478 papers
This study demonstrates that the specific pairing of sterols with sphingolipids of matching chain lengths is essential for forming ordered membrane domains, as the ability of ergosterol and cholesterol to support liquid-ordered phases is critically dependent on the presence of very long-chain versus short-chain sphingolipids.
This study presents the crystal structures of full-length and truncated *Entamoeba histolytica* APS kinase, revealing that a unique, lineage-specific AS-like domain dynamically interacts with and regulates the catalytic activity of the kinase domain, representing a novel evolutionary adaptation in PAPS biosynthesis.
Using cryogenic electron microscopy under acidic conditions, researchers determined the structure of the bacterial ligand-gated ion channel DeCLIC in a previously unreported expanded-pore conformation, identifying it as a functional open state and elucidating how calcium binding and N-terminal domain dynamics drive channel closure.
This paper introduces biophysical fitness landscape design (FLD), a computational framework that uses optimized antibody ensembles to quantitatively reshape viral fitness landscapes, thereby proactively suppressing the evolution of escape variants like those of SARS-CoV-2 before they emerge.
This study benchmarks twelve fixed-charge force fields across a diverse set of twelve peptides to evaluate their ability to model structural plasticity and folding behaviors, revealing that while no single model is universally optimal, the results provide critical insights into current limitations and practical guidance for peptide simulations.
Using mass photometry and kinetic modeling, this study characterizes the binding dynamics of the bispecific antibody ivonescimab, revealing that it predominantly forms stable 2:2 dimers with VEGF and ternary complexes presenting two PD-1 molecules, with distinct dissociation constants for each interaction.
This paper presents a minimal cell-based model demonstrating that active intermittent attachments drive the transition of cell populations into three-dimensional aggregates with emergent fluid-like properties, successfully explaining experimental observations of cancer cell dewetting, shape fluctuations, and collective chemotaxis.
This study benchmarks AI-based ensemble predictors and physics-based molecular dynamics simulations against experimental data for cryptic pockets in Ebola VP35 and TEM -lactamase, revealing that while these methods can successfully predict the relative impact of mutations on pocket opening, they currently fail to reliably predict absolute opening probabilities, particularly for rare states with less than 1% occupancy.
Using macrophages as a model system, this study demonstrates that both Gβγ and Gαq independently recruit PLCβ enzymes to the plasma membrane to activate them, establishing that Gβγ alone is sufficient for PLCβ activation in specific endogenous signaling contexts.
This study utilized OpenSim inverse dynamics and static optimization on data from 16 cyclists to characterize substantial inter-subject variability in knee joint moments and reaction forces, highlighting the critical roles of specific muscle groups and supporting the need for personalized training and rehabilitation strategies in cycling.
This paper introduces a novel theoretical framework using concentric morphoelastic cylindrical shells to analytically model how tissue-scale structural incompatibilities and residual stresses drive the axial growth, bending, and autotropic behaviors of rod-like plant organs, thereby providing a mechanistic basis for the "epidermal growth control" hypothesis.
This paper challenges the validity of recent claims regarding extracranial ultraweak photon emission as a non-invasive brain biomarker by demonstrating that reported signals are likely dominated by background light and scalp emission rather than genuine brain activity due to experimental flaws and tissue attenuation.
Using the residue-level coarse-grained Mpipi-Recharged model, this study establishes a predictive framework linking protein sequence and multiscale dynamics to the emergent material properties of electrostatic protein condensates by revealing how fast intermolecular interactions coexist with slowed mesoscale dynamics in a length scale-dependent manner.
This study reveals that sodium ions regulate dopamine D2 receptor activation by remodeling allosteric coupling networks and disrupting a critical internal water column, thereby stabilizing the inactive state through newly identified binding sites and altered hydration patterns.
This paper introduces COMET, an open-source, cost-function optimized algorithm that significantly improves the precision, accuracy, and temporal resolution of drift correction in single-molecule localization microscopy (SMLM), thereby enabling higher-resolution imaging across various experimental modalities.
This paper demonstrates that a protein's native fold can be more efficiently predicted by encoding the binary core identity (buried vs. exposed) of each residue than by using traditional contact maps, sequence embeddings, or pairwise contact predictions, effectively reframing protein folding as a residue burial prediction problem.
This study systematically compares volume and surface methods for microparticle traction force microscopy through simulations and DNA-based hydrogel experiments, demonstrating that the surface method generally yields more accurate traction reconstructions with lower errors than the volume method.
This study introduces ICed-ENM, a computationally efficient coarse-grained modeling framework that refines elastic network models to quantify how disease-related missense mutations reshape protein conformational energy landscapes and identify mutation-sensitive regions through vibrational entropy changes.
This paper introduces Independent Fluorescence Component Analysis (IFCA), a novel framework utilizing third-order cumulant tensor decomposition to robustly unmix and quantitatively characterize complex, heterogeneous signals from freely diffusing single molecules, even under low photon rates and rapid sub-millisecond dynamics.
This paper demonstrates that fiber optical parametric amplification significantly enhances the sensitivity, bandwidth, and dynamic range of near-infrared laser scanning microscopy, enabling deep-tissue imaging with lower power requirements and superior performance compared to conventional photodiode and photomultiplier tube detection.