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Cytoplasmic proteins must recruit to membranes to function in processes such as endocytosis and cell division. Many of these proteins recognize not only the chemical structure of the membrane lipids, but the curvature of the surface, binding more strongly to more highly curved surfaces, or curvature sorting. Curvature sorting by amphipathic helices is known to vary with membrane bending rigidity, but changes to lipid composition can simultaneously alter membrane thickness, spontaneous curvature, and leaflet symmetry, thus far preventing a systematic characterization of lipid composition on such curvature preferences through either experiment or simulation.

Hepatitis C virus (HCV) genome codes for various proteins essential to its replication cycle. Among these, the core protein (HCC) forms the capsid via organised multimerization, thereby guiding viral assembly. This process depends on the dynamic localisation of HCC between the endoplasmic reticulum bilayer membrane and the lipid droplet monolayer. While past studies have examined the role of some HCC structural properties and other viral and host proteins in the assembly process, the contribution of lipid molecules was not thoroughly investigated yet.

Mechanical overstretching of individual RNA-DNA hybrids is used as a novel in vitro assay to prepare a co-transcriptional RNA structure and study its interaction with proteins. Dual optical traps hold two microscopic beads linked by a RNA-DNA molecular construct that is designed such that the RNA strand progressively peels off and folds when trap-to-trap distance increases. Subsequent distance reduction leads to duplex reannealing, RNA structure and its interaction with proteins are probed by continuously measuring force during this peeling/reannealing cycle.

RAFs initiate the cascade leading to activation of the extracellular signal-regulated kinases (ERK). In a substantial fraction of cancer cells, RAFs are the least abundant pathway proteins between receptor tyrosine kinases (RTKs) and ERK. In some cases, active RAF kinases are present at the plasma membrane at just hundreds of copies per cell, but the consequences of such limited RAF abundance are unclear. By developing continuum and stochastic computational models of the epidermal growth factor receptor (EGFR)-ERK pathway, we showed that low RAF abundance creates signaling bottlenecks between RTKs and ERK with a potential for stochastic RAF dynamics that can propagate especially to low-abundance downstream pathway proteins.

Numerous proteins are associated with cellular membranes and often contain single or multiple membrane-spanning helices. These helices can mediate membrane protein interactions to form functional complexes involved in enzymatic or signaling processes. A detailed understanding of interactions and driving forces is essential for the understanding of membrane protein association and for membrane protein complex design. The glycophorin-A (GpA) transmembrane helical dimer has been studied extensively by biochemical and structural methods, including mutagenesis of dimer interface residues.

Focal adhesions play critical roles in a variety of cellular behaviors and physiological processes, including cell migration, proliferation, wound healing, and tumor invasion. While focal adhesions are recognized as key protein signaling and mechanosensory hubs that mediate interactions between the cell and the extracellular matrix (ECM), the mechanisms by which cells sense and respond to ECM geometry at the subcellular level, and how these cues are translated into cell-scale behaviors, remain unclear.

Cellular environments are crowded systems with reduced solvent polarity, yet how solvent polarity shapes RNA elasticity remains unclear. In this work, our high-precision magnetic tweezers and all-atom molecular dynamics simulations showed that decreasing solvent polarity with ethanol as a model cosolvent produces a biphasic response for double-stranded (ds) RNA: moderate ethanol concentration softens dsRNA, causing a slight decrease in bending persistence length P and stretch modulus S, but high ethanol concentration markedly stiffens dsRNA, reflected by the ∼2-fold increase in P and ∼4-fold increase in S.

The apparent bending moduli KC of bilayers composed of binary mixtures of lipids with different spontaneous curvatures have been obtained using x-ray diffuse scattering (XDS). The mixtures that were studied are POPC/POPE, POPC/POPA, POPC/POPS, and DLPC/DiphyPC. The data are qualitatively consistent with what is expected from the theory of diffusional softening for lipids with different spontaneous curvatures. However, the derived spontaneous curvature differences are larger than those obtained from the hexagonalII phase and from a recent GUV study.

Cells sense substrate mechanical properties through the integrin-talin-F-actin linkage. Talin’s N-terminal head domain binds β-integrin, whereas its C-terminal domain connects to F-actin directly via two actin binding sites (ABS) and indirectly through cryptic vinculin binding sites (VBS) within rod domain bundles. Force-induced unfolding of these alpha helical bundles exposes VBS, recruiting vinculin to strengthen the talin-actin bond. This system is sensitive to the loading rate and is influenced by rates of F-actin movement and substrate stiffness.

Single-molecule manipulation techniques are used to elucidate mechanisms in biological systems. Optical tweezers are powerful tools because of their ease of use in combination with optical microscopy and appropriate torque range. However, the use of optical tweezers to generate rotational motion is difficult owing to the complexity of applying constant torque to a moving molecule. The magnitude of the torque applied with optical tweezers depends on the positional relationship with the trapping particle and requires positional feedback.

Biomolecular systems operate across an extraordinary range of spatial and temporal scales, from the electronic rearrangements underlying catalysis to the mesoscale organization of membranes, chromatin, and supramolecular condensates. Coarse-grained (CG) and multiscale modeling have become essential tools for bridging these scales, enabling us to follow complex processes over biologically relevant times and system sizes while retaining mechanistic detail where it matters most. With the rapid growth of graphics processing unit (GPU) computing, improved force fields, and machine learning (ML)-assisted models, the field is now poised for predictive, design-capable frameworks that can interface directly with experimental data.

In 1952, Alan Turing showed that analog reaction-diffusion equations were extremely powerful models of biological development and of distributed cellular automata. Analog circuits have been shown to accelerate the simulation of chemical reactions by many orders of magnitude, including in stochastic (noisy) cytomorphic chips which are useful for drug-cocktail formulation and in systems medicine. However, the simulation of the partial differential equations of diffusion is expensive to architect in analog systems.