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(Biophysical Journal 125, 868–880; February 3, 2026)

Cells sense and respond to fluid shear stress. Cell surfaces are exposed to flow, yet the influence of shear stress on the behavior of plasma membrane proteins remains unclear. Here we show that extracellular flow induces the gradient distribution of cell membrane proteins with increasing concentration toward the downstream direction of the flow. Shear stress at 10-30 dynes/cm2 caused formation of concentration gradients of both GPI-anchored proteins and transmembrane proteins, including integrinß1, E-cadherin and the insulin receptor in Xenopus XTC cells.

The development of accurate and efficient computational models is essential for understanding RNA structures and biological pathways; however, the application of all-atom models to large RNA systems is often limited by their vast degrees of freedom and high computational cost. Consequently, various coarse-grained (CG) models have been developed to enhance computational efficiency while maintaining structural accuracy. Here, we discuss the major considerations in the force field development for current RNA CG models, as well as the design principles and training strategies employed in building RNA CG force fields.

In desmin-related cardiomyopathy, cellular stresses cause desmin to cleave and aggregate in vivo. Cleaved desmin fragments are amyloidogenic and induce misfolding, aggregation, and amyloid fibril formation of full-length wild type desmin. Alongside this disease condition, cells overexpress αB-crystallin and heat shock protein (HSP) 27 as cardioprotective chaperones. Chaperone proteins may refold, sequester, or disaggregate misfolded or aggregating client proteins. Previously, little was known about the protective influence of chaperone proteins on desmin fragment amyloid formation.

Amyloid fibrils are highly ordered protein aggregates that, beyond their pathological roles, are increasingly recognized as functional structures in food systems. κ-casein is a particularly interesting model due to its dual relevance: it stabilizes casein micelles in milk but can also form amyloid fibrils under destabilizing conditions. In this work, we investigate how the food-grade osmolyte sorbitol modulates the fibrillation, structure, and nanomechanics of κ-casein.Thioflavin T fluorescence assays revealed that sorbitol accelerates fibril formation by eliminating the initial lag phase while maintaining similar elongation kinetics.

Homeodomain transcription factors (TFs) recognize their DNA targets through both sequence-specific base contacts and readout of local DNA shape. While intrinsic DNA structure is encoded by nucleotide sequence, it also undergoes protein-induced structural deformation upon binding. Yet, the interplay between intrinsic and protein-induced DNA shape remains unclear. Here, we dissect how these two readout modes determine binding specificity in a trimeric complex composed of the Drosophila Hox TF Sex combs reduced (Scr) and its co-factors, Homothorax (Hth) and Extradenticle (Exd).

Proteins are dynamic molecular machines whose functions are determined by their structures. While static structures can offer initial insights or hypotheses about protein function, they are often insufficient for a detailed mechanistic understanding. Molecular dynamics (MD) simulations provide atomistic view of protein’s dynamic motion and conformational change, but the resulting high-dimensional data are challenging to interpret. Traditional summary statistics and dimensionality-reduction methods often focus on global motions and can overlook regional, yet functionally critical motions.

In the late 20th century, calcium took on the identity of an independent fusogen, when it was found to induce fusion of anionic large unilamellar vesicles (LUVs), yet its ability to drive fusion in cell-sized membranes remains poorly understood. Here, we directly quantify calcium-mediated fusion of giant unilamellar vesicles (GUVs) using a microfluidic trapping platform combined with confocal microscopy, enabling simultaneous measurement of lipid mixing, content mixing, and fusion outcomes across hundreds of single vesicles.

Ion channels are membrane proteins comprised of distinct modular domains. One example is the voltage-activated human ERG (hERG) potassium channel, which has specialized gating (opening and closing) transitions that are regulated by an intracellular N-terminal Per-Arnt-Sim (PAS) domain. Direct interactions between the PAS domain and other intracellular domains are required for the characteristic slow deactivation (closing) that is a hallmark of hERG channels, but the mechanism for PAS domain regulation of gating remains unclear.

Biomolecular condensates are viscoelastic materials that display composition-specific rheological properties and responses to mechanical forces. For condensates formed by intrinsically disordered proteins and multivalent nucleic acids, structures from coarse-grained simulations have been used in graph-based descriptions of internal, mesoscale structures to extract viscoelastic moduli using a generalized Rouse model. This model rests on the use of eigenvalues of graph Laplacians that are derived from computed, condensate-specific graphs.

Bifurcations are a crucial part of the mammalian microvasculature, as they establish the interface between blood and tissue. The flexibility of red blood cells (RBCs), the main cellular constituent of blood, is believed to strongly impact their partitioning, quantitative in vivo measurements have so far been elusive. This study investigates the effect of cell rigidity on the lateral movement after arteriole bifurcations, and lingering by comparing the movement of artificially rigidified RBCs with that of healthy RBCs in vivo.

Isothermal titration calorimetry (ITC) is a powerful technique for probing biomolecular interactions. However, accurate and precise determination of binding parameters—such as enthalpy and free energy, as well as associated uncertainties—can be hindered by noise and concentration variability. In particular, the recently noted mathematical ambiguity surrounding analyte concentrations intrinsically limits the precision with which binding parameters can be determined. Here, we compare several Bayesian approaches to validate a pipeline that resolves this ambiguity by combining two key strategies: simultaneous analysis of multiple ITC datasets and a hierarchical Bayesian treatment of analyte concentration priors.