Journal of Biological Physics最新文献

Energy landscape theory provides a unifying framework for describing protein structure, dynamics, and function across hierarchies of spatial and temporal scales. In practice, however, protein energy landscapes are never accessed directly; they are represented through a hierarchy of theoretical models, from quantum mechanical potential energy surfaces to coarse-grained potentials of mean force. Each level of description entails a systematic reduction of degrees of freedom and a corresponding transformation of the underlying landscape. In this review, we examine how protein energy landscape representations change under successive approximations to the molecular Hamiltonian, with particular emphasis on the emergence, interpretation, and robustness of landscape concepts across scales. We argue that many simplified models succeed not because they reproduce microscopic interactions in detail, but because key topological features of the landscape, such as funnels, barriers, and competing basins, are preserved under projection. This article also clarifies the physical principles underlying coarse-graining, solvent modelling, and multilevel simulation strategies and demonstrates why energy landscape theory remains predictive despite reduced chemical resolution, highlighting its role as a unifying framework for exploring biomolecular space.

The family of deubiquitinating enzymes is primarily involved in the removal of ubiquitin chains from specific target proteins. Among these proteins, ubiquitin-specific protease 12 (USP12 protein) has been identified as a key molecule in regulating cellular homeostasis, cancer progression, and immune regulation. This protein is reportedly associated with colorectal cancer, prostate cancer, and breast cancer, along with neurodegenerative disorders like Huntington’s disease. The study of mutations in USP12 could be crucial for understanding its impact on cancer and neurodegeneration, making it a potential target for therapeutics against such diseases. Our study uses a sequence-based and a structure-based screening method to identify a mutation in USP12 having the most deleterious and destabilizing effect. The mutation Y49N was found to significantly alter structural and biological functions of USP12 protein while compromising its stability. A total of 5000 conformations were generated for wild-type and Y49N_USP12 structures through normal mode analysis and a comparative study was conducted. We evaluated parameters like RMSD and R_g values to study structural divergence and reduced compactness in mutant protein conformations. Analysis of RMSF values of mutant protein showed significant structural deviations hinting at its increased flexibility. Further, heavily modified surface charge distributions were found through electrostatic surface charge mapping and fluctuations in energetic distribution indicated conformational perturbation. Moreover, the study shows how Y49N mutation could induce a helix to coil conversion in the N-terminal region of mutant protein structures throughout 5000 cycles of simulation. Our work helps advance our understanding of USP12 and its clinical value which needs to be explored further.

This study presents a novel approach to modeling fluid and ion transport in the proximal convoluted tubule (PCT) of the nephron using bond graphs. Bond graphs provide a robust framework for analyzing complex systems, explicitly depicting multi-domain energy exchange. Leveraging the modular nature of bond graphs, we first defined resistive modules representing membranes and capacitive modules representing solution-filled compartments, then coupled them using circuit theory. Our implementation extends beyond previous bond graph models of physiological processes by explicitly representing volumetric flow as a distinct variable within capacitive modules. In so doing, our model enables the consideration of mechanotransduction effects, where changes in fluid volume can influence membrane transporter activity, a crucial aspect of PCT function. Our bond graph model of the PCT (BG-PCT) comprises four fluid compartments bounded by five distinct membranes. The BG-PCT considers five chemical species (Na(^{+}), K(^+), Cl(^-), HCO(_3^-), and glucose) and six key membrane transporters distributed across the different membranes. Each structural subsystem comprises elementary thermodynamic processes, including dissipation, free-energy change, and power flow. This study demonstrates the advantages of bond graph modeling, particularly in its capacity to couple multiple energy domains and its modularity, which enables future extensibility. The BG-PCT provides a flexible, thermodynamically consistent platform for in silico research on epithelial transport dynamics and is available on GitHub under an open-source license to facilitate future research.

Efflux pump (EP) proteins play an important role in the emergence of multidrug-resistant (MDR) Staphylococcus aureus and in reducing the effectiveness of antibiotic therapy. EP, NorA of the Major Facilitator Superfamily (MFS) family, is well known for effluxing fluoroquinolones, thereby reducing the intracellular drug concentrations to sub-inhibitory levels and causing S. aureus to be less susceptible. NorA uses the electrochemical proton gradient to efflux drugs across the cell membrane; however, the mechanism of drug efflux remains to be discovered. In the present study, conventional molecular dynamics of 1.0 μs have been performed and essential dynamics (ED), and global motion of the structure has been observed and further used as reference for specifying collective variables (CVs). A metadynamics (MetaD) simulation of 100 ns was employed to sample the conformational space based on the assigned collective variables (CVs). Five energy minima states, including a global minimum, were identified from the free-energy landscape analysis, demonstrating the opening and closing mechanisms of the NorA efflux pump. Transmembrane helices 1 and 2 are identified as the most flexible helices of the efflux pump, performing the function of a lid in the extracellular section (Leu 21 to Leu 42). The efflux process through the NorA efflux pump can be observed from the resulting conformational states, which may be further utilized for the future design and development of next-generation EP inhibitors to address the drug resistance issue in S. aureus.

Phototherapy using indocyanine green (ICG) has been shown to utilize photothermal and photodynamic effects, and its effectiveness is determined through complex interactions of light transport, heat generation, and reactive oxygen species (ROS) production. In this paper, we report a computational framework for simulating the pulsed 808-nm photoactivation of ICG in a three-dimensional tumor spheroid. Photon transport in the heterogeneous spheroid domain is simulated using GPU-accelerated Monte Carlo photon transport, and the absorbed optical energy is coupled with a transient bioheat equation, an oxygen diffusion–reaction equation, and ROS production equation. The computational domain was defined as a voxelized spheroid with dimensions of 100 × 100 × 100 voxels, which represented the hypoxic tumor core and proliferative tumor areas. The simulation revealed that the fluence distribution is heterogeneous with significant attenuation, with about 70% being reduced within the first 400 µm. The maximum temperature ranged from 41.2 ± 0.6 to 53.6 ± 1.4 °C based on the pulse duration. The oxygen-dependent ROS generation was found to be highest in the oxygenated proliferative shell, whereas the hypoxic tumor core presented reduced photodynamic effects. The coupled cytotoxicity simulation revealed apoptotic-dominant areas in the oxygen-enriched tumor and necrosis due to heat in the case of increased pulse energy. The pulse duration, oxygen diffusion coefficient, and ICG absorption strength were found to be the most significant parameters affecting the treatment outcome based on the sensitivity analysis. The proposed multiphysics approach can be used as a quantitative tool to analyze laser-induced tumor phototherapy and can be helpful in the computational optimization of the treatment approach. The model is physics-based, and it predicts relative response tendencies to therapy rather than actual biological responses.

Biological rhythms serve as essential timing mechanisms for regulating physiological processes, with period and amplitude being two key characteristics. Decoupled control of these characteristics is challenging due to their complex interdependencies. This study proposes a combinatorial coordination ratio perturbation approach for independently modulating the period and amplitude of biological rhythms. The approach integrates correlation analysis and Taylor expansion. Correlation analysis offers potential perturbation combinations, while Taylor expansion assists in determining the coordination perturbation ratio. We mathematically demonstrate the feasibility of independently adjusting the period and amplitudes through combinatorial perturbation and have developed an algorithm to identify optimal parameter combinations. When applied to the Per-Cry-Bmal1 circadian model, the method enables amplitude modulation while maintaining a constant period, and it also allows for period modulation while keeping the amplitude constant, thus demonstrating its practical effectiveness. This study advances circadian rhythm research by providing a simple and feasible method for decoupled period-amplitude control, with potential applications in the treatment of circadian-related disorders and chronomedicine. Moreover, this method exhibits excellent generality and is applicable to other oscillatory dynamics as well.

Estradiol (E2), a sex steroid hormone molecule, plays a key role in regulating the actin and shape dynamics of cells in a multitude of normal and pathophysiological conditions. While cytoskeletal rearrangements, membrane dynamics, and cellular protrusions are intimately involved in cell motility and invasiveness, little is known about the impact of E2 on these processes in estrogen-dependent epithelial cells. In this study, we quantified the impact of E2 on epithelial cell shape and actin dynamics. 12Z human endometriotic epithelial cells were transfected with LifeAct-GFP and observed with lattice lightsheet microscopy, a new imaging technique fast enough to capture 3D dynamics on second timescales. E2, when applied for 24 h, significantly decreased cell circularity, solidity, and rate of change of circularity, indicating a transition to a more elongated and less variable morphology. 24-h E2 treatment also induced the formation of large membrane protrusions reminiscent of invadopodia and led to a more disordered flow of actin within those protrusions. However, these effects were not seen after 15 min of E2 treatment, suggesting that longer-term signaling is required to drive these structural changes. Together, these results suggest that E2 modulates actin polymerization and membrane protrusion dynamics in endometriotic epithelial cells and may prime them for cell invasion. This work highlights a role for hormonal signaling in mediating cytoskeletal plasticity and migratory cell phenotypes.

A digital holographic interferometer is used to measure surface deformation and fracture points in hen eggs under mechanical compression. All samples were subjected to a constant compression load until they fractured. Three different tests are performed to analyze the eggs’ mechanical response. In the first test, the egg is vertically oriented, and so the applied load; meanwhile, for the second test, the egg is horizontally oriented with the load applied vertically. The third test keeps the egg horizontal, but on this occasion, the applied load is also horizontal. As the mechanical load is applied, a camera records full-field holograms that retrieve the entire surface deformation of each egg. The influence of the egg’s orientation and the load direction modifies the eggshell surface deformation and fracture pattern. In general, fracture propagation is aligned with the load direction. From the results, samples compressed along the length of the egg show fractures, but remained in one piece. A different behavior is observed when the load is applied at the egg’s width, which separates the eggshell into two semispheres, allowing the egg’s content to drain out. A multivariate analysis was used to integrate the egg dimensions with the resulting optical data, showing a strong relationship between egg size and the fracture point. Larger eggs tend to exhibit more extensive fractures, while smaller and medium-sized eggs showed minor damage. Even though some of this information is empirically known, this is the first time it has been proven by a full imaging inspection showing eggshell deformation and cracks across eggs, independent of egg size. The latter is an advantage as there is no need to limit the study to particular dimensions to measure the exact moment of the fracture, its position, and distribution.

HER2 plays a crucial role in breast cancer (BC) progression, with the D769H and D769Y mutations significantly influencing its structural integrity, drug-binding dynamics, and therapeutic response. This study employs molecular docking and molecular dynamics simulations (MDS), with trajectories propagated for 1000 ns, to examine their distinct effects. Root mean square deviation (RMSD) analysis indicates increased conformational deviations in mutant structures, signifying heightened instability, while root mean square fluctuation (RMSF) reveals enhanced flexibility near the mutation site. Solvent accessible surface area (SASA) calculations highlight changes in solvent exposure, directly affecting ligand accessibility, while radius of gyration (Rg) assessments suggest structural loosening or tightening in response to mutation-induced alterations. Binding free energy calculations using MM-PBSA indicate variability in drug affinity, with mutations disrupting hydrogen-bonding networks and altering ligand stability. Principal Component Analysis (PCA) delineates distinct motion trajectories in mutant proteins, revealing shifts in conformational behavior. Umbrella sampling simulations indicate that while the wild-type HER2-drug complex requires 150 ps to reach equilibrium, the D769H mutant stabilizes within 100 ps, suggesting diminished drug retention. Conversely, the D769Y mutation enhances ligand binding, surpassing wild-type interaction strength. These findings elucidate mutation-specific effects on HER2 structural dynamics and drug interactions, underscoring the need for mutation-tailored therapeutic strategies to mitigate the impact of these variants.

The study employs dynamic mode decomposition (DMD) to elucidate the underlying mechanisms contributing to the enhanced motility observed in sperm bundles, primarily focusing on the role of flagellar synchronization. The decomposition reveals that synchronized flagellar movements might be a key factor enabling sperm cells to attain higher velocities when connected in bundles. Through DMD, periodical characteristics of individual periodical motion patterns, such as frequency, amplitude, and modal growth/decay rates (from DMD eigenvalues), are characterized, elucidating main parameters of the dynamic behavior of these biological systems, such as dominant frequencies of periodical motion, as well as amplitudes and velocities. The implications of this research extend beyond understanding sperm bundle dynamics, as the methodology is adaptable for identifying healthy sperm cells based on their motility patterns. Additionally, the approach holds potential for broader applications in studying other flagellar-driven microorganisms, providing a valuable tool for comparative analysis across various species.