Journal of Molecular Biology最新文献_第2页

Deeptosis: A Deep Learning-Based Platform for Label-Free Discrimination of Apoptosis and Pyroptosis from Brightfield Microscopy. Deeptosis：一个基于深度学习的平台，用于明视野显微镜下细胞凋亡和焦亡的无标记区分。

IF 4.5 2区生物学

Journal of Molecular Biology Pub Date : 2026-04-16 DOI: 10.1016/j.jmb.2026.169815

Haiji Wang, Shaofeng Lin, Chenbei Li, Fengzi Zhang, Yuyuan Zhu, Xu Liu, Cainian Huang, Min Cao, Sijia Jiang, Yaqin Liu, Tao Wang, Lijie Wang, Shuaijie Liu, Haodong Xu, Liming Wang

{"title":"Deeptosis: A Deep Learning-Based Platform for Label-Free Discrimination of Apoptosis and Pyroptosis from Brightfield Microscopy.","authors":"Haiji Wang, Shaofeng Lin, Chenbei Li, Fengzi Zhang, Yuyuan Zhu, Xu Liu, Cainian Huang, Min Cao, Sijia Jiang, Yaqin Liu, Tao Wang, Lijie Wang, Shuaijie Liu, Haodong Xu, Liming Wang","doi":"10.1016/j.jmb.2026.169815","DOIUrl":"10.1016/j.jmb.2026.169815","url":null,"abstract":"<p><strong>Motivation: </strong>Accurately distinguishing apoptosis from pyroptosis is essential for studying regulated cell death and its roles in immunity and disease, but their similar morphologies and shared upstream signals make label-free bright-field discrimination difficult.</p><p><strong>Results: </strong>We present Deeptosis, an end-to-end deep learning pipeline that performs automatic cell segmentation (Cellpose) and single-cell classification with a Vision Transformer (ViT). Trained on 26,565 manually annotated bright-field cells (apoptosis, pyroptosis, other), the model achieved a mean AUROC of 0.999 in five-fold cross-validation and retained high performance on an independent test set (AUROC 0.990 apoptosis, 0.982 pyroptosis, 0.983 other). The system outputs color-coded visualization and a per-cell CSV containing coordinates, labels, and confidence scores, and can be operated through a web interface for batch analysis.</p><p><strong>Availability: </strong>Source code and scripts are available at GitHub (https://github.com/Bamba-WangLab/Deeptosis); a prototype web app (http://modinfor.com/Deeptosis) demonstrates the workflow.</p><p><strong>Conclusion: </strong>Deeptosis provides a label-free framework for quantitative analysis of cell death modalities.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169815"},"PeriodicalIF":4.5,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

mdxplain: Scalable molecular dynamics analysis with machine learning-based feature selection and modular workflows. 基于机器学习的特征选择和模块化工作流的可扩展分子动力学分析。

IF 4.5 2区生物学

Journal of Molecular Biology Pub Date : 2026-04-16 DOI: 10.1016/j.jmb.2026.169809

Maximilian Salomon, Maik Pankonin, Maeve Branwen Butler, Hossein Batebi, Peter F Stadler, Peter W Hildebrand, Guillermo Pérez-Hernández

{"title":"mdxplain: Scalable molecular dynamics analysis with machine learning-based feature selection and modular workflows.","authors":"Maximilian Salomon, Maik Pankonin, Maeve Branwen Butler, Hossein Batebi, Peter F Stadler, Peter W Hildebrand, Guillermo Pérez-Hernández","doi":"10.1016/j.jmb.2026.169809","DOIUrl":"10.1016/j.jmb.2026.169809","url":null,"abstract":"<p><p>Molecular dynamics (MD) simulations provide detailed, time-resolved insight into molecular motion. Advances in hardware and software now make very large systems accessible, increasing the need for efficient tools to analyze the resulting trajectories. We introduce mdxplain, a high-level Python API that facilitates the creation of scalable, streamlined, and reusable analysis pipelines for large MD datasets with only a few lines of code. A unified object exposes all functionality, combining typical MD featurization and MD metrics with dimensionality reduction, clustering and feature selection via decision trees, supporting expert and non-expert users in identifying structural patterns and explain the dynamic behavior of their systems. Leveraging metadata annotations for trajectory- and residue-selection, mdxplain can handle multiple topologies in a single execution and uses optimized memory handling to process large datasets (millions of frames) efficiently. Its reports include distributional and time-series plots, representative conformations and decision trees combined with optional 3D visualization via PyMOL and NGLView. Pipelines can be exported at all time, bundling all relevant data for sharing and reuse, ensuring reproducibility and FAIR compliance. The Python API, together with documentation, examples, and tutorials is available on github.com/maximilian-salomon/mdxplain and on mdxplain.de.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169809"},"PeriodicalIF":4.5,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

OpenRecombinHunt: Automatic detection of recombination in publicly available viral sequences. OpenRecombinHunt：自动检测重组在公开可用的病毒序列。

IF 4.5 2区生物学

Journal of Molecular Biology Pub Date : 2026-04-16 DOI: 10.1016/j.jmb.2026.169811

Tommaso Alfonsi, Yavuz Samet Topcuoglu, Matteo Chiara, Anna Bernasconi

{"title":"OpenRecombinHunt: Automatic detection of recombination in publicly available viral sequences.","authors":"Tommaso Alfonsi, Yavuz Samet Topcuoglu, Matteo Chiara, Anna Bernasconi","doi":"10.1016/j.jmb.2026.169811","DOIUrl":"10.1016/j.jmb.2026.169811","url":null,"abstract":"<p><p>Zoonotic transmission and viral spillover events pose severe threats to public health, as underscored by recent pandemics. Mitigating these risks requires robust genomic surveillance systems, supported by the growing availability of openly accessible viral genome sequences through dedicated resources such as NCBI Virus and Nextstrain/Pathogens. This wealth of data highlights the need for lightweight, automated computational tools to monitor viral evolution and spread. OpenRecombinHunt extends our previously published RecombinHunt method, originally developed to identify recombinant SARS-CoV-2 lineages, to prioritize recombination patterns in any virus for which a large corpus of sequences is publicly available. Here, we couple RecombinHunt with HaploCoV, a computational workflow that stratifies viral genomes into distinct groups based on high-frequency genomic variants, without requiring a predefined reference nomenclature. We apply this framework to openly-accessible datasets for SARS-CoV-2, Respiratory Syncytial Virus (RSV) A/B, Monkeypox, Zika, Yellow Fever, and hemagglutinin segments of H5N1 Influenza A, reporting interesting recombination patterns. OpenRecombinHunt monthly updates ensure continuous monitoring, providing temporal snapshots of viral genomes with potential mosaic structure. Our method and Web Server have the potential to unlock large-scale automated support to detection of recombination in viruses, in line with current genomic surveillance interests. The Web Server is freely available at http://gmql.eu/openrecombinhunt/.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169811"},"PeriodicalIF":4.5,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ShapeME: A Tool and Web Front-end for De Novo Discovery of Structural Motifs Underpinning Protein-DNA Interactions. ShapeME：一个工具和web前端，用于从头发现支撑蛋白质- dna相互作用的结构基序。

IF 4.5 2区生物学

Journal of Molecular Biology Pub Date : 2026-04-15 DOI: 10.1016/j.jmb.2026.169810

Jeremy W Schroeder, Vivian Ramirez, Michael B Wolfe, Lydia Freddolino

{"title":"ShapeME: A Tool and Web Front-end for De Novo Discovery of Structural Motifs Underpinning Protein-DNA Interactions.","authors":"Jeremy W Schroeder, Vivian Ramirez, Michael B Wolfe, Lydia Freddolino","doi":"10.1016/j.jmb.2026.169810","DOIUrl":"10.1016/j.jmb.2026.169810","url":null,"abstract":"<p><p>Determining where proteins bind a genome is paramount to understanding gene regulation. In addition to DNA sequence motifs, structural motifs (e.g., a narrow minor groove width) determine binding for some proteins (Rohs et al., 2009) [1]. Algorithms using structural features of DNA to predict protein binding exist (Mathelier et al., 2016; Samee et al., 2019; Yang et al., 2019; Pal et al., 2019) [2-5], but a structural motif discovery framework which can be applied to a variety of experimental designs is needed. We present a workflow capable of utilizing virtually any type of data representing sequence coverage or enrichment (e.g. ChIP-seq, RNA-seq, SELEX, etc.) to discover structural motifs with explanatory power for a protein's DNA binding preference. Our approach to motif discovery wraps shape and sequence motif inference into a single tool called ShapeME (github: https://github.com/freddolino-lab/ShapeME.git, web interface: https://seq2fun.dcmb.med.umich.edu/shapeme). Application of ShapeME to ENCODE datasets reveals proteins for which short structural motifs outperform the best PWM for that protein at the JASPAR database, or as identified by the sequence motif elicitation tool STREME. ShapeME is a powerful, versatile framework for inferring structural DNA binding motifs.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169810"},"PeriodicalIF":4.5,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147715440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

GalaxyCDock: Webserver for Covalent Protein-Ligand Binding Mode Prediction. GalaxyCDock：共价蛋白-配体结合模式预测的Webserver。

IF 4.5 2区生物学

Journal of Molecular Biology Pub Date : 2026-04-10 DOI: 10.1016/j.jmb.2026.169807

Sumin Lee, Nuri Jung, Hyeonuk Woo, Jinsol Yang, Chaok Seok

引用次数: 0

plantiSMASH 2.0: Improvements to Detection, Annotation, and Prioritization of Plant Biosynthetic Gene Clusters. plantiSMASH 2.0：改进植物生物合成基因簇的检测、注释和优先排序。

IF 4.5 2区生物学

Journal of Molecular Biology Pub Date : 2026-04-08 DOI: 10.1016/j.jmb.2026.169798

Elena Del Pup, Charlotte Owen, Ziqiang Luo, Hannah E Augustijn, Arjan Draisma, Guy Polturak, Satria A Kautsar, Anne Osbourn, Justin J J van der Hooft, Marnix H Medema

{"title":"plantiSMASH 2.0: Improvements to Detection, Annotation, and Prioritization of Plant Biosynthetic Gene Clusters.","authors":"Elena Del Pup, Charlotte Owen, Ziqiang Luo, Hannah E Augustijn, Arjan Draisma, Guy Polturak, Satria A Kautsar, Anne Osbourn, Justin J J van der Hooft, Marnix H Medema","doi":"10.1016/j.jmb.2026.169798","DOIUrl":"10.1016/j.jmb.2026.169798","url":null,"abstract":"<p><p>Plants produce bioactive compounds as part of their specialized metabolism, with applications in medicine, agriculture, and nutrition. The biosynthesis of a growing number of these specialized metabolites has been found to be encoded in biosynthetic gene clusters (BGCs), creating increasing demand for genome mining tools to automate their detection. plantiSMASH enables the identification of putative plant BGCs through a rule-based approach, available via both command-line and web interfaces. Here, we present plantiSMASH 2.0 (https://plantismash.bioinformatics.nl/), a major update that expands and improves the original framework with revised and additional BGC detection rules (now supporting 12 BGC types), substrate prediction for selected enzyme families, and regulatory analysis through transcription factor binding site detection. The updated plantiSMASH 2.0 database includes 30,423 putative BGCs across 430 genomes. Together, these improvements make plantiSMASH 2.0 a powerful and comprehensive platform for the detection and characterization of plant biosynthetic pathways, supporting and accelerating research in plant specialized metabolism and plant natural product discovery.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169798"},"PeriodicalIF":4.5,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147653425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RNApdbee 3.0: A unified web server for comprehensive RNA secondary structure annotation from 3D coordinates. RNApdbee 3.0：一个统一的web服务器，用于从3D坐标进行全面的RNA二级结构注释。

IF 4.5 2区生物学

Journal of Molecular Biology Pub Date : 2026-04-07 DOI: 10.1016/j.jmb.2026.169795

Jan Pielesiak, Kamil Niznik, Pawel Snioszek, Gabriel Wachowski, Mikolaj Zurawski, Maciej Antczak, Marta Szachniuk, Tomasz Zok

{"title":"RNApdbee 3.0: A unified web server for comprehensive RNA secondary structure annotation from 3D coordinates.","authors":"Jan Pielesiak, Kamil Niznik, Pawel Snioszek, Gabriel Wachowski, Mikolaj Zurawski, Maciej Antczak, Marta Szachniuk, Tomasz Zok","doi":"10.1016/j.jmb.2026.169795","DOIUrl":"10.1016/j.jmb.2026.169795","url":null,"abstract":"<p><p>RNApdbee 3.0 (publicly available at https://rnapdbee.cs.put.poznan.pl/) offers an advanced pipeline for comprehensive RNA structural annotation, integrating 2D and 3D data to build detailed nucleotide interaction networks. It classifies base pairs as canonical or noncanonical using the Leontis-Westhof and Saenger schemes and identifies stacking, base-ribose, base-phosphate, and base-triple interactions. The tool handles incomplete or modified residues, marking missing nucleotides and distinguishing noncanonical base pairs for accurate and effective visualization. Results are provided in standard formats - namely, extended dot-bracket notation, BPSEQ, and CT - and in detailed graphical visualizations. RNApdbee decomposes 2D structures into stems, loops, and single strands and offers flexible pseudoknot encoding. Its unified framework addresses inconsistencies across structural data formats by standardizing all inputs to PDBx/mmCIF and integrating seven widely used annotation tools. Finally, RNApdbee ensures reliable, format-independent, and comprehensive RNA structural annotation and interpretation.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169795"},"PeriodicalIF":4.5,"publicationDate":"2026-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147643553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SiteContext: A Web Server for Protein Binding Site Comparison. SiteContext：一个用于蛋白质结合位点比较的Web服务器。

IF 4.5 2区生物学

Journal of Molecular Biology Pub Date : 2026-04-02 DOI: 10.1016/j.jmb.2026.169791

Hiba Bhatti, Jiadong Yu, Rahul Singh

引用次数: 0

Structural Basis for Non-classical WIN Peptides Recognition by WDR5 WDR5识别非经典WIN多肽的结构基础。

IF 4.5 2区生物学

Journal of Molecular Biology Pub Date : 2026-04-01 Epub Date: 2026-01-30 DOI: 10.1016/j.jmb.2026.169666

Yang Yang , Yan Pan , Qingying Wang , Hao Li , Shuting Zhang , Xuefang Sun , Lingyun Xia , Li Xu , Xuemin Chen

{"title":"Structural Basis for Non-classical WIN Peptides Recognition by WDR5","authors":"Yang Yang , Yan Pan , Qingying Wang , Hao Li , Shuting Zhang , Xuefang Sun , Lingyun Xia , Li Xu , Xuemin Chen","doi":"10.1016/j.jmb.2026.169666","DOIUrl":"10.1016/j.jmb.2026.169666","url":null,"abstract":"<div><div>WD repeat–containing protein 5 (WDR5) is a core scaffolding component of multiple chromatin-modifying complexes that engages diverse partner proteins through a conserved arginine-binding cavity known as the WDR5-interacting (WIN) site. Dysregulation of WDR5 has been implicated in oncogenesis, making the WIN site a promising therapeutic target. Current inhibitor development has primarily focused on mimicking canonical WIN motif interactions, thereby limiting exploration of alternative recognition modes. Here, we present high-resolution crystal structures of two arginine-containing peptide probes that reveal previously unrecognized binding geometries at the WIN pocket. One peptide adopts an extended linear conformation that bridges both the WIN pocket and the adjacent S7 site. The other binds in a reversed, or “<em>trans</em>-WIN,” orientation, in which a C-terminal arginine anchors the WIN site while an upstream proline residue occupies the S7 pocket. Isothermal titration calorimetry confirmed moderate and specific affinities for both peptides. These findings reveal unexpected conformational adaptability of the WIN site and demonstrate that its recognition capacity extends beyond the canonical mode defined by histone H3 and other partner proteins. Collectively, our results expand the structural repertoire of WIN-site recognition and establish a framework for rational design of next-generation WDR5 inhibitors that exploit multi-site engagement and alternative binding topologies.</div></div>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":"438 7","pages":"Article 169666"},"PeriodicalIF":4.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146099548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rising Stars: Adaptation to Environment: From Hormone Signaling to Gene Silencing 冉冉升起的新星：适应环境：从激素信号到基因沉默。

IF 4.5 2区生物学

Journal of Molecular Biology Pub Date : 2026-04-01 Epub Date: 2026-01-29 DOI: 10.1016/j.jmb.2026.169665

Hongwei Guo, Yichuan Wang, Zhenyu Wang, Yuelin Liu

{"title":"Rising Stars: Adaptation to Environment: From Hormone Signaling to Gene Silencing","authors":"Hongwei Guo, Yichuan Wang, Zhenyu Wang, Yuelin Liu","doi":"10.1016/j.jmb.2026.169665","DOIUrl":"10.1016/j.jmb.2026.169665","url":null,"abstract":"<div><div>The survival of plants depends on sensitive and efficient systems that perceive and integrate internal hormonal signals with external environmental cues. Deciphering how plants sense and adapt to changing conditions is a fundamental biological question with direct relevance to crop improvement and sustainable agriculture. Hongwei Guo received training in plant molecular genetics and light signaling during his doctoral studies, then turned to how diverse signal pathways converge to coordinate plant development. In his postdoctoral work, he identified EBF1/2-mediated ubiquitin–proteasome turnover of EIN3 as a core mechanism of ethylene signaling. Building on this foundation, his independent research uncovered additional post-transcriptional strategies: proteolytic cleavage and translational repression that fine-tune ethylene responses. He also established an EIN3-centered regulatory network that integrates hormonal and environmental cues to coordinate diverse physiological processes. A forward genetic screen of ethylene-activated plants unexpectedly extended Dr. Guo’s research to siRNA-based regulation. His group discovered a cytoplasmic “dual-safeguard” mechanism in which impairment of mRNA decay triggers the production of coding-transcript–derived siRNAs (ct-siRNAs) that silence endogenous genes. They further showed that stress-induced 22-nt ct-siRNAs amplify silencing to modulate nitrate assimilation and energy balance under abiotic stress. More recently, Dr. Guo’s laboratory has focused on how plant cells sense physical and chemical changes in their surroundings. They identified two extracellular peptide–receptor complexes as apoplastic pH sensors, and demonstrated that cytoplasmic protein DCP5 senses osmotic stress through phase separation to form new stress granules and rapidly reprogram gene expression. Collectively, Dr. Guo’s research connects hormone signaling, gene regulation, and environmental adaptation.</div></div>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":"438 7","pages":"Article 169665"},"PeriodicalIF":4.5,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146096690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0