Biophysical journal最新文献

{"title":"Reorganization of DNA loops by competition between condensin I and a linker histone.","authors":"Tetsuya Yamamoto, Keishi Shintomi, Tatsuya Hirano","doi":"10.1016/j.bpj.2025.09.002","DOIUrl":"https://doi.org/10.1016/j.bpj.2025.09.002","url":null,"abstract":"<p><p>Condensin-mediated loop extrusion is thought to be one of the primary mechanisms underlying mitotic chromosome assembly. However, how this process is affected by other chromosomal proteins, such as histones, is not well understood. Our previous study showed that in Xenopus egg extracts codepleted of topoisomerase IIα and the histone chaperone Asf1, a highly characteristic chromatin structure called the \"sparkler\" is assembled. The sparkler is a compact structure assembled on nucleosome-free, entangled DNA in which multiple protrusions radiate from a core. Interestingly, condensin I is concentrated at the tips of the protrusions, whereas the linker histone H1.8 is enriched in the remaining regions of the structure. To understand the biophysical mechanisms underlying sparkler assembly, we construct a model predicting that DNA loops extruded from the entangled DNA undergo phase separation into two domains: loops enriched in condensin I remain as protrusions, whereas those enriched in H1.8 are reeled into the central region. We propose that H1.8 competes with condensin I for DNA binding, thereby reorganizing DNA loops formed by condensin I under this specialized condition.</p>","PeriodicalId":8922,"journal":{"name":"Biophysical journal","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diverse Conformational Ensembles Define the Shared Folding-Allosteric Landscapes of Protein Kinases.","authors":"Dhruv Kumar Chaurasiya,Athi N Naganathan","doi":"10.1016/j.bpj.2025.09.035","DOIUrl":"https://doi.org/10.1016/j.bpj.2025.09.035","url":null,"abstract":"Sequence variation across members of an enzyme family contributes to diverse ensemble behaviors, which subtly influence substrate affinity, selectivity and regulation. A classic example is the family of eukaryotic protein kinases (EPKs), which regulate numerous cellular processes and serve as important drug targets. Here, we dissect the consequences of sequence variation on the folding-conformational landscapes by performing a meta-analysis of 274 EPKs through a structure-based statistical mechanical framework. We find that EPKs populate several partially structured states in their native ensemble with a hierarchy of structural order in the N-terminal lobe that is critical for catalysis and activation. Despite this, the (un)folding mechanism is uniquely conserved across the majority of kinases, with the N-terminal lobe unfolding first. Kinase activation modulates the local stability and thermodynamic connectivity in a non-conserved manner and across the entire structure, due to the strong coupling between the active site residues to distant sites, including the established allosteric pockets. We further show how activation drives the Abl kinase ensemble towards a more folded and thermodynamically coupled system in a graded manner. Our work uncovers the thermodynamic design principles of kinases with insights into allostery, while shedding light on the extents to which ensemble behaviors are impacted by sequence variations in paralogs.","PeriodicalId":8922,"journal":{"name":"Biophysical journal","volume":"61 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145140243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SAXS Assistant: Automated SAXS Analysis for Structural Discovery in Biologics and Polymeric Nanoparticles.","authors":"Cesar Ramirez,Elena Di Mare,James Byrnes,Eman Ahmed,Maria Pineiro-Goncalves,Cristian Lopez,N Sanjeeva Murthy,Adam J Gormley","doi":"10.1016/j.bpj.2025.09.034","DOIUrl":"https://doi.org/10.1016/j.bpj.2025.09.034","url":null,"abstract":"Small-angle X-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. We present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (Rg), pair distance distribution function (PDDF)-derived Rg, maximum particle dimension (Dmax), and Kratky plots. The script builds upon BioXTAS RAW, and validates reliability via Guinier/PDDF Rg agreement, an important indicator of well-measured datasets. For assistance in Dmax estimation, a multi-layer perceptron (MLP) regressor was trained with 1,940 data files from the small angle scattering biological data bank (SASBDB). The model achieved a test set performance R2 = 0.90 and mean absolute error (MAE) = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess Dmax estimations from PDDF. Gaussian mixture model (GMM) clustering was implemented to classify profiles into structural classes based on entries in the SASBDB. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large datasets at high-throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.","PeriodicalId":8922,"journal":{"name":"Biophysical journal","volume":"27 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145140446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Multimodal Glimpse into the Amyloid Precursor Protein Intracellular Domain Ensembles.","authors":"Veronica Isabel Dodero","doi":"10.1016/j.bpj.2025.09.033","DOIUrl":"https://doi.org/10.1016/j.bpj.2025.09.033","url":null,"abstract":"","PeriodicalId":8922,"journal":{"name":"Biophysical journal","volume":"36 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic Microtubules as Sensors in Animal Cells.","authors":"Timothy J Mitchison","doi":"10.1016/j.bpj.2025.09.032","DOIUrl":"https://doi.org/10.1016/j.bpj.2025.09.032","url":null,"abstract":"Microtubules physically organize eukaryotic cells by serving as structural elements and polarized transport tracks. This article advances the hypothesis that dynamic microtubules also serve as sensors of cell shape and cytoplasmic state, building on ideas proposed for higher plant cells1. Microtubule polymerization dynamics and lattice structure are sensitive to mechanical, chemical and signaling inputs which alter the balance between microtubules and soluble tubulin and regulate MAP binding affinity. These changes are detected by transducers which include the GTP exchange factor GEF-H1 (ARHGEF2) and MARK family kinases. The resulting signals regulate cytoplasmic behavior, gene expression and tissue physiology. The microtubule destabilizing drugs colchicine and plinabulin may mimic sensing of pathophysiological cues by microtubules, leading to activation gene expression programs that promote cell survival, growth and repair which account for the therapeutic actions of the drugs. In tissue cells with stable morphologies, the sensory functions of microtubules may be as or more important than their architectural functions. This re-framing of microtubule biology suggests new directions for mechanistic inquiry and drug discovery.","PeriodicalId":8922,"journal":{"name":"Biophysical journal","volume":"17 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling Actin-Microtubule Crosstalk , in Migrating Cells.","authors":"Pinaki Nayak, Anil Kumar Dasanna, Raja Paul, Heiko Rieger","doi":"10.1016/j.bpj.2025.09.029","DOIUrl":"https://doi.org/10.1016/j.bpj.2025.09.029","url":null,"abstract":"<p><p>Actin-Microtubule crosstalk regulates the polarity and morphology of migrating cells and encompasses mechanical interactions, mediated by crosslinkers, molecular motors, and cytoskeletal regulators. Recent experiments indicate that local microtubule depolymerization promotes local actomyosin retraction, whereas local microtubule polymerization promotes local actin polymerization. Based on these observations, we develop a computational whole-cell model involving dynamic microtubules interacting mechanically and chemically with an active cell boundary. Specifically, the tips of microtubules send signals for local expansion or contraction to the active cell boundary, depending on whether they are in the growth or shrink phase. A rich, self-organized, dynamic behavior emerges, characterized by the repositioning of the microtubule-organizing center relative to the nucleus and the direction of migration. This also includes a variety of migration patterns, cell morphologies, and complex responses to obstacles in microfluidic and obstacle park environments. We demonstrate that microtubule length and numbers have a significant impact on these features, highlighting the need for new experimental investigations. Thus, the model provides a unified framework that explains a wide range of experimental observations and setups where actin-microtubule crosstalk plays a crucial role.</p>","PeriodicalId":8922,"journal":{"name":"Biophysical journal","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145136325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in FRET methodologies for probing molecular interactions.","authors":"Geetika Verma,Vasanthi Jayaraman","doi":"10.1016/j.bpj.2025.08.027","DOIUrl":"https://doi.org/10.1016/j.bpj.2025.08.027","url":null,"abstract":"Förster resonance energy transfer (FRET) has evolved into a powerful, quantitative approach for probing biomolecular structure, dynamics, and interactions. This research highlight brings together recent studies in Biophysical Journal that push the boundaries of traditional FRET. These innovations expand the spatial and temporal resolution of FRET, enabling its application to increasingly complex biological systems.","PeriodicalId":8922,"journal":{"name":"Biophysical journal","volume":"33 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145127156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Materials and measurement in mechanobiology.","authors":"Treena Livingston Arinzeh, Jianping Fu, Guy M Genin","doi":"10.1016/j.bpj.2025.09.008","DOIUrl":"https://doi.org/10.1016/j.bpj.2025.09.008","url":null,"abstract":"","PeriodicalId":8922,"journal":{"name":"Biophysical journal","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145130044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biophysical Mechanisms of SARS-CoV-2-Induced Surfactant Inhibition.","authors":"Guangle Li,Xiaojie Xu,Bingbing Sun,Yi Y Zuo","doi":"10.1016/j.bpj.2025.09.028","DOIUrl":"https://doi.org/10.1016/j.bpj.2025.09.028","url":null,"abstract":"Surfactant replacement has been studied as a supportive therapy for managing COVID-19-induced acute respiratory distress syndrome (ARDS). The clinical applications require biophysical understanding of the molecular mechanisms behind SARS-CoV-2-induced surfactant inhibition. While SARS-CoV-2 is known to attack alveolar type II epithelial cells, it is unknown whether the virus can directly interact with the pulmonary surfactant film adsorbed at the alveolar surface. The virus utilizes its spike (S) protein, consisting of two functional subunits (S1 and S2), to bind to the host cell membrane and mediate subsequent membrane fusion. We hypothesize that these two subunits may differentially interact with pulmonary surfactant, resulting in distinct effects on surfactant inhibition. The biophysical impact of recombinant S1 and S2 subunit proteins on a bovine-extracted natural pulmonary surfactant film was investigated with combined constrained drop surfactometry and atomic force microscopy. Our findings revealed that the S2 subunit, in contrast to the S1 subunit, selectively induces surfactant inhibition, evidenced by its capacity in reducing dynamic surface activity and causing domain fusion in surfactant monolayers. These results contribute novel insights into the biophysical mechanisms underlying surfactant inhibition in SARS-CoV-2-induced ARDS, and may hold translational implications for advancing surfactant therapy to manage COVID-19.","PeriodicalId":8922,"journal":{"name":"Biophysical journal","volume":"35 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145103538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Side Chain Conformations in Folded Proteins by AlphaFold: Perspective and Challenges.","authors":"Gia G Maisuradze,Abhishek Thakur,Kisan Khatri,Allan Haldane,Ronald M Levy","doi":"10.1016/j.bpj.2025.09.030","DOIUrl":"https://doi.org/10.1016/j.bpj.2025.09.030","url":null,"abstract":"AlphaFold has revolutionized protein structure prediction by accurately creating 3D structures from just the amino-acid sequence. However, a key question important for the molecular modeling field remains: Can AlphaFold predict the conformations of individual amino-acid residue side chains within a folded protein? Herein, we investigate the ability of ColabFold, an online implementation of AlphaFold2, and AlphaFold3 to predict the side-chain conformations in folded proteins. We find that over a set of 10 benchmark proteins (set A) representing several different highly-populated fold families, which are included in the AlphaFold protein structure database, the side-chain conformation prediction error of ColabFold is ∼14% for χ1 dihedral angles, and increases to ∼48% for χ3 dihedral angles. Prediction error is smaller for non-polar side chains and is somewhat improved using structural templates. ColabFold demonstrates a bias towards the most prevalent rotamer states in protein data bank, potentially limiting its ability to capture rare side-chain conformations effectively. Additionally, for 10 recently-released protein structures, which were not employed in the training of AlphaFold2, we show that ColabFold predicts side-chain conformations with almost the same accuracy as for the set A. Also, we demonstrate the side-chain prediction accuracy by AlphaFold3 is slightly better than by ColabFold. As an application of AlphaFold to explore the structural consequences of strongly cooperative mutations on side-chain rearrangements, we employ a Potts sequence-based statistical energy model to perform large scale mutational scans of two proteins ABL1 and PIM1 kinase, searching for the most strongly cooperative mutational pairs, and then use ColabFold to predict the structural signatures of this cooperativity on the interacting side chains. Our results demonstrate that integration of the sequence-based Potts model with AlphaFold into a single pipeline provides a new tool that can be used to explore the fundamental relationship between protein mutations, and cooperative changes in structure, and fitness.","PeriodicalId":8922,"journal":{"name":"Biophysical journal","volume":"56 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145103537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}