390 papers
Biophysics sits at the fascinating intersection where the laws of physics meet the complexity of living systems. This field uses tools like light, electricity, and mechanical forces to decode how cells move, how proteins fold, and how our senses translate the world around us. Rather than just observing biology, biophysicists measure and model life to understand the fundamental machinery that powers every organism.
On Gist.Science, we make these discoveries accessible by curating the latest preprints directly from bioRxiv. Our team processes every new submission in this category, providing both clear, plain-language overviews and detailed technical summaries so readers of all backgrounds can grasp the cutting-edge science. Below are the most recent biophysics papers from bioRxiv, ready for you to explore.
This paper introduces a multistable slow-fast dynamical model linking circadian rhythms and stochastic perturbations to explain how physiological mood variations can transition into pathological bipolar episodes, demonstrating that weakened circadian drive and geometric biases increase the likelihood of prolonged depressive or manic states.
This study presents a reconstitution protocol for myristoylated human GRASP65 and GRASP55 in lipid model membranes, revealing that these lipid-anchored proteins influence membrane dynamics, potentially mediated by their disordered SPR domains.
CTCF regulates chromatin boundary permeability by utilizing a dynamic ensemble of DNA-binding conformations, which is tuned by various epigenetic and structural factors to probabilistically determine whether cohesin stalls or bypasses the boundary.
The Life Science X-ray Scattering (LiX) beamline at NSLS-II has implemented new high-throughput, semi-automated methodological advances to support rapid small-angle X-ray scattering experiments on various muscle tissues for the study of sarcomeric proteins and myopathies.
DynMoCo is a novel deep learning framework that utilizes graph convolutional and recurrent networks to perform dynamic community detection on molecular dynamics simulations, transforming high-dimensional protein motion data into interpretable, time-evolving modular substructures.
This paper introduces a Markov State Model-based framework that characterizes small molecule interactions with disordered proteins through dynamic "binding paths" rather than static pockets, thereby rationalizing recognition mechanisms and identifying druggable regions to facilitate drug discovery for previously intractable targets.
The paper introduces ST-Analyzer, a freely available, cross-platform open-source tool that bridges command-line and graphical interfaces to simplify the reproducible analysis of high-performance computing simulation trajectories for both experts and non-experts.
This paper introduces CTMD, a fast, physics-based, and open-source metadynamics protocol that utilizes the reversible-work estimator c(t) to achieve robust early enrichment in virtual screening, effectively bridging the gap between approximate docking/AI methods and expensive free energy calculations while avoiding the memorization artifacts and training-set biases observed in recent AI co-folding approaches.
The paper introduces "Unbend," a new feature in the cisTEM software that utilizes a 3D cubic spline model to correct localized beam-induced sample motion in cryo-EM images, significantly improving particle detection rates and signal-to-noise ratios across diverse specimen types while introducing minimal additional distortion.
This study presents biochemical data and high-resolution cryo-EM structures of a circularly permuted group II intron from *Comamonas testosteroni* to elucidate the mechanistic switch from branching to hydrolytic splicing pathways, revealing active-site rearrangements that enable circular RNA production and offering new strategies for therapeutic engineering.