced before: the volume method, which reconstructs surface stresses from the displacements of fiducial markers embedded inside the particles, and the surface method, which infers stresses directly from the deformation of the particle surface. However, a systematic comparison of the two methods has been lacking. Here, we quantitatively compare both approaches using simulated traction fields representing biologically relevant loading scenarios. We find that the surface method consistently reconstructs traction profiles with substantially lower errors than the volume method, which suffers from displacement tracking and stress calculation at the surface. At high noise levels, however, the performance gap becomes smaller. To compare the performance of the two methods in a realistic experimental setting, we developed DNA-based hydrogel microparticles equipped with both fluorescent surface labels and embedded fluorescent nanoparticles, enabling the direct comparison of the two methods within the same system. Compression experiments produced traction profiles consistent with Hertzian contact mechanics and confirmed the trends observed in the simulations. While our computational workflow establishes a framework to apply both methods, our experimental workflow establishes DNA microparticles as versatile and biocompatible probes for measuring cellular forces.

Smooth muscle (SM) contraction is well known to be regulated by the reversible phosphorylation of the myosin regulatory light chain. However, SM force generation and relaxation are often uncoupled from myosin phosphorylation levels (e.g. the latch-state), indicating that additional regulatory mechanisms must be at play. The precise effects of the actin binding protein caldesmon (CaD) on SM force production and relaxation remain ambiguous, largely due to contradictory findings in experiments performed at the tissue level. To date, there are no studies that have measured the effects of CaD on force and relaxation at the molecular level. Here, we use a laser-trap assay to measure the force produced by SM myosin molecules in the presence and absence of CaD. Measurements were performed before and during myosin dephosphorylation, thus simulating SM contraction and relaxation in-vitro. We demonstrate that CaD inhibits force generation, most likely through competitive inhibition of actomyosin binding while simultaneously introducing a resistive load via tethering of actin and myosin. We also establish CaD as a potentiator of relaxation, increasing force decay rate during myosin dephosphorylation. Finally, we show that CaD directly modulates the dependence of myosin-actin mechanics on myosin phosphorylation levels. These findings refine our understanding of SM regulation, highlighting CaD not merely as a passive structural stabilizer, but as a critical regulatory component of force development and relaxation. Ultimately, understanding these mechanical functions offers new perspectives on pathophysiologies involving SM, such as asthma, hypertension, and gastrointestinal disorders, potentially guiding targeted therapeutic strategies. SIGNIFICANCE STATEMENTSmooth muscle (SM) is responsible for controlling the internal diameter of blood vessels and viscera. Understanding the precise regulation of SM relaxation by actin-binding proteins remains a fundamental lacuna in physiology. Using a molecular mechanics chamber to manipulate the biochemical milieu during active measurements, we demonstrate, for the first time at the molecular level, that caldesmon (CaD) acts as a mechanical modulator that inhibits force generation and accelerates relaxation of SM myosin ensembles. Our results provide a molecular basis for resolving previous contradictory findings reported in tissue-level experiments. Ultimately, understanding the role of contractile and regulatory proteins of SM will provide the basis for understanding SM disorders, such as hypertension and asthma, and guide the development of targeted therapeutic strategies.

The cell surface localization of the Na,K-ATPase (sodium pump) is required for maintaining transmembrane electrochemical gradients. While glycosylation of the {beta}1 subunit facilitates trafficking from the endoplasmic reticulum to the plasma membrane, its role in nanoscale surface organization is not characterized. This study employed GlycoSHIELD computational modeling and DNA-PAINT single-molecule localization microscopy (SMLM) to evaluate how N-glycans influence pump distribution. In-silico simulations indicated that N-glycans sequester the protein core, providing a steric shield that increases with structural complexity. To investigate this experimentally, glycosylation-deficient mutants (3NQ) were generated and confirmed via immunoblotting. Quantitative SMLM analysis of A498 cells demonstrated that wild-type pumps exhibit higher localization density and form larger (144 nm) and more frequent clusters than 3NQ mutants (109 nm). These results indicate that N-glycosylation promotes stable enzyme clustering, supporting a galectin-lattice mechanism of organization rather than steric repulsion.

Proteins with intrinsically disordered regions (IDRs) migrate at a higher apparent molecular weight in sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) complicating their analysis and identification. Here, we investigate the sequence determinants of the hypomobility of IDRs using a series of synthetic low complexity domains. We find that negative charge increases the apparent molecular weight, but neutral polar tracts also have abnormally slow migration. Positive charge and hydrophobic residues decrease the apparent molecular weight, although lysine residues show a biphasic effect with decreased migration at high fractional contents. Combinations of residues show that different sequence contributions to the apparent molecular weight are not additive. The results can be rationalized by the protein-decorated micelle model by considering both SDS binding and the compaction of protein SDS-complexes.

Understanding how cells migrate through confined environments is crucial for elucidating fundamental biological processes, including cancer invasion, immune surveillance, and tissue morphogenesis. The nucleus, as the largest and stiffest cellular organelle, often limits cellular deformability, making it a key factor in migration through narrow pores or highly constrained spaces. In this work, we introduce a geometric surface partial differential equation (GS-PDE) model in which the cell plasma membrane and nuclear envelope are described as evolving energetic closed surfaces governed by force-balance equations. We replicate the results of a biophysical experiment, where a microfluidic device is used to impose compressive stresses on cells by driving them through narrow microchannels under a controlled pressure gradient. The model is validated by reproducing cell entry into the microchannels. A parametric sensitivity analysis highlights the dominant influence of specific parameters, whose accurate estimation is essential for faithfully capturing the experimental setup. We found that surface tension and confinement geometry emerge as key determinants of translocation efficiency. Although tailored to this specific setup for validation purposes, the framework is sufficiently general to be applied to a broad range of cell mechanics scenarios, providing a robust and flexible tool for investigating the interplay between cell mechanics and confinement. It also offers a solid foundation for future extensions integrating more complex biochemical processes such as active confined migration.

Phase separated condensates are recognized as a ubiquitous mechanism of spatial organization in cell biology. Biophysical modeling of condensates provides critical insights into the dynamics and functions of these subcellular structures that are difficult to extract via experiments. Here we present an efficient computational pipeline, CASPULE (Condensate Analysis of Sticker Spacer Polymers Using the LAMMPS Engine), to simulate and analyze the biological condensates made of sticker-spacer polymers. CASPULE implements a unique force field that combines traditional Langevin dynamics with a "detailed balance proof" protocol for single-valent bond formation between stickers. This framework allows us to study the non-trivial biophysics that emerge out of the single-valent sticker interactions coupled with the effect of separation in energetic contribution by stickers and spacers. We provide detailed documentation on how to setup the simulation environment, perform simulations and analyze the results. Through case studies, we highlight the utility and efficacy of our pipeline. Importantly, we provide statistical parameters to characterize the cluster size distribution often observed in biological systems. We envision this tool to be broadly useful in decoding the interplay of kinetics and thermodynamics underlying the formation and function of biological condensates.

Methods to visualize and quantify the molecular responses of cells to local forces exerted at adhesions are crucial to elucidate how physical forces control cellular behavior. Of the many proteins involved in focal adhesions, vinculin plays a key role in mediating force-sensitive processes. Here, we combined optical tweezers and Forster resonance energy transfer (FRET) microscopy to measure the intensity and FRET efficiency of the vinculin tension sensor, VinTS, in response to a force. Fibroblasts expressing VinTS formed adhesions on fibronectin-coated, 3m-diameter, polystyrene beads. As the beads were displaced by the cell, we applied an optical trap to counteract this movement and increase the traction force required by the cell to maintain the bead displacement. The optical trap stiffness varied from zero (no laser) up to 0.26 pN/nm. In this range, the median bead displacement after 5 min was ~200nm in all trapping conditions inducing counteracting forces in the 10-100pN range. To maintain this displacement, vinculin recruitment increased (up to 35% in relative intensity at high stiffness) while tension increased but more moderately (1-2% decrease in absolute FRET efficiency). For higher trap stiffness, the main response was an increase in vinculin recruitment, while the tension did not increase significantly. The increase in vinculin intensity was correlated with the decrease in FRET efficiency at 0.26 pN/nm but not at lower stiffness. Thus, the presence of the high stiffness optical trap over 5 min appears to induce a positive correlation between vinculin recruitment and vinculin tension. In a few instances, vinculin puncta migrated a few microns away from the bead exceeding the bead movement speed while experiencing an increase in both vinculin intensity and tension. Taken together, the results suggest that combining an optical trap with vinculin tension measurements uncovers novel vinculin dynamics in the presence of a force.

Reactive oxygen species generated during inflammation can oxidize viral envelope lipids, with outcomes ranging from modulated infectivity to viral inactivation. For SARS-CoV-2, the molecular mechanisms by which membrane lipid oxidation influences spike protein anchoring remain poorly understood. We use all-atom molecular dynamics (MD) simulations to quantify how graded oxidation of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) affects the anchoring of the SARS-CoV-2 spike transmembrane (TM) region in an endoplasmic-reticulum-Golgi intermediate compartment (ERGIC)-like multicomponent membrane. Viral envelopes containing 0, 25, 50, 75, and 100% oxidized POPC (PoxnoPC) corresponding to 0 - 55% oxidation of all PO-type phospholipids were simulated with the spike TM helix and cytoplasmic tail embedded in a POPC/POPE/POPI/POPS/cholesterol mixture. Steered MD and umbrella sampling were used to calculate the potential of mean force (PMF) for extracting the TM+CT region along the membrane normal. Partial oxidation (25 - 75% POPC) produced reductions in the detachment barrier that were not statistically distinguishable from the native system within the sampling uncertainty, whereas full POPC oxidation lowered the anchoring free energy by about 23% (from 606 {+/-} 39 to 464 {+/-} 38 kJ mol-1), indicating that oxidation of roughly half of the glycerophospholipids can measurably weaken spike-membrane coupling. Despite this reduction, the remaining barrier (about 180kBT ) is still large, suggesting that oxidation alone may be insufficient for spontaneous spike detachment and likely acts synergistically with mechanical forces during fusion or immune engagement. Analysis of acyl-chain order parameters, area per lipid, membrane thickness, number-density profiles, and lateral lipid clustering reveals that POPC peroxidation decreases lipid order, thins and softens the bilayer, and disrupts cholesterol-stabilized clusters that refer to large cooperative lipid assemblies (>10 lipids) identified via RDF-based clustering. These oxidation-induced changes reduce hydrophobic matching around the TM helix and facilitate its extraction from the viral envelope. Our results provide a mechanistic link between lipid peroxidation, membrane nanostructure, and spike anchoring, supporting lipid oxidation for example during cold atmospheric plasma or ozone treatment as a physically grounded contributing antiviral mechanism against SARS-CoV-2.

Cytokine-mediated communication is a central mechanism by which immune cells coordinate activation, differentiation and proliferation. While mechanistic reaction-diffusion models provide detailed descriptions of cytokine secretion and uptake at the cellular scale, their computational cost limits their applicability to large and densely packed cell populations. Previously employed approximations of cytokine diffusion fields rely on assumptions that neglect the influence of cellular geometry and volume exclusion. In this work, we study a macroscopic description of cytokine diffusion and reaction dynamics based on homogenization techniques, rigorously linking microscopic reaction-diffusion formulations to effective continuum models. The resulting homogenized equations replace discrete responder cells with a continuous density, while retaining essential features of cellular uptake and excluded-volume effects. Further, we show that in regimes with approximate radial symmetry, classical Yukawa-type solutions emerge as limiting cases of the homogenized model, provided appropriate correction factors are included. Overall, our approach allows efficient multiscale modeling of cytokine signaling in complex immune-cell environments.

Cell division in large embryos is coordinated by spatial waves of Cyclin B-Cdk1 activity that spread through the cytoplasm and affect cortical contractility. However, it is still unclear how cell size and localized activation near the nucleus shape these waves, and how the cytoplasmic signal is transmitted to the cortex. Here, we develop a reaction-diffusion model of Cyclin B-Cdk1 signaling in spherical cells with localized nuclear activation. We find that cytoplasmic waves have two distinct parts: an activation front that travels as a trigger wave, and a wave back that is controlled by inhibitory gradients in the cell cycle oscillator. Because these two parts are generated by different mechanisms, they can move at different speeds or even in opposite directions. This gives rise to different wave behaviors depending on nuclear size, nuclear position, and effective cell size. We then couple the Cdk1 signal to a cortical excitable network and show how cytoplasmic waveforms can regulate Rho-actin reactivation through inhibition of the RhoGEF Ect2. In this model, cortical patterns emerge mainly as downstream responses to cytoplasmic signaling, rather than as self-organized cortical waves. Overall, our results provide a mechanistic framework linking localized nuclear activation, cytoplasmic cell cycle waves, and cortical responses in large embryonic cells.