Ca2+ binding regulates muscle contraction through coupled structural and dynamical mechanisms, yet a unified description of mutation-induced perturbations in binding energetics remains incomplete. Mutational effects on proteins are often high-dimensional and difficult to interpret mechanistically. Here, we develop a physically interpretable low-dimensional reaction coordinate that captures coordination environment, electrostatic features, and dynamical coupling. Structural, electrostatic, and dynamical descriptors correlate with experimental binding free energies with Pearson coefficients of Rp = 0.83, 0.83, and 0.85, respectively. Integration of these domains improves agreement with experiment (Rp = 0.90), indicating substantial dimensional compression of the underlying descriptor space. This framework provides a physically grounded description of how mutations reshape Ca2+ binding energetics in a minimal EF-hand system.
The SARS-CoV-2 main protease (MPro) is an essential enzyme for viral replication and a primary target for antiviral drug development. Despite extensive structural and biochemical characterization, the allosteric mechanisms by which dimerization informs conformational changes at active site lack an explicit comparison across the different states that identify key residues that connect substrate binding, dimerization, and catalytic activation. Here, we integrate microsecond time scale all-atom molecular dynamics (MD) simulations with dynamical network analysis to characterize how ligand binding and dimerization modulate the allosteric communication landscape of MPro. We performed triplicate 1-μs simulations of MPro in the monomer and dimer states. For each of these states, we simulated MPro in the apo state, as well as bound to a natural peptide substrate (nsp 15/16), the covalent inhibitor nirmatrelvir (Paxlovid) and the noncovalent inhibitor ensitrelvir (Xocova). Dynamical network analyses from the resulting simulations reveal that dimerization redirects the highest correlated motions from the interdomain loop towards the domain II and III interface. At the dimer interface, we identified N-terminal and domain II β-hairpin residues that act as central communication hubs creating networks that connect both chains in the dimer. Small molecule binding to the active site further modulates these networks in distinct ways: nirmatrelvir and peptide substrate binding results in the formation of allosteric networks within the oxyanion loop, while ensitrelvir-bound monomeric MPro results in a dimer-like network, suggesting an inhibitory “allosteric switch” mechanism that may hinder dimerization upon binding. Across all systems, domain III emerges as an allosteric “pivot”, providing a platform that allows the most relevant networks to connect inter-chain communication to the active site upon dimerization. Together, these findings define how correlated motion networks couple active-site dynamics to dimerization and ligand binding, providing molecular insight into the principles governing allosteric regulation in MPro. This framework highlights potential avenues for developing antivirals that target not only the catalytic site but also the communication pathways sustaining dimer stability and enzymatic function.
Most cancer deaths result from metastasis, yet only a subset of tumor cells can complete this process. Polyaneuploid cancer cells (PACCs), which arise via endoreplication under stressors such as hypoxia, are implicated as metastatic drivers, but how they acquire this capacity remains unclear.Here, we show that under extreme self-generated hypoxia, the polyaneuploid subset of PC3 prostate cancer cells upregulates a hypoxia-responsive, HIF-1α-dependent RhoA signaling axis that promotes aerotaxis, a behavior predictive of intravasation during metastasis. We observe an enrichment of PACCs using a membrane-based culture system in which extreme, self-generated radial oxygen gradients emerge as cellular oxygen demand exceeds supply, recapitulating key features of the tumor microenvironment. Under these conditions, PACCs exhibited elevated HIF-1α and RhoA expression relative to non-PACCs. Disruption of either HIF-1α or RhoA attenuates aerotaxis, with RhoA expression suppressed upon HIF-1α inhibition, suggesting a functional HIF-1α- dependent RhoA pathway selectively enhanced in the PACC state.Quantitative analysis of nuclear morphology further reveals that nuclear circularity and solidity, morphology metrics associated with nuclear rounding and boundary organization, increase with and saturate at high nuclear area. Notably, the hypoxic PACC population exhibits significantly greater nuclear circularity and solidity compared to non-PACCs, suggesting increased rounding and stabilization of the enlarged nuclear architecture characteristic of PACCs under extreme hypoxia.Together, these findings reveal a new functional role for HIF-1α- dependent RhoA signaling in regulating aerotaxis in polyaneuploid cancer cells, which may enable aerotactic escape from hypoxic tumor cores and entry into oxygen-rich vasculature. Additionally, the association between elevated RhoA signaling and increased nuclear circularity at larger nuclear area suggests a potential link between hypoxia-responsive migration and maintenance of enlarged nuclear architecture in the PACC state. Collectively, these characteristics highlight PACCs as a hypoxia-adapted subpopulation with relevance for anti-metastatic therapeutic strategies.
Integrins are bidirectional mechanochemical receptors that transmit signals upon ligand binding to the cytoskeleton (outside-in) and cytoskeletal forces back across the membrane (inside-out) to the integrin-ligand bond. Integrins are activated prior to ligand binding, which involves large conformational rearrangements across the extracellular, transmembrane (TM), and cytoplasmic regions. While the conformational and energetic basis of outside-in activation is increasingly well defined, the mechanical forces required for separating the tightly packed αβ TM helices during inside-out signaling remain largely unknown. Here, we directly quantify the forces required to dissociate integrin TM domains (TMDs) in a lipid environment. Engineered α5β1 polypeptides consisting of TMDs and cytoplasmic tails were reconstituted into lipid nanodiscs and probed using single-molecule optical tweezers. Mechanical marker domains on each cytoplasmic tail verified correct vectorial force application, and fluorescent lipids confirmed nanodisc integrity. We find that the heterodimeric TM complex is a mechanically robust unit. In wild-type constructs, no TMD separation was observed in repeated pulls up to ∼35 pN. Point mutations in the β1-TMD (G744L, L748R) that weaken TMD interactions revealed discrete splitting events. The high mechanical forces necessary for TMD separation support a "ratchet-like" role for mechanical forces in inside-out signaling: rather than actively opening closed TMDs, they prevent re-closing of spontaneously split TMDs, thus keeping them open and activated.
Several members of the adhesion subfamily of G protein-coupled receptors (aGPCRs) are capable of self-activation by an internal agonist sequence (i.e., the Stachel) that is exposed upon removal or conformational changes of the N-terminal fragment of the receptor. Synthetic peptides derived from the Stachel sequence can be used as exogenous agonists. In the inactive form of the full-length receptor, the Stachel is sequestered as the β13 strand within the G protein-coupled receptor (GPCR) autoproteolysis-inducing (GAIN) domain, but it engages the seven transmembrane region as a helix when it is either an intramolecular sequence or a synthetic peptide. Little is known about the molecular details underlying this transition, but we hypothesize that a disordered conformation is central to this intermediate state in receptor activation. Despite the primarily helical Stachel AlphaFold3 and PEP-FOLD4 models predicted with high confidence for the entire aGPCR subfamily, computational predictions and biophysical experiments reveal a predominantly disordered conformation in solution. Investigating the ADGRG6 (also known as GPR126) Stachel peptide, circular dichroism (CD) and nuclear magnetic resonance (NMR) experiments reveal a predominantly random-coil conformation in aqueous buffer, polar detergent micelles, and zwitterionic lipids. Titration of trifluoroethanol uncovered a two-state equilibrium between an unfolded and helix-containing conformation with NMR localizing a single-turn helix to residues L846-L849. Taken together, these data indicate the ADGRG6 Stachel peptide is primarily disordered with a subset adopting partial helical structures, likely requiring the steric hindrance of the receptor binding pocket to fully induce helix formation in an induced-fit mechanism.
Within the islets of Langerhans, pancreatic beta cells coordinate pulsatile insulin release that is essential for metabolic homeostasis. This coordination emerges from complex intercellular coupling and unfolds across at least three nested timescales: (1) slow, metabolism-driven oscillations lasting several minutes; (2) fast, electrically driven bursts of a few seconds; and (3) ultrafast action-potential spikes on the order of tens of milliseconds. To unravel the principles governing this multiscale collective behavior and its link to secretion, we developed a phenomenological multicellular mathematical model based on realistic intercellular interaction patterns and combined it with timescale-specific functional connectivity analysis. Despite its deliberate simplicity, the model reproduces the rich dynamics observed experimentally, disentangling how structural coupling and multimodal connectivity patterns shape wave-like signal propagation across all three oscillatory domains. By extending the model with a secretion module, we demonstrate that the metabolic oscillation dictates the period of insulin pulses, whereas burst activity modulates their amplitude by sculpting underlying spike trains and determining the duty cycle or active time. The integrated framework therefore explains how coupling between distinct temporal domains and intercellular interactions supports robust regulation of secretion under different stimulatory conditions. Finally, by imposing changes in the form of decreased intercellular coupling and increased cellular excitability, the model predicts diminished insulin pulsatility together with elevated average secretory output, thereby recapitulating key features of secretory dysregulation observed during the early stages of type 2 diabetes pathogenesis. Thus, our findings provide a unifying multiscale perspective on beta cell network dynamics and identify specific network features whose disruption may underlie disease-related secretory defects, offering quantitative targets for experimental interrogation and therapeutic intervention.
Cancer cells in hypoxic environments often proliferate less but exhibit enhanced migration relative to their normoxic counterparts. Recent in vitro and in silico studies have characterized the role of hypoxic memory - the ability of cancer cells to retain their hypoxic phenotype even when reoxygenated - in tumor invasion. However, the observations have been limited either to exposing cancer cells to hypoxia for a fixed duration or by assuming a fixed-time persistence of the hypoxic state upon reoxygenation independent of the duration of hypoxia exposure. Thus, duration-dependent cell-state changes during hypoxia and their impact on hypoxic memory remains unclear. Here, we first analyze transcriptomic data from breast cancer samples to show that the genes upregulated at transcriptional level and hypomethylated at epigenetic level are enriched in cell invasion, indicating hypoxic memory-driven process of tumor invasion. Next, we used a computational model to investigate how the spatial-temporal dynamics of oxygen levels in a tumor drive duration-dependent changes in hypoxic memory and influence tumor invasion dynamics. Our simulation results show that such dynamic hypoxic memory can drive enhanced tumor invasion over a fixed hypoxic memory by a) enriching hypoxic cell density at the tumor front, b) reducing sensitivity of hypoxic cell state to fluctuations in oxygen supply, and c) enhancing effective diffusion of hypoxic cells. Our results highlight the crucial role of dynamic hypoxic memory in shaping tumor invasion dynamics, underscoring the need to elucidate its underlying mechanisms in future studies.
Accurately predicting RNA secondary structure remains a central challenge in computational biology. Although standard methods based on minimum free energy (MFE) optimization often produce good predictions, their accuracy varies, and they can still miss helices present in known structures. Because the thermodynamics of multibranch loops strongly influence these predictions, we examine how changes to the multiloop initiation and branching penalties affect prediction performance, focusing specifically on recall.Using a recent algorithm that partitions the branching-parameter space, we generate all distinct optimal structures obtainable under different choices of the multiloop parameters. We then evaluate the recall of these alternative structures for the Archive II dataset. Our results show that many sequences admit multiple alternative structures with substantially higher recall than the MFE prediction, establishing the predictive potential of multiloop reparameterization.We next introduce an energy-based filtering method that retains only those structures whose adjusted residual energy is at least as good as that of the MFE structure. This produces a tractable number of candidates while preserving most of the achievable improvements in recall. Compared with Boltzmann sampling, the resulting ensemble typically provides a more favorable balance between recall and precision at the level of helix classes despite being much smaller, making it particularly useful for identifying lower-probability structural features.Overall, our results show that examining branching configurations optimal modulo the branching energy provides structural information beyond the standard MFE prediction. The proposed energy-filtering approach yields a compact set of alternative structural hypotheses that can complement Boltzmann sampling and provide a practical source of candidate helices for downstream computational or experimental analysis.
Eukaryotic genomes self-organize into diverse three-dimensional (3D) chromatin conformations through intranuclear long-range interactions, yet it remains challenging to interpret how concurrent interactions combine along a chromatin polymer to shape measurable conformational readouts. Building on a minimal harmonic polymer model and the Gaussian covariance formalism, we present a 3D genome circuit representation that reorganizes the covariance-derived effective interaction strength (EIS) of a target locus pair into motif-level interaction patterns. In this representation, the graph topology of a chromatin interaction network determines the arrangement of circuit operations that summarize how local loop motifs contribute to EIS through series-like, parallel-like, or more general coupled-network combinations. The resulting EIS is then connected to experimentally accessible statistics, including pairwise contact probabilities and spatial-distance distributions from the Gaussian equilibrium ensemble, and loop stability through a first-passage description. Beyond single-pair readouts, we derive a closed-form Pearson correlation coefficient between two inter-locus spatial distances in a general harmonic network, providing an analytical way to quantify coordinated proximity changes between two locus pairs. We apply the framework to (1) estimate the effective Shh-ZRS interaction strength in a preformed CTCF-dependent loop configuration and (2) quantify enhancer-promoter proximity coordination in a shared-enhancer configuration. This motif-level circuit representation provides physics-grounded design rules for interpreting how local interaction topology, interaction strength, and perturbations such as anchor deletion or tether addition alter EIS and associated 3D conformational readouts.
Biomolecular condensates formed by phase separation inside cells often exhibit viscoelastic behavior, yet their shape recovery and fusion dynamics are frequently interpreted using purely viscous models. Here, we develop a unified theoretical and computational framework to quantify how viscoelasticity governs these two fundamental processes. We combine analytical theory for small-deformation shape recovery with axisymmetric finite-element simulations based on the Oldroyd-B constitutive model to systematically investigate both shape recovery and droplet fusion under comparable physical conditions. Our results show that, although both processes are driven by capillary forces, they are distinct in their underlying physics. Shape recovery is governed by global viscocapillary relaxation of a single connected interface and follows single- or multi-exponential decay depending on the relative magnitude of the viscocapillary timescale and the stress relaxation time. In contrast, droplet fusion is intrinsically a multi-stage process involving localized curvature-driven neck formation, rapid bridge expansion, and a transition to global relaxation. We demonstrate that viscoelasticity introduces an additional intrinsic timescale that governs the competition between capillary driving and stress relaxation, characterized by the Deborah number. This leads to enhanced intermediate-stage fusion dynamics and modified relaxation behavior compared to Newtonian droplets. Furthermore, we show that the presence of an exterior fluid with finite viscosity introduces additional hydrodynamic dissipation through two-phase coupling, significantly slowing the fusion process. Finally, we compare the computationally predicted droplet fusion in the Newtonian and viscoelastic cases with a stretched-exponential empirical formula. Deviations observed in viscoelastic regimes highlight the limitations of purely viscous descriptions and the need for models incorporating stress relaxation and memory effects.
The interactions among condensate-forming biomolecules dictate both the specificity and properties of these condensates, including their fluid-like nature and material exchange dynamics among condensate droplets. While interaction specificity is typically associated with mean interaction lifetimes, the role of interaction lifetime distributions in shaping condensate behavior remains unexplored. This is a critical gap where extensive research has focused on interaction strengths and mean lifetimes. Using a heuristic modeling approach, we show that independent and sequential multi-step binding-unbinding interactions between protein molecules lead to similar average interaction lifetimes but fundamentally different lifetime distributions: exponential and truncated power law, respectively. Combining the binding-unbinding models with Brownian dynamics simulations, our findings show that an alteration in the binding-unbinding interaction mechanism in a protein-specific system impacts the exchange dynamics, aging, and size distribution of condensates, even when mean interaction lifetimes remain constant. Our work demonstrates a link between binding-unbinding mechanisms, lifetime distributions, and features of condensates.
Pulmonary surfactant adsorbs rapidly to the surface of the liquid layer that lines the alveolar air sacs of the lungs. When compressed by the decreasing alveolar surface area during exhalation, the adsorbed films avoid collapse from the air/liquid interface and reduce surface tension to exceptionally low levels. Results with factors that induce surfactant lipids to increase intrinsic curvature suggest that adsorption proceeds via a curved rate-limiting structure. Samples with negative intrinsic curvature, defined by a concave hydrophilic surface, adsorb rapidly, but they also desorb quickly. Prior reports show that by optimizing chain packing, n-tetradecane (td) can promote conversion of planar bilayers to the negatively curved cylindrical monolayers of the inverse hexagonal phase without changing intrinsic curvature. The studies here show that td increases the rate of adsorption by the complete set of surfactant lipids without affecting intrinsic curvature and without promoting desorption of the adsorbed film during compression.
Gasdermins (GSDMs) are pore-forming proteins that trigger pyroptosis, an inflammatory cell death process that plays a crucial role in immunity. Recent experiments and atomistic simulations have shed light on GSDM molecular structure and their conformational transitions when inserting into the membrane to form pores. However, the dynamics of pore assembly remain incompletely understood. In this work, we propose a minimal coarse-grained model of GSDM proteins and run extensive molecular dynamics simulations that bridge the gap between atomistic simulations on a single molecule level and biological length and time scales relevant for membrane pore assembly. We observe supramolecular structures similar to those reported in experiments: rings, slits, and arcs with significantly different pore cross-sections. By informing our model with experimental observations, we show that the dominant regulatory factors for the assembly of pores are closely related to the kinetics of monomer conformational transition from prepore to pore state. When the monomer insertion kinetics is slow (late insertion), protein interaction strength is the key quantity promoting the formation of circular pores (rings), which maximize the pore area and consequentially the transport across the pore. In the case of fast (early) insertion, the ring formation is generally suppressed; we observe a prevalence of slit-like pores that are sub-optimal for transport. Different from the late insertion scenario, the rings are here promoted by increasing the membrane coverage with proteins. Our findings provide a mechanistic basis for understanding and potentially modulating pyroptotic cell death in various physiological and disease contexts.
Measurements and models of cochlear mechanics are built upon understanding the fluid mechanics within the cochlear scalae and the fluid interactions within the organ of Corti, basilar membrane (BM), and tectorial membrane, which together make up the organ of Corti complex (OCC). Even in the absence of an active mechanism, the passive cochlea exhibits a traveling wave, which peaks at a location slightly basal of the active peak for a given stimulus frequency, and terminates at a location similar to that of the active traveling wave. The mechanics that result in the termination of the traveling wave are not fully understood. Here, we examine motion in the lateral region of the guinea pig OCC, including the BM, Boettcher's cells (BCs), and Hensen's cells, using optical coherence tomography. We explore this motion as a potential source of viscous forces due to motion gradients. The BCs lie on the BM and were found to move at the same amplitude as the BM. Beyond the BCs, displacement amplitudes exponentially decreased, suggesting that the lateral region motion is "fluid-like." The displacement amplitude decay rates in the lateral region were similar to motion decay rates previously observed in the scala tympani fluid. We compare our results to predictions from a 3D cochlear model and estimate power dissipation as a result of the viscous forces associated with the displacement gradients in the lateral region. The fluid-like motion and viscous forces in the lateral region may serve as a source of power dissipation and thus traveling wave damping.
The eukaryotic genomes encode hundreds of proteins that function as ion channels and transporters. Essential for sustaining life, these proteins mediate the movement of inorganic ions (e.g., K+, Na+, Cl-, and Ca2+) across the plasma membrane according to their electrochemical gradients. In multicellular organisms, a diverse array of ion channels contributes to the maintenance of the resting membrane potential, the regulation of pH, osmolarity, and cell volume, and the control of secretion, electrical excitability, and synaptic activity, among many other fundamental physiological processes. Although independent evolutionary origins have been proposed for several ion channel families, their relative hierarchical importance for cellular viability remains poorly understood. To advance our knowledge of ion channel evolutionary history, we focused on determining the minimal combination of permeabilities that allows cellular viability. To this end, we conducted a survey of representative prokaryotes with small genomes across bacterial and archaeal phyla. By focusing on the smallest genomes, our approach enabled the identification of five ion channel architectures shared among prokaryotes. Among these, non-selective mechanosensitive channels (MscS and MscL) are the most abundant, followed by potassium channels, CLC-type channels and proton channels of the MotA/TolQ/ExbB family. The conservation of the mechanosensitive protein architecture across archaeal and bacterial membranes suggests that the capacity to monitor physical membrane integrity predates the requirements for electrical communication.
Immune cells operate within a dynamic mechanical environment. Shear stress, matrix stiffness, membrane tension, and cellular traction continuously shape their fate and function. Mechanosensitive ion channels (MSICs) are the convergent molecular transducers of these forces. Five families dominate immune mechanotransduction: Piezo, TRPV4, K2P/TREK, TMEM63/OSCA, and ENaC. Each converts mechanical input into Ca²⁺, K⁺, or Na⁺ fluxes that drive the transcriptional and effector programs governing immune cell behavior. Two organizing principles that have emerged from the past decade of work structure this review. First, MSICs act as mechanical immune checkpoints. Their gating state controls T cell, NK cell, and dendritic cell function in stiff tumor stroma. This parallels the chemical checkpoints exploited by current immunotherapies. Second, MSICs display context-dependent functional polarity. The same channel produces opposite outputs depending on the magnitude, geometry, and timescale of the mechanical input. PIEZO1 has been reported to promote T cell activation under physiological shear in some experimental settings but restrain cytotoxicity in stiff stroma in others. It drives a pro-inflammatory macrophage phenotype in atherosclerosis but a tissue-reparative phenotype in sepsis. It restrains ILC2s acutely but drives type 2 pathology chronically. We integrate these principles with the structural biophysics of MSIC gating, contrasting force-from-lipid and force-from-filament mechanisms. We then trace MSIC function across macrophages, microglia, T cells, NK cells, dendritic cells, neutrophils, B cells, and innate lymphoid cells. We connect this biology to the emerging mechanomedicine toolkit: sonogenetics, magnetogenetics, force-responsive nanoparticles, organ-on-chip platforms, and engineered cellular therapies. Together, mechanical immune checkpoints and context-dependent polarity reframe immunity as a force-programmable system. This view positions MSICs as translational substrates for next-generation immunotherapies in cancer, autoimmunity, fibrosis, and chronic inflammation.
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 2D 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 3D 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.
How do changes in electrical charge drive protein dysfunction and result in pathogenicity? This study investigates the relationship between charge-altering missense mutations and pathogenicity across a large-scale dataset, the Monogenic Genetic Disorder (MOGEDO) database. Using electrostatic energy calculations, we quantified the shift in interaction energy between the rest of the protein and either the wild-type or mutant residues. Our analysis shows that pathogenic variants are characterized by substantially larger electrostatic perturbations than their benign counterparts. We found that the outcome of a mutation is highly transition specific: because protein interiors tend to maintain a negative electrostatic potential, the introduction of acidic residues creates a destabilizing “energy penalty.” Conversely, basic residues often result in stabilizing shifts. Structural context further shaped these effects: buried residues showed larger electrostatic perturbation values overall, and pathogenic variants were enriched at deeply buried sites, consistent with reduced solvent screening amplifying charge perturbations. Because electrostatic interactions contribute substantially to protein binding and molecular recognition, the enrichment of pathogenic variants among binding-associated proteins suggests that electrostatic perturbations may be especially relevant in disease-associated contexts. Complementary analyses showed that pathogenic variants occur at more rigid local sites and are more often located in high-confidence modeled regions and that pathogenic-only genes show stronger gene constraint. This work therefore provides an electrostatics-focused framework for interpreting how charge-altering missense variants disrupt local protein electrostatic environments and how these disruptions are linked to pathogenicity.
