Biophysics and Physicobiology

Interleukin-13 (IL-13) is an immunomodulatory cell signaling cytokine that has been implicated in neurodegenerative disease and chronic inflammation. IL-13 binds to its low and high affinity receptors, IL-13 receptor 1 (IL-13R1) and IL-13 receptor 2 (IL-13R2), respectively, with residence times that vary accordingly. As the binding kinetics of the cytokine-receptor complexes influence cellular responses, we employed the molecular dynamics (MD) simulation-based{tau} -random acceleration molecular dynamics method ({tau}RAMD) to compute relative residence times for wild-type (WT) IL-13 and 19 IL-13 mutants to the two receptors. Comparison with experimental kinetic data shows that the{tau} RAMD computations capture the trends in residence times. Analysis of simulated dissociation trajectories of the cytokine-receptor complexes reveals two distinct dissociation pathways of IL-13 from each of the receptors. This study thus pinpoints key determinants of the interaction of IL-13 with its receptors which could be targeted for therapeutic design. Statement of SignificanceCytokines are regulatory proteins that bind to cell surface receptors and thereby send signals to the cellular interior. Interleukin-13 (IL-13) is a cytokine that has a low and a high affinity receptor. It has important physiological roles, and its deregulation is involved in diseases such as atopic dermatitis and asthma. We employed a molecular dynamics simulation-based method to compute the effects of changes in the sequence of IL-13 on the lifetimes of complexes of IL-13 and its receptors. Comparison with experiments supports the validity of the computational approach and analysis of the simulations reveals two distinct ways in which IL-13 dissociates from each receptor. These results thus provide a map for targeting IL-13 - receptor interactions for the design of therapeutics.

Neutron scattering is a powerful technique to investigate atomic structures and molecular dynamics of proteins at the nano-scale. When it comes to dynamics, incoherent and coherent scattering respectively provide information on the single and collective dynamics of nuclei. In proteins, hydrogen has the highest incoherent cross-section, and it is common practice to overlook the contribution of coherent terms stemming from all nuclei. However, the fast collective dynamics of heavier nuclei could also be studied if coherent scattering and incoherent scattering were experimentally separated. The recent advent of polarized neutron spectroscopy with sufficient flux and energy resolution has made it possible, and opens new perspectives to investigate the relative importance of coherent scattering and the information it provides on biological samples. The present study reports on the use of polarized quasi-elastic neutron scattering (QENS) and the application of a minimalistic model adapted to both individual and collective dynamics. Using a perdeuterated green fluorescent protein as a model globular protein, the study provides an interpretation of the dynamical parameters obtained with QENS, and a comparative study of the Elastic Coherent and Incoherent Scattering Factor. Based on both experiments and calculations, we discuss the relative importance of distinct and self components of coherent scattering, which is often wrongly assumed to be representative of collective dynamics only. The results highlight the current impediments rendering complicated a straightforward analysis of fast collective dynamics in hydrated protein samples.

The process of drug unbinding is of immense importance in the field of biophysics and therapeutics. The behavior of these systems is greatly influenced by their thermodynamic and kinetic properties. Therefore, it is crucial to accurately estimate the ligand binding free energies and rate of ligand dissociation, yet these processes are often governed by rare event transitions that lie beyond the reach of standard brute-force molecular dynamics simulations. While enhanced sampling simulations offer a solution, their efficacy is strictly contingent upon the selection of appropriate collective variables (CVs) which is non-trivial for complex systems like protein-ligand complexes. In this study, we present a method to derive optimized CV from transition state region (TS) via an interpretable machine learning (ML) model, Elastic Net. By employing some physically intuitive order parameters, the derived optimized CV from the TS-region greatly accelerate ligand binding-unbinding transitions and achieves rapid free energy surface (FES) convergence across diverse systems including buried and solvent exposed active sites such as Trpsin-benzamidine complex, host-guest systems and sodium epoxidase etc. Intriguingly significant contribution of the ligand hydration is found in the optimized CV which depicts crucial role of solvent in driving ligand binding-unbinding transitions. The estimated binding free energies for different protein-ligand complexes match quite well with experiments, while maintaining a low computational cost. The derived optimized CV is also used to calculate the ligand residence times across different systems and calculated residence times are within the experimental range for all systems, again with very little computational costs. Moreover, we show that the optimized CV constructed from TS region via an interpretable ML model is transferable across diverse systems, offering a robust and scalable framework for drug discovery and investigation of complex biomolecular recognition.

Phosphatase and tensin homolog (PTEN)-induced putative kinase 1 (PINK1), a key regulator of mitophagy, has been linked to the pathogenesis of Parkinson's disease (PD). PINK1 recruits Parkin, an E3 ubiquitin ligase, triggering mitophagy in response to mitochondrial damage. During mitophagy, the quantity, stability, and activity of PINK1 must be strictly regulated; however, the mechanisms governing these parameters under cellular stress are still unclear. Herein, we determined the structural basis for PINK1 maturation mediated by heat shock protein 90/cell division cycle 37/FK506-binding protein 51 (HSP90/CDC37/FKBP51) chaperone complex. We identified PINK1-associated proteins using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and determined the structures of the complexes using Cryo-Electron Microscopy (Cryo-EM). Results showed that FKBP51 potentially interacts with a conserved leucine-proline-phenylalanine (LPF) motif on the activation loop of PINK1 and negatively regulates PINK1 functions in mitophagy. A PINK1 mutation located at the FKBP51 recognition site is linked to mitophagy deficiency, which can be partially rescued by specific inhibition of FKBP51. These findings reveal a general mechanism for PINK1 recognition by the HSP90/CDC37/FKBP51 chaperone complex and suggest a potential approach for upregulating PINK1 activity, which is impaired in PD.

Cholesterol is a key component of eukaryotic cell membranes, promoting membrane stability and modulating the function of many membrane proteins, including ion channels. In our previous work using purified human voltage-gated proton channel proteins, we showed that cholesterol inhibits the hHv1 channel by altering the conformational dynamics of its S4 segment, the key element that senses membrane voltage to control proton permeation. In the present work, we examined the effects of cholesterol analogs and potential sites in the hHv1 channel mediating cholesterol inhibition using site-directed mutagenesis and docking simulations. Our results showed that desmosterol, the immediate precursor of cholesterol, markedly attenuates cholesterol inhibition. Using single-molecule Fluorescence Resonance Energy Transfer (smFRET), we showed that desmosterol attenuates cholesterol inhibition by promoting the intermediate and open state conformations of the S4 segment. Moreover, we identified multiple residues in the hHv1 channel that are critical for cholesterol inhibition, including Y141A in the S2 segment, which reduces cholesterol inhibition by nearly 3-fold. Our smFRET results showed that the Y141A mutation promotes the intermediate conformation in the S4 segment, which underlies the attenuation of cholesterol inhibition. Consistently, docking simulations also revealed multiple residues spanning the transmembrane domain, rather than clustered within a single localized pocket. Our work identified the key molecular determinant in the hHv1 channel that mediates cholesterol inhibition and also provided a mechanism linking the conversion between demosterol and cholesterol by DHCR24 to pH homeostasis in many cells, such as phagocytes, cardiomyocytes, neurons and microglial cells.

Imipramine is known as an older generation tricyclic antidepressant drug. It has been identified in prior studies that imipramine blocks Apolipoprotein E4 (ApoE4)-induced amyloid-{beta}(A{beta}) aggregation and is associated with an improved AD diagnosis [Johnson et al. Alzheimers Research Therapy, 2022, 14, 88]. Using NMR methods such as 1H-1H NOESY and Saturation Transfer Difference Spectroscopy, we demonstrate the binding of A{beta} monomers to imipramine when the full-length A{beta} (1-42) sequence is considered. The more abundant but less toxic form, A{beta} (1-40) does not show interaction with imipramine.

Eukaryotic translation initiation is tightly regulated by interactions among translation initiation factors (eIFs) that ensure accurate start codon selection. The translation regulator, eIF5 mimic protein 1 (5MP1) contributes to this process by competing with eIF5 for binding to eIF2, thereby increasing the stringency of translation initiation. Despite its important regulatory role and emerging involvement in tumorigenesis, structural information on human 5MP1 remains limited. Here, we report the near-complete backbone and partial side-chain NMR resonance assignments of the C-terminal domain of human 5MP1 (residues 250-419), carrying a W404E substitution that disrupts dimerization. The WT protein forms a dimer at NMR concentrations, which increases the effective size of the protein and also causes disappearance of peaks corresponding to aminoacids at the dimer interface due to conformational exchange. Backbone resonance assignments were completed for 96.4% of the non-proline residues. Secondary structure was analyzed using Chemical Shift Index (CSI) and compared with the AlphaFold structural model. Regions of disagreement between the experimental and computational secondary structure assignments were further examined using 15N-NOESY-HSQC spectra, allowing experimental validation of local structural features. While the AlphaFold model accurately reproduces the overall fold of the 5MP1 C-terminal domain, several localized discrepancies were identified, particularly near the N- and C-terminal regions of the domain, where experimental NMR data support alternative secondary structure assignments. These resonance assignments and experimentally validated structural features provide a foundation for future investigations of the molecular interactions, dynamics, and functions of 5MP1 in translation initiation.

Diffusion within the cytoplasm is fundamental to numerous biological processes. Fluorescence recovery after photobleaching (FRAP) is one of the most common method for quantifying molecular diffusivity in living cells using standard laser scanning confocal microscopy (LSCM). However, accurately measuring fast cytoplasmic diffusion (typically >10 m^2/s) is challenging due to rapid recovery kinetics, weak signal-to-noise ratios, post-bleach signal artifacts, and spatial restrictions affecting normalization. While individual challenges have been addressed in specific contexts, a simple and robust framework to quantify cytoplasmic diffusivity remains elusive. Here, we present a FRAP methodology specifically designed to overcome these obstacles. By utilizing the Gaussian function -- the impulse response (ImpRes) of the diffusion equation in an infinite medium -- our approach leverages the full spatiotemporal dataset through a single-equation three-parameter fitting procedure, thus releasing restrictions to small regions of interest and arbitrary initial time-points. The methodology was validated on three datasets of increasing complexity: in silico simulated recovery profiles, in vitro data from FITC-dextran in glycerol solution, and live-cell imaging of free cytoplasmic GFP. Systematic comparison with existing models demonstrates that the ImpRes approach significantly reduces sensitivity to noise and imperfect fluorescence normalization, while remaining robust against short-term biases, such as transient probe photo-activation. Given its robustness under realistic experimental conditions and its ease of implementation, the proposed FRAP methodology provides a reliable tool for quantitative cytoplasmic analysis.

The rotary motor F1-ATPase has been extensively studied as a model molecular machine, yet rational engineering of its catalytic activity remains challenging because ATP hydrolysis is regulated by long-range intersubunit allostery and large conformational transitions. Here, we developed a homolog-guided engineering strategy to increase the maximum rotation rate of the thermophilic Bacillus PS3 F1-ATPase (TF1). Candidate mutation sites were first identified by comparing TF1 with the homologous enzymes bovine mitochondrial F1 (bMF1) and Paracoccus denitrificans F1 (PdF1), both of which exhibit higher maximum rotation rates than TF1. Systematic exploration of these sites identified four activity-enhancing hotspots, followed by focused hotspot exploration and machine-learning-assisted prioritization of combinatorial mutants. The best mutant, TF1({beta}Y313L/{beta}E332S), exhibited a 1.8-fold higher maximum rotation rate than TF1(WT) while retaining its functional thermostability. Interestingly, activity-enhancing substitutions were not limited to the residues conserved in both bMF1 and PdF1, indicating that the bMF1-PdF1 consensus substitutions effectively identify activity-enhancing hotspots rather than uniquely defining the optimal amino acid. Machine-learning-assisted exploration efficiently prioritized highly active mutants, although the predictive performance was limited by the relatively small training dataset and epistatic interactions among mutations. Kinetic and structural comparisons further provided mechanistic insights into the enhanced catalytic activity of the engineered mutant. Together, these results establish a practical strategy for engineering complex molecular motors by combining homolog-guided hotspot identification with focused hotspot exploration.

N-linked glycosylation is known to modulate the catalytic function of human carbonic anhydrase (HCA) IX, yet its influence on the underlying free-energy landscape remains largely unexplored. In the present work, we combine extensive all-atom molecular dynamics simulations with kinetic transition network analysis to investigate the effect of glycosylation on the conformational organization of the catalytic domain of HCA IX in both monomeric and dimeric forms. The multidimensional conformational space is discretized into distinct free energy minima using the distribution of reciprocal interatomic distances (DRID), and the effective barriers separating them are estimated using the max flow-min cut formalism. The corresponding free energy landscapes are visualized in terms of disconnectivity graphs, which provide a faithful representation of underlying kinetics. Minimum free energy paths, mean first passage times, as well as frustration metrics are computed to further quantify the effect of glycosylation on landscape topography. Unglycosylated systems are found to exhibit predominantly funnel-like landscapes, with a limited number of metastable states in the vicinity of the native protein fold. In contrast, glycosylation enhances landscape complexity, resulting in a wide array of relaxation timescales. Strikingly, the two glycan chains affect the landscape topography in distinct ways, despite having closely matching sequences. Dimerization couples the glycan chain dynamics, with transitions between key metastable states involving coordinated motions of both the chains. Our work illustrates that interpretation in terms of disconnectivity graphs and transition networks could reveal important insights into the organization of glycoprotein energy landscapes.

Nile Red is widely used for the detection of microplastics because its fluorescence emission is sensitive to local polarity and can distinguish hydrophobic plastics from hydrophilic ones. The fluorescence of the molecular rotor, 9-(dicyanovinyl)-julolidine (DCVJ) is less sensitive to polarity but more to viscosity. DCVJ is less widely used for microplastic analysis, although it has been used to detect polystyrene nanobeads. Here, we compared these dyes with standard samples from the Hawaii Pacific University Polymer Kit 1.0 and confirmed that Nile Red, in general, was better for the detection and identification of microplastics. Fluorescence emission was analyzed using photography, as well as spectroscopy. The color and peak emission wavelength of some stained environmental microplastics were affected by additives. Raman spectroscopy was used to confirm the chemical identity of such samples. Although DCVJ emits green fluorescence on binding to some microplastics, a peak at 620 nm has been reported with polystyrene nanobeads, attributed to dimer/excimer formation. We confirmed this property and directly observed diffraction-limited spots using fluorescence microscopy, attributed to single or just a few nanobeads. Nile Red also stains polystyrene nanobeads and gave stronger signals than with DCVJ, but Nile Red was prone to false positives due to dye aggregation in aqueous solutions.

Monitoring pH and extracellular acidification rate (ECA) in biological samples containing live mammalian cells can provide valuable information on the glycolytic activity and bioenergetic status of cells. Compared to pH electrodes, optochemical pH sensors look more advantageous, since they allow rapid, non-invasive parallel analysis of multiple samples with stable readout of pH. We have developed new fluorescent pH sensors based on hydrophobic protonable metal-free porphyrins,OEP and OEPK, embedded in a plasticized PVC matrix containing a proton transfer agent. These pH sensors provide internally-referenced calibration-free operation, both in ratiometric intensity and lifetime-based detection modes. Sensor development included optimization of the indicator dye and its photophysical characteristics, screening of different proton transfer agents to minimize sensor toxicity, tuning of the protonation range and pKa, long-term storage stability and response time studies. Optimised pH sensor coatings were then deposited on plastic substrates (96-well microplates) and used for real-time monitoring of Extracellular Acidification Rate (ECAR) for cultured cancer cells and 3D spheroid structures on standard laboratory equipment (multi-label plate reader and confocal FLIM microscope). The advanced pH sensors tailored for use with biological samples have high potential for cell analysis and related applications.

Cellular systems must act robustly to maintain organismal health, including maintaining biophysical properties that allow for appropriate cellular function, and adapting these properties through changes such as those that occur during cell division. However, we still lack tools to measure many of these physical properties with precision in the living cell. For example, the mechanical properties of the nucleoplasm, the fluid-like substance that fills the nucleus, have not been fully characterized. To investigate these properties, we have turned to the fission yeast Schizosaccharomyces pombe (S. pombe), a well-established, genetically tractable model organism that has been used extensively for studying a variety of cell biophysical processes and structures, including the cytoskeleton and cell division. It is an apt system for studying how the nucleus adapts over the course of the cell cycle, since it undergoes closed mitosis, where the nuclear envelope remains intact during cell division. Studying nucleoplasm properties over the course of closed mitosis may help reveal how nuclear volume, shape, surface area expansion, and chromosome segregation are linked and coordinated. To measure nucleoplasm material properties in S. pombe, we have paired Fluorescence Correlation Spectroscopy (FCS) with a photoswitchable fluorophore, enabling fine control over fluorescent intensity inside live cells. We infer material properties from FCS measurements, while the photoswitchable probe enables confocal imaging in conjunction with these measurements, yielding corresponding information about cellular state and dynamics. Interestingly, we find that nucleoplasm material properties do not vary significantly over the cell cycle. Future studies will use this tool to examine how diverse molecular and genetic perturbations alter nucleoplasmic properties, providing insight into how these properties maintain nuclear function and protect genomic integrity over the cell cycle and during development.

The rising incidence of invasive fungal diseases emphasizes the need for novel therapeutic strategies, including membrane-targeting antifungal agents, which require representative lipid models for detailed molecular-level studies. In this work, we propose a consensus quinary fungal plasma membrane model based on lipidomic literature data, specifically PC:PE:PI:PA:PS phospholipid model with ratio of 44:29:13:8:6. Using a bottom-up approach, we characterized the biophysical properties of this system - with particular emphasis on mechanical parameters such as bending rigidity and area compressibility - by combining molecular dynamics simulations with experimental flicker-noise and ATR-FTIR spectroscopies. Furthermore, we investigated the effect of two key non-phospholipid components: ergosterol and triacylglycerols. Biophysical analysis revealed that DPPI and its specific interactions with DSPS induced the most substantial deviations in baseline membrane parameters, particularly area per lipid, membrane thickness, and area compressibility, while DSPS influenced bending rigidity change and DLiPA primarily affected lipid packing defects. In addition, ergosterol and TGs were found to influence all of the investigated parameters to different degree. Notably, the overall biophysical profile of the proposed FPMM closely mimicked that of natural vesicles derived from yeast lipid extracts, establishing this model may provide a reliable platform for studying fungal membrane biophysics and lipid-targeting interactions.

Nanodiscs and bicelles are widely used as membrane mimetics for structural studies of membrane-associated systems. Studies have reported that their magnetic alignment behavior and phase stability are highly sensitive to composition and temperature. In this study, we systematically investigate the effects of cholesterol on bicelle formation and magnetic alignment in DMPC + 0.2 glycyrrhizic acid (GA) systems using a combined 31P and 14N solid-state NMR experimental and simulation-based approach. Temperature dependent 31P NMR spectra reveal a clear transition from vesicle dominant to aligned bicelles/nanodsics phase, while 1N quadrupolar splitting and lineshape analysis provides quantitative insights into heterogeneous lipid bilayer populations, distinguishing large aligned nanodiscs (B(L)), small nanodiscs (B(S)), and isotropic/random components (B(R)). A strong correlation is observed between the 31P derived bicelle fraction and the 14N B(L) population, confirming that macroscopic alignment in the presence of an external magnetic field directly reflects the growth of large, well-ordered nanodiscs. Cholesterol is found to play a critical dual role by modulating membrane order and curvature. At low cholesterol concentration (0 to 5 mole percent), nanodiscs alignment occurs gradually with increasing temperature, while at higher cholesterol concentration (15 to 25 mole percent), the alignment is delayed and accompanied by broader spectral features, indicating structural heterogeneity. Notably, 10 mole percent cholesterol consistently provides the optimal balance, enabling efficient temperature dependent conversion to aligned bicelles while maintaining high B(L) populations (about 70-80 percentage) and minimal isotropic fractions. In contrast, higher cholesterol maintains significant B(S) and B(R) populations, even at elevated temperature. The 14N quadrupolar coupling (Cq is approximately 8.5 to 9.2 kHz for aligned nanodiscs) remains nearly invariant across compositions, showing that cholesterol does not change local headgroup dynamics but instead redistributes lipid populations. These findings establish a combined 31P and 14N solid -state NMR approach provides a valuable platform for quantitatively correlating membrane structure, dynamics, and alignment, offering practical guidelines for optimizing bicelle systems for high resolution solid-state NMR studies of membrane associated biomolecules.

Residual dipolar couplings (RDCs) obtained via magnetic field-induced alignment offer a powerful, media-free approach for the structural analysis of biomolecules. However, their detection in short, fast-tumbling nucleic acids remains elusive at conventional magnetic fields due to insufficient alignment and sensitivity. Here, we demonstrate the direct observation of these RDCs at 1.3 GHz in a 14-mer hairpin fragment derived from an HIV-1 Vif-targeting aptamer. The 1JNH scalar couplings of imino protons were measured at fields ranging from 600 MHz to 1.3 GHz. While the coupling constants remained invariant between 600 and 900 MHz, a clear deviation was exclusively captured at 1.3 GHz for all base-paired stem residues, demonstrating the first media-free detection of field-induced RDCs in a short RNA of this size. This breakthrough arises from a synergistic B07/2 scaling, combining enhanced alignment ({propto} B02) and sensitivity ({propto} B03/2). These RDCs showed excellent agreement with the NOE-derived structure. Additionally, the flexible loop residue G8 exhibited no detectable RDC, but displayed a field-dependent TROSY/anti-TROSY intensity inversion at 1.3 GHz, reflecting an unusual 1H chemical shift anisotropy (CSA) tensor that corroborates the local base-packing environment. Our findings highlight 1.3 GHz NMR as an indispensable tool for the structural analysis of short RNAs.

This paper presents and critically reviews the results of original and some literature based experimental studies conducted by the authors last years on the structural organization of DNA in dormant (starvation stress), anabiotic dormant (4 HR treatment) E. coli cells, as well as the K12 {Delta}dps strain, which lacks the Dps protein (Dps null E. coli). The experimental data includes small-angle synchrotron radiation diffraction (SAXS) and transmission electron microscopy (TEM) data. Synchrotron radiation diffraction experiments on K12{Delta}dps cells allowed us to conclude that peaks at 44.3, 22.1, and 14.8 angstrom resolutions are associated exclusively with ordered DNA organization. Peaks at 44.3, 22.1, and 14.8 angstrom resolutions are also observed for samples of dormant (starvation stress) cells and anabiotically dormant cells. Therefore, this ordered DNA organization also applies to samples of dormant and anabiotically dormant cells. A model is proposed that considers the ordered DNA organization in the cell as a cholesteric liquid crystal. The powder diffraction pattern calculated based on this model is compared with experimental small angle X ray scattering (SAXS) data obtained on Dps-null cell samples. The model completely reproduces the key features of the experimental diffraction pattern from Dps-null cell samples. Accordingly, the cholesteric liquid crystal model corresponds to DNA packaging in dormant and anabiotically dormant cells. Cholesteric liquid crystal ordering should be further considered in all models of cellular DNA packaging. To address the question of which structural organization of DNA predominates in the cell: the cholesteric liquid crystal or nanocrystalline or whether they coexist and fully manifest themselves under different external conditions, it is necessary to utilize the latest methodological advances in structural analysis.

Polyglutamine (polyQ) aggregation plays a central role in several neurodegenerative diseases, including Huntington's disease. DNAJB6b, a molecular chaperone involved in protein quality control, is known to efficiently suppress polyQ aggregation, but its anti-aggregation mechanism remains unclear. In this work we investigate the interaction between DNAJB6b and the polyQ region (Q48) of mutant Huntingtin Exon 1 (mHttEx1) using a custom-built coarse-grained molecular dynamics model. The model incorporates a two-bead-per-amino-acid representation with hydrogen bonding (termed 2BPA-HB), and is calibrated against all-atom molecular dynamics data in terms of geometry, hydrophobicity, and hydrogen bonding. The model reproduces the tertiary structure of DNAJB6b and its interactions with Q48, and reveals an inverse correlation between DNAJB6b concentration and Q48 aggregation propensity. Our simulations show that DNAJB6b co-condensates with polyQ molecules, thereby shielding the polyQ from forming the intermolecular hydrogen bonds necessary for amyloid formation. The 2BPA-HB CGMD model en- ables efficient exploration of DNAJB6b conformations, supporting future studies of chaperone-mediated aggregation suppression and therapeutic development.

Classical neuronal cable theory relies on quasi-static electric field approximations and neglects magnetic induction, Lorentz force coupling, and transient electromagnetic currents, limiting its ability to fully characterize action potential propagation within geometrically branched axons and dendrites. This work develops a coupled Maxwell-electromagnetic cable framework by integrating finite-difference time-domain (FDTD) solutions of Maxwells equations with extended Hodgkin-Huxley and Fitzhugh-Nagumo membrane dynamics, incorporating magnetic gating perturbations, electromagnetic trans-membrane currents IEM, and nanoscale quantum corrections for thin neural segments. Controlled propagation experiments are designed to quantify deviations from standard cable predictions across asymmetric and symmetric axonal bifurcation geometries. Numerical results demonstrate that inductive magnetic effects lower the critical branch radius for junction conduction failure and break symmetric action potential invasion in geometrically identical child branches under external transverse magnetic fields. An electromagnetic corrected geometric ratio GREM is proposed to revise impedance-matching conditions at branch points, accounting for size-dependent axial current imbalance induced by magnetic and displacement currents. Parent axon conduction velocity deviates substantially from the canonical [Formula] scaling law when electromagnetic feedback and quantum charge distributions are included, triggering early signal blockage at large cable diameters. Collectively, this study establishes that quasi-static cable models underestimate electromagnetic corrections to propagation speed, waveform shape, and bifurcation transmission fidelity; the coupled Maxwell-cable framework provides a comprehensive multi-physics tool for modeling electrodynamic signal behavior in complex neuronal architectures.

Mucopolysaccharidosis IIIC (Sanfilippo syndrome type C) is a rare lysosomal storage disorder caused by loss-of-function mutations in HGSNAT, which encodes an enzyme involved in heparan sulfate (HS) degradation, leading to impaired HS catabolism, lysosomal accumulation, and progressive neurodegeneration. Because enzyme replacement therapies have limited penetration across the blood-brain barrier, substrate-reduction therapy represents an alternative therapeutic strategy. Here, N-deacetylase/N-sulfotransferase 1 (NDST1), a key enzyme responsible for HS biosynthesis, was investigated as a potential substrate-reduction target. A structure-based computational pipeline was used to identify and evaluate inhibitors targeting the NDST1 sulfotransferase domain. Approximately 4.1 million drug-like compounds and FDA-approved drugs were screened by molecular docking, followed by pharmacokinetic filtering, molecular dynamics simulations, and MM/PBSA binding free energy calculations. In parallel, peptide binders targeting the same site were generated using diffusion-based protein design and evaluated using molecular dynamics and MM/GBSA analysis. Four chemically distinct small-molecule scaffolds and three peptide candidates were identified as stable binders to the NDST1 active site. The lead small-molecule candidate exhibited a predicted binding free energy of -13.36 {+/-} 5.87 kcal mol-1. These provide a focused set of candidates for further investigation and support the feasibility of targeting NDST1 as a substrate-reduction strategy for MPS IIIC.