503 papers
This study systematically evaluates various design components of FRET-based vinculin tension sensors to establish a comparative framework for interpreting force measurements and provide practical guidelines for optimizing molecular probe engineering.
Using a laser-trap assay to resolve previous contradictions in tissue-level studies, this research demonstrates that caldesmon acts as a critical molecular regulator in smooth muscle by inhibiting force generation through competitive actomyosin binding and accelerating relaxation, thereby offering new insights into the pathophysiology of disorders like hypertension and asthma.
This study presents the first molecular structures of active Photosystem I-platinum nanoparticle biohybrids to define the interface topology and electron transfer pathways, thereby establishing design principles for optimizing protein-nanomaterial architectures for solar fuel production.
This study demonstrates that Repetitive Extragenic Palindrome (REP) elements in *E. coli* function as context-dependent dual regulators of 3'UTRs by simultaneously acting as partial Rho-dependent transcription terminators and mRNA stabilizers, thereby tuning gene expression and contributing to regulatory diversity across strains without altering coding sequences.
Using cryo-electron tomography, this study reveals that influenza hemagglutinin trimers on native virions form flexible, locally ordered lattices through lateral HA1-mediated interactions, which are essential for coordinating membrane fusion and facilitating efficient viral entry.
The paper introduces MORPHIS, a machine learning framework that utilizes explainable, analytically rich features to robustly quantify and interpret heterogeneous single-cell morphological responses to diverse perturbations, including pharmacological treatments and aging, across various biological contexts.
This study reveals that the Escherichia coli MscM channel employs a unique gating mechanism where membrane tension sensed by the transmembrane domain is transmitted via a cytoplasmic TM7 extension to open lateral fenestrations through conformational changes in the cytoplasmic domain, distinguishing it from other MscS-like channels.
This study identifies the specific sequence determinants, including negative charge, neutral polar tracts, and hydrophobic residues, that govern the anomalous slow migration of intrinsically disordered proteins in SDS-PAGE, explaining these effects through a protein-decorated micelle model that accounts for both SDS binding and complex compaction.
The paper introduces CGRig, a rigid-body protein model that integrates residue-level interaction sites with overdamped Langevin dynamics to enable efficient, large-scale simulations of protein assembly while preserving essential structural specificity and achieving performance comparable to all-atom accuracy.
This study identifies SNOR, a novel conserved ribosome-associated factor in *Schizosaccharomyces pombe* that represses protein synthesis by structurally blocking the ribosome during glucose-induced dormancy and is essential for translation restart upon stress relief.
This study demonstrates that macromolecular crowding enables ATP to overcome electrostatic and entropic barriers to form protein-free, responsive liquid-like condensates that create distinct microenvironments for selective molecular enrichment and RNA protection, thereby expanding ATP's role beyond an energy carrier to a structural and regulatory architect in cellular and prebiotic contexts.
The authors developed an investigator-blind, unsupervised analysis pipeline for molecular dynamics data that successfully identified both known functional microswitches and two novel structural motifs (a kink in transmembrane helix 2 and a coupled piston-like motion of TM2 and TM3) controlling GPCR function.
This study identifies a conserved G4-binding motif across hemorrhagic fever viruses and demonstrates that the Yellow Fever virus NS3 protease domain specifically and with high affinity binds parallel G-quadruplexes through a unique stacking interaction involving key residues like PHE40, suggesting a novel target for antiviral development.
This study demonstrates that knot theory-derived entanglement measures, specifically writhe and the second Vassiliev invariant, reveal evolutionarily conserved, functionally relevant topological organization in intrinsically disordered proteins that bridges the gap between sequence composition, structural ensembles, and biological function.
The paper introduces RESURF, a lightweight deep learning framework that enables real-time, high-throughput super-resolution fluctuation imaging of live cells by reconstructing high-resolution images from as few as eight low-resolution frames in under 30 milliseconds.
This study demonstrates that membrane curvature significantly enhances lipid oxidation by exposing lipid tails to reactive oxygen species, a process that is modulated by lipid composition, with low to moderate cholesterol suppressing curvature-dependent oxidation while high cholesterol restores it.
This study demonstrates that a per-residue mutational robustness index, derived from the stability variance of single-amino-acid substitutions, effectively predicts protein dynamics across both natural and de novo designed proteins, offering a biophysically grounded complement to structural confidence scores like pLDDT.
By reconstituting the E. coli KdpFABC potassium pump into lipid nanodiscs and utilizing cryo-EM, researchers determined high-resolution structures of the complex in active turnover states, revealing that specific structural and annular lipids are essential for maintaining the complex's integrity and facilitating the conformational changes required for potassium transport.
By applying a first-passage-renewal framework to model protein target search on DNA as a resetting process, this study reveals that broad distributions of sliding times are a universal fingerprint of optimal search efficiency, demonstrating how intermittent detachment regulates both the mean search time and its fluctuations.
This study utilizes an explainable AI framework integrating protein language models and energy landscape analysis to reveal that the "allosteric blind spot" in predictive models arises from the intrinsic biophysical design of protein kinases, where orthosteric sites reside in optimized, minimally frustrated regions while allosteric sites are encoded in persistent, neutrally frustrated zones that enable regulatory versatility.