bioRxiv : the preprint server for biology最新文献

{"title":"Harnessing cGAS-STING signaling to counteract the genotoxic-immune nexus in tauopathy.","authors":"Himanshi Singh, Sazzad Khan, Jianfeng Xiao, Nicole Nguyen, Asmita Das, Daniel Johnson, Francesca Fang-Liao, Sally A Frautschy, Michael P McDonald, Tayebeh Pourmotabbed, Mohammad Moshahid Khan","doi":"10.1101/2025.09.27.678980","DOIUrl":"https://doi.org/10.1101/2025.09.27.678980","url":null,"abstract":"<p><p>Tauopathies are progressive neurodegenerative disorders characterized by aberrant tau aggregation, cognitive decline, and persistent neuroinflammation, yet the mechanisms driving neuroinflammation and disease progression remain incompletely understood. Here, utilizing human postmortem AD brains and a mouse model of tauopathy, we report that genotoxic stress-induced cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) immune pathway form a self-amplifying loop that fuels neuropathology and cognitive deficits. Targeted disruption of this cycle through either genetic deletion of cGAS or pharmacological inhibition of STING restores immune homeostasis and attenuates tau pathology and cognitive deficits. Our results showed a significant accumulation of DNA double-strand breaks (DDSBs) and impaired DNA repair function, alongside elevated cGAS-STING signaling and type I interferon (IFN-I) responses in human AD brains compared to non-AD. In the PS19 transgenic (PS19Tg) mouse model of tauopathy, we found significantly elevated levels of DDSBs and altered expression of DNA repair proteins during early stages of disease, which preceded the dysregulation of cGAS-STING signaling and emergence of significant neuropathology in the later stage. Interestingly, genetic deletion of cGAS shifted microglial polarization from a pro-inflammatory M1 phenotype toward an anti-inflammatory M2 state, accompanied by a reduction in IFN-I signaling and improved cognitive performance in PS19Tg mice. Pharmacological STING inhibition reshaped the transcriptomic landscape, revealing selective regulation of pathways governing synaptic plasticity, and immune responses. This transcriptional reprogramming was accompanied by suppression of inflammatory responses, reduction in synaptic pathology, and attenuation of tau pathology in PS19Tg mice, underscoring STING as a therapeutic target for tauopathy. In conclusion, our findings reveal that genotoxic-immune crosstalk drives neuroinflammation and tau pathology and identify a conserved, druggable cGAS-STING axis that can be targeted to impede or slow disease progression in tauopathies.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485913/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does genetic variation in controlled experiments predict phenology of wild plants?","authors":"Victoria L DeLeo, David L Des Marais, Claire M Lorts, Thomas E Juenger, Jesse R Lasky","doi":"10.1101/2024.09.02.610887","DOIUrl":"10.1101/2024.09.02.610887","url":null,"abstract":"<p><p>Phenology and the timing of development are often under selection. However, the relative contributions of genotype, environment, and prior developmental transitions to variance in the phenology of wild plants is largely unknown. Individual components of phenology (e.g., germination) might be loosely related with the timing of maturation due to variation in prior developmental transitions. Given widespread evidence that genetic variation in life history is adaptive, we investigated to what degree experimentally measured genetic variation in Arabidopsis phenology predicts phenology of plants in the wild. As a proxy of phenology, we obtained collection dates from nature of 227 naturally inbred <i>Arabidopsis thaliana</i> accessions from across Eurasia. We compared this phenology in nature with experimental data on the descendant inbred lines that we synthesized from two new and 155 published controlled experiments. We tested whether the genetic variation in flowering and germination timing from experiments predicted the phenology of the same lines in nature. We found that genetic variation in phenology from controlled experiments significantly predicts day of collection from wild individuals, as a proxy for date of flowering, across Eurasia. However, local variation in collection dates within a region was not explained by genetic variance in phenology in experiments, suggesting high plasticity across small-scale environmental gradients or complex interactions between the timing of different developmental transitions. While experiments have shown phenology is under selection, understanding the subtle environmental and stochastic effects on phenology may help to clarify the heritability and evolution of phenological traits in nature.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11398302/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142305803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combinatorial protein barcodes enable self-correcting neuron tracing with nanoscale molecular context.","authors":"Sung Yun Park, Arlo Sheridan, Bobae An, Erin Jarvis, Julia Lyudchik, William Patton, Jun Y Axup, Stephanie W Chan, Hugo G J Damstra, Daniel Leible, Kylie S Leung, Clarence A Magno, Aashir Meeran, Julia M Michalska, Franz Rieger, Claire Wang, Michelle Wu, George M Church, Jan Funke, Todd Huffman, Kathleen G C Leeper, Sven Truckenbrodt, Johan Winnubst, Joergen M R Kornfeld, Edward S Boyden, Samuel G Rodriques, Andrew C Payne","doi":"10.1101/2025.09.26.678648","DOIUrl":"10.1101/2025.09.26.678648","url":null,"abstract":"<p><p>Mapping nanoscale neuronal morphology with molecular annotations is critical for understanding healthy and dysfunctional brain circuits. Current methods are constrained by image segmentation errors and by sample defects (e.g., signal gaps, section loss). Genetic strategies promise to overcome these challenges by using easily distinguishable cell identity labels. However, multicolor approaches are spectrally limited in diversity, whereas nucleic acid barcoding lacks a cell-filling morphology signal for segmentation. Here, we introduce PRISM (Protein-barcode Reconstruction via Iterative Staining with Molecular annotations), a platform that integrates combinatorial delivery of anti-genically distinct, cell-filling proteins with tissue expansion, multi-cycle imaging, barcode-augmented reconstruction, and molecular annotation. Protein barcodes increase label diversity by >750-fold over multicolor labeling and enable morphology reconstruction with intrinsic error correction. We acquired a ~10 million μm³ volume of mouse hippocampal area CA2/3, multiplexed across 23 barcode antigen and synaptic marker channels. By combining barcodes with shape information, we achieve an 8x increase in automatic tracing accuracy of genetically labelled neurons. We demonstrate PRISM supports automatic proofreading across micron-scale spatial gaps and reconnects neurites across discontinuities spanning hundreds of microns. Using PRISM's molecular annotation capability, we map the distribution of synapses onto traced neural morphology, characterizing challenging synaptic structures such as thorny excrescences (TEs), and discovering a size correlation among spatially proximal TEs on the same dendrite. PRISM thus supports self-correcting neuron reconstruction with molecular context.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485930/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and validation of a streamlined workflow for proteomic analysis of proteins and post-translational modifications from dried blood.","authors":"Matthew W Foster, Youwei Chen, Marlene Violette, Michael T Forrester, J Scott Mellors, Brett S Phinney, Robert S Plumb, J Will Thompson, Timothy J McMahon","doi":"10.1101/2025.09.26.678912","DOIUrl":"10.1101/2025.09.26.678912","url":null,"abstract":"<p><p>It is increasingly recognized that the 'omic analysis of whole blood has applications for precision medicine and disease phenotyping. Despite this realization, whole blood is generally viewed as a challenging analytical matrix in comparison to plasma or serum. Moreover, proteomic analyses of whole blood proteomics have almost exclusively focused on (non)targeted analyses of protein abundances and much less on post-translational modifications (PTMs). Here, we developed a streamlined workflow for processing twenty microliters of venous blood collected by volumetric absorptive microsampling that incorporates serial trypsinization, N-glycopeptide and phosphopeptide enrichment and avoids laborious sample dry-down or cleanup steps. Up to 10,000 analytes (reported as protein groups, glycopeptidoforms and phosphosites) were quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in approximately 2 h of MS acquisition time. Using these methods, we explored the stability of \"dried\" and \"wet\" blood proteomes, as well as effects of ex vivo inflammatory stimulus or phosphatase inhibition. Multi-omics factor analysis enabled facile identification of analytes that contributed to inter-individual variability of the blood proteomes, including N-glycopeptides that distinguish immunoglobulin heavy constant alpha 2 allotypes. Collectively, our results help to establish feasibility and best practices for the integrated MS-based quantification of proteins and PTMs from dried blood.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485729/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cellular and Spatial Drivers of Unresolved Injury and Functional Decline in the Human Kidney.","authors":"Blue B Lake, Ricardo Melo Ferreira, Jens Hansen, Rajasree Menon, Jeannine Basta, Heather Thiessen Philbrook, Stephanie Reinert, Robin Fallegger, Asmita K Lagwankar, Xi Chen, Soumya Maity, Katerina V Djambazova, Brittney L Gorman, Nicholas Lucarelli, Debora L Gisch, Insa M Schmidt, Viji Nair, Fadhl Alakwaa, Eirini Kefaloyianni, Bo Zhang, Amanda L Knoten, Madhurima Kaushal, Edgar A Otto, Melissa A Farrow, Dinh Diep, Dusan Velickovic, Angela R Sabo, Elijah Cole, Ian Tamayo, Jovan Tanevski, Kimberly Y Conklin, Rachel S G Sealfon, Yongqun He, Michelle Brennan, Lynn Robbins, Ying-Hua Cheng, Markus Bitzer, Aditya Surapaneni, Steven Menez, Peter V Kharchenko, Charles E Alpers, Ulysses G J Balis, Laura Barisoni, Ian H de Boer, Dawit Demeke, Agnes B Fogo, Joel M Henderson, Leal Herlitz, Gilbert W Moeckel, Parmjeet S Randhawa, Avi Z Rosenberg, Jennifer A Schaub, Suman Setty, Frank C Brosius, Maria L Caramori, Steven G Coca, Robert S Figenshau, Eric H Kim, Krzysztof Kiryluk, James P Lash, R Tyler Miller, John F O'Toole, Paul M Palevsky, Eugene P Rhee, Ana C Ricardo, Sylvia E Rosas, Prabir Roy-Chaudhury, Minnie M Sarwal, John R Sedor, Robert D Toto, Aydin Turkmen, Sushrut S Waikar, James C Williams, F P Wilson, E Steve Woodle, Evan Z Macosko, Julio Saez-Rodriguez, Pierre C Dagher, Morgan E Grams, Petter Bjornstad, Tarek M El-Achkar, Olga G Troyanskaya, Nikole Bonevich, Pinaki Sarder, Sanjeev Kumar, Christopher R Anderton, Jeffrey M Spraggins, Kumar Sharma, Michael Rauchman, Jonathan Himmelfarb, Joseph P Gaut, Kidney Precision Medicine Project, Kun Zhang, Ravi Iyengar, Matthias Kretzler, Jeffrey B Hodgin, Chirag R Parikh, Michael T Eadon, Sanjay Jain","doi":"10.1101/2025.09.26.678707","DOIUrl":"https://doi.org/10.1101/2025.09.26.678707","url":null,"abstract":"<p><p>Building upon a foundational Human Kidney resource, we present a comprehensive multi-modal atlas that defines spatially resolved versus unresolved repair states and mechanisms in human kidney disease. Homeostatic interactions between injured kidney epithelium and its surrounding milieu determine successful repair outcomes, while pathogenic signaling promotes unresolved inflammation and fibrosis leading to chronic disease. We integrated multiple single-cell and spatial modalities across ~700 samples from >350 patients (~250 research biopsies), analyzing ~1.7 million cells alongside complementary mouse multi-omic profiles spanning acute-to-chronic injury and aging (>300,000 cells) and spatial transcriptomic analysis of >150 human biopsies. This cross-species atlas delineates functional pathways and druggable targets across the nephron and defines gene regulatory networks and chromatin landscapes governing tubular, fibroblast, and immune cell transitions from injury to either recovery or failed repair states. We identified distinct cellular states associated with specific pathological features that show dynamic distributions between acute kidney injury (AKI) and chronic kidney disease (CKD), organized within unique spatial niches that reveal progression mechanisms from early injury to unresolved disease. Gene regulatory analyses prioritized key transcription factor activities (SOX4, SOX9, NFKB1, REL, KLFs) and their target networks establishing disease states and tissue microenvironments. These regulatory programs were directly linked to clinical outcomes, identifying molecular signatures of recovery and secreted biomarkers predictive of AKI-to-CKD progression, providing a key resource for therapeutic development and precision medicine approaches in kidney disease.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485684/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human patient-specific FOXG1 syndrome mouse model revealed FOXG1-MYCN-mediated regulation of protein homeostasis in neurodevelopmental disorder.","authors":"Shin Jeon, Liwen Li, Ji-Hwan Moon, DongJun Shin, Jaein Park, Eunjin Kwak, Jae W Lee, Soo-Kyung Lee","doi":"10.1101/2025.09.27.678882","DOIUrl":"https://doi.org/10.1101/2025.09.27.678882","url":null,"abstract":"<p><p>Neurodevelopmental disorders are characterized by disruptions in brain development, resulting in cognitive, behavioral, and neurological impairments. FOXG1 syndrome (FS), caused by heterozygous mutations in the FOXG1 gene, exemplifies a severe monogenic neurodevelopmental disorder. To investigate its pathogenesis, we generated a patient-specific W300X mouse model carrying a truncation variant of FOXG1. We found that the truncated FOXG1 protein in W300X-heterozygous (W300X-Het) mice is more abundant and more nuclear-localized than the full-length FOXG1 protein, implicating a pathogenic mechanism involving the truncated protein. Interestingly, W300X-Het mice exhibited profound abnormalities in the dentate gyrus, including disrupted neurogenesis, impaired granule cell migration, and altered dendritic morphology. Transcriptomic profiling identified broad dysregulation in protein homeostasis pathways, particularly ribosomal biogenesis, translation, and proteostasis. Disruption of the FOXG1-MYCN pathway, critical for robust protein synthesis during neural stem cell division, synaptogenesis, and synaptic plasticity, emerged as a key mechanism underlying these defects. In parallel, microglial activation and inflammation were markedly increased in the dentate gyrus, contributing to a pro-inflammatory environment that exacerbates neurogenic and structural deficits. Consistent with hippocampal dysfunction in FS patients, W300X-Het mice exhibited significant spatial learning and memory impairments. Together, our study highlights disrupted protein homeostasis and neuroinflammation as key drivers of FS pathogenesis, providing a framework for developing therapeutic strategies targeting these pathways.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12486130/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"STAT3 operates as an inflammation-dependent transcriptional switch.","authors":"Simon Grassmann, Hyunu Kim, Christin Friedrich, Marine Pujol, Sherry Fan, Jennifer Zhang, Giorgi Beroshvili, Veit R Buchholz, Georg Gasteiger, Joseph C Sun","doi":"10.1101/2025.09.26.678857","DOIUrl":"https://doi.org/10.1101/2025.09.26.678857","url":null,"abstract":"<p><p>Signal transducer and activator of transcription 3 (STAT3) is a key regulator of immune cell function, but its role in lymphocytes remains incompletely understood. Here, we show that STAT3 has a context-dependent function in antiviral natural killer (NK) cells, either promoting or impairing adaptive NK cell responses dependent on the level of inflammation. STAT3 is recruited to distinct genomic sites under homeostatic versus inflammatory environments, where it drives different transcriptional programs. Through this re-localization, STAT3 regulates downstream transcription factors MYB and BLIMP-1 in an inflammation-dependent manner to shape NK cell differentiation under homeostasis and during infection. Thus, STAT3 acts as a transcriptional switch that integrates cytokine signals to control lymphocyte adaptation to different environments. This mechanism highlights how therapeutic interventions targeting STAT3 can result in different outcomes depending on the degree of inflammation.</p><p><strong>Highlights: </strong>STAT3 exerts a context-dependent role on adaptive NK cells during viral infectionSTAT3 modulates IL-15 signaling by competing with STAT5 and regulating MYBHomeostatic versus inflammatory cytokines relocate STAT3 to distinct genomic sitesDownstream transcription factors MYB and BLIMP-1 govern STAT3-dependent differentiation.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485730/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiscale predictive modeling robustly improves the accuracy of pseudo-prospective seizure forecasting in drug-resistant epilepsy.","authors":"Gagan Acharya, Erin Conrad, Kathryn A Davis, Erfan Nozari","doi":"10.1101/2025.09.27.678967","DOIUrl":"10.1101/2025.09.27.678967","url":null,"abstract":"<p><p>Extensive research over the past two decades has focused on identifying a preictal period in scalp as well as intracranial EEG (iEEG). This has led to a plethora of seizure prediction and forecasting algorithms which have reached only moderate success on curated and pre-segmented EEG datasets (accuracy/AUC ≳ 0.8). Furthermore, when tested on their ability to pseudo-prospectively predict seizures from <i>continuous</i> EEG recordings, all existing algorithms suffer from low sensitivity (large false negatives), high time in warning (large false positives), or both. In this study we provide pilot evidence that <i>predictive modeling of the dynamics of iEEG features (biomarkers), seizure risk, or both</i> at the scale of tens of minutes can significantly improve the pseudo-prospective accuracy of almost any state-of-the-art seizure forecasting model. In contrast to the bulk of prior research that has focused on designing better features and classifiers, we start from off-the-shelf features and classifiers and shift the focus to learning how iEEG features (classifier input) and seizure risk (classifier output) evolve over time. Using iEEG from <math><mi>n</mi> <mo>=</mo> <mn>5</mn></math> patients undergoing presurgical evaluation at the Hospital of the University of Pennsylvania and six state-of-the-art baseline models, we first demonstrate that a wide array of iEEG features are highly predictable over time, with over 99% and 35% of studied features, respectively, having <math> <msup><mrow><mi>R</mi></mrow> <mrow><mn>2</mn></mrow> </msup> <mo>></mo> <mn>0</mn></math> for 10-second- and 10-minute-ahead prediction (mean <math> <msup><mrow><mi>R</mi></mrow> <mrow><mn>2</mn></mrow> </msup> </math> of 0.85 and 0.2). Furthermore, in almost all patients and baseline models, we observe a strong correlation between feature predictability (with some features remaining predictable up to 30 minutes) and classification-based feature importance. As a result, we subsequently demonstrate that adding an autoregressive model that predicts iEEG features on 12 ± 4 minutes into the future is almost universally beneficial, with a mean improvement of 28% in terms of area under pseudo-prospective sensitivity-time in warning curve (PP-AUC). Addition of the second autoregressive predictive model at the level of seizure risk further improved accuracy, with a total mean improvement of 51% in PP-AUC. Our results provide pioneering evidence for the long-term predictability of seizure-relevant iEEG features and the vast utility of time series predictive modeling for improving seizure forecasting using continuous intracranial EEG.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485719/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of TdP Arrhythmia Risk Through Molecular Simulations of Conformation-specific Drug Interactions with the hERG K⁺, Na_v1.5, and Ca_v1.2 Channels.","authors":"Kyle C Rouen, Kush Narang, Yanxiao Han, David Wang, Ensley Jang, Sophia Brunkow, Vladimir Yarov-Yarovoy, Alexander D MacKerell, Igor Vorobyov","doi":"10.1101/2025.09.25.678690","DOIUrl":"10.1101/2025.09.25.678690","url":null,"abstract":"<p><p>Unintended block of cardiac ion channels, particularly hERG (K_v11.1), remains a key concern in drug development as disruption of ion channel function can lead to deadly arrhythmia. To assess proarrhythmic risk, we investigated how drugs interact with hERG in its open and inactivated states and whether drug interactions with other cardiac channels like Na_v1.5 and Ca_v1.2 mitigate that risk. Using cryo-EM structures, we modeled open and inactivated conformations of these channels with Rosetta and AlphaFold. We then applied Site Identification by Ligand Competitive Saturation (SILCS), a physics-based pre-computed ensemble docking method, to predict drug binding affinities. SILCS leverages molecular simulation-generated free energy maps for high-throughput docking against hydrated lipid bilayer-embedded ion channel models. Bayesian machine learning was used to refine SILCS scoring using experimental IC₅₀ values from 69 known hERG blockers outperforming Schrödinger Glide, AutoDock Vina, and OpenEye FRED drug docking predictions. Computed drug binding affinities for hERG and Ca_v1.2 channels were used to train machine learning models that successfully classified around 300 drugs from the CredibleMeds database. Cationic nitrogen SILCS fragment free energy scores were found to be top physical properties that are predictive of drug-induced Torsades de Pointes (TdP) arrhythmia risk. This approach, which relies on the predicted binding free energies and predicted physical properties of drugs rather than the chemical structure of the drugs themselves as features could be extended to facilitate the design of new drugs where rapid assessment of arrhythmia risk can be performed prior to experimental testing.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485723/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145215219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cleavage of MEP-1 by DPF-3 Reveals Novel Substrate Specificity and Its Impact on Reproductive Fitness.","authors":"Ilkin Aygun, Afzal Amanullah, Jan Seebacher, Daniel Hess, Charlotte Soneson, Helge Grosshans, Rajani Kanth Gudipati","doi":"10.1101/2025.09.26.678732","DOIUrl":"https://doi.org/10.1101/2025.09.26.678732","url":null,"abstract":"<p><p>Proteases are enzymes that catalyse the hydrolysis of peptide bonds in proteins for their functional, modification or degradation. Members of the Dipeptidyl Peptidase IV (DPPIV) family are exopeptidases that cleave dipeptides off the N-termini of their substrate peptides, typically after proline or alanine. Recently, we showed that human DPP4 and Caenorhabditis elegans DPF-3 have a larger target repertoire in vitro, permitting cleavage after additional amino acids. Here, we use TAILS (Terminal Amine Isotopic Labelling of Substrates) to identify DPF-3 targets in vivo and observe cleavage of MEP-1 after threonine, confirming a broader substrate specificity of DPF-3 also in vivo. Demonstrating physiological relevance, we show that rendering MEP-1 resistant to cleavage disrupts its stability, leading to developmental abnormalities such as defective gonadal migration and reproductive issues. Collectively, our findings highlight a previously unappreciated complexity in the substrate specificity of DPPIV family proteases and suggest that their physiological roles may extend beyond what is currently known.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485953/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145214880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}