Pub Date : 2026-01-06DOI: 10.1016/j.jmb.2026.169632
Caeden D Meade, Biswajit Banerjee, Yuzheng Yang, Arsh Suri, David Hoksza, Loren Dean Williams, Anton S Petrov
RNA secondary structures serve as bridges between RNA sequences and often-unknown three-dimensional structures, offering insights into base pairing, structural motifs, and the overall organization of RNA molecules. To support efficient visualization and editing of these structures, we present Exornata, a modern, web-based tool designed to facilitate generation of detailed and standardized RNA secondary structure modeling. Exornata is an expanded successor to the original XRNA software and is implemented using React and JavaScript/TypeScript technologies to ensure flexibility, interactivity, and high-quality rendering. Users can load, edit, and export RNA structures in multiple supported formats, ranging from conventional SVG to an advanced, in-house-developed JSON schema designed for interoperability with other resources such as R2DT, Traveler, and RiboVision2. The application supports multiple constraint-based editing modes (e.g., nucleotide, strand, helix, and domain) allowing precise and hierarchical manipulation of RNA elements. Exornata supports detailed, interactive visualization of canonical and non-canonical base pairs. It enables researchers to format and annotate structures, and to integrate them into broader bioinformatics pipelines. The tool is open-source, freely available at https://exornata.chemistry.gatech.edu/ and is accompanied by a user guide.
{"title":"Exornata: A Web-based Tool for the Visualization and Editing of RNA Secondary Structures.","authors":"Caeden D Meade, Biswajit Banerjee, Yuzheng Yang, Arsh Suri, David Hoksza, Loren Dean Williams, Anton S Petrov","doi":"10.1016/j.jmb.2026.169632","DOIUrl":"10.1016/j.jmb.2026.169632","url":null,"abstract":"<p><p>RNA secondary structures serve as bridges between RNA sequences and often-unknown three-dimensional structures, offering insights into base pairing, structural motifs, and the overall organization of RNA molecules. To support efficient visualization and editing of these structures, we present Exornata, a modern, web-based tool designed to facilitate generation of detailed and standardized RNA secondary structure modeling. Exornata is an expanded successor to the original XRNA software and is implemented using React and JavaScript/TypeScript technologies to ensure flexibility, interactivity, and high-quality rendering. Users can load, edit, and export RNA structures in multiple supported formats, ranging from conventional SVG to an advanced, in-house-developed JSON schema designed for interoperability with other resources such as R2DT, Traveler, and RiboVision2. The application supports multiple constraint-based editing modes (e.g., nucleotide, strand, helix, and domain) allowing precise and hierarchical manipulation of RNA elements. Exornata supports detailed, interactive visualization of canonical and non-canonical base pairs. It enables researchers to format and annotate structures, and to integrate them into broader bioinformatics pipelines. The tool is open-source, freely available at https://exornata.chemistry.gatech.edu/ and is accompanied by a user guide.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169632"},"PeriodicalIF":4.5,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145931741","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}
Pub Date : 2026-01-06DOI: 10.1016/j.jmb.2026.169631
John Erol Evangelista, Daniel J B Clarke, Anna I Byrd, Shivaramakrishna Srinivasan, Sumana Srinivasan, Mano R Maurya, Sherry L Jenkins, Ido Diamant, Ethan Sanchez, Zhuorui Xie, Stephanie Olaiya, Heesu Kim, Giacomo B Marino, Nasheath Ahmed, Srinivasan Ramachandran, Shankar Subramaniam, Avi Ma'ayan
The NIH Common Fund Data Ecosystem (CFDE) program was established to facilitate data accessibility and interoperability across multiple Common Fund (CF) programs, promote collaborations and accelerate discoveries by combining diverse data types from different CF programs. The CFDE Data Resource Center (DRC) was tasked with developing two web-based portals: an Information Portal to serve information about the CFDE, and a Data Portal to host harmonized metadata and processed data contributed by participating CF Data Coordination Centers (DCCs) and other sources. To achieve these goals, the CFDE DRC developed the CFDE Workbench, a web-based platform that hosts processed data, metadata, tools, use cases, and analyses developed by the CFDE. The Cross-Cut Metadata Model (C2M2) and several other processed data are hosted by the CFDE Workbench, including set libraries (XMTs), Knowledge Graph (KG) assertions, and attribute tables. These processed data formats make information derived from CF programs more findable, accessible, interoperable, and reusable (FAIR), and artificial intelligence (AI)-ready for cross-DCC knowledge discovery. Besides serving data, metadata, and code assets, the CFDE Workbench has also developed several tools that utilize these resources to enable cross-CF-program knowledge discovery use cases. Overall, the CFDE Workbench is a platform that consolidates efforts toward making CF resources harmonized, FAIR, and AI-ready. The CFDE Workbench website is available from https://cfde.cloud.
{"title":"The CFDE Workbench: Integrating Metadata and Processed Data from Common Fund Programs.","authors":"John Erol Evangelista, Daniel J B Clarke, Anna I Byrd, Shivaramakrishna Srinivasan, Sumana Srinivasan, Mano R Maurya, Sherry L Jenkins, Ido Diamant, Ethan Sanchez, Zhuorui Xie, Stephanie Olaiya, Heesu Kim, Giacomo B Marino, Nasheath Ahmed, Srinivasan Ramachandran, Shankar Subramaniam, Avi Ma'ayan","doi":"10.1016/j.jmb.2026.169631","DOIUrl":"10.1016/j.jmb.2026.169631","url":null,"abstract":"<p><p>The NIH Common Fund Data Ecosystem (CFDE) program was established to facilitate data accessibility and interoperability across multiple Common Fund (CF) programs, promote collaborations and accelerate discoveries by combining diverse data types from different CF programs. The CFDE Data Resource Center (DRC) was tasked with developing two web-based portals: an Information Portal to serve information about the CFDE, and a Data Portal to host harmonized metadata and processed data contributed by participating CF Data Coordination Centers (DCCs) and other sources. To achieve these goals, the CFDE DRC developed the CFDE Workbench, a web-based platform that hosts processed data, metadata, tools, use cases, and analyses developed by the CFDE. The Cross-Cut Metadata Model (C2M2) and several other processed data are hosted by the CFDE Workbench, including set libraries (XMTs), Knowledge Graph (KG) assertions, and attribute tables. These processed data formats make information derived from CF programs more findable, accessible, interoperable, and reusable (FAIR), and artificial intelligence (AI)-ready for cross-DCC knowledge discovery. Besides serving data, metadata, and code assets, the CFDE Workbench has also developed several tools that utilize these resources to enable cross-CF-program knowledge discovery use cases. Overall, the CFDE Workbench is a platform that consolidates efforts toward making CF resources harmonized, FAIR, and AI-ready. The CFDE Workbench website is available from https://cfde.cloud.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169631"},"PeriodicalIF":4.5,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145931673","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}
Pub Date : 2026-01-05DOI: 10.1016/j.jmb.2026.169629
Kui Wang, Gang Hu, Sushmita Basu, Lukasz Kurgan
flDPnn3 provides fast and highly accurate predictions of intrinsic disorder. Compared to its earlier versions, it uses a more sophisticated sequence-derived profile as input, covering a modern protein language model and additional predicted disorder functions, while maintaining a similarly small computational footprint. flDPnn3 and over 70 other disorder predictors were independently evaluated on the Disorder-NOX dataset by assessors in CAID3 (3rd Critical Assessment of protein Intrinsic Disorder prediction). A side-by-side comparison in CAID3, including low-sequence-similarity subsets of the CAID3 test data, reveals that our method matches the predictive quality of the best disorder predictors. The runtime analysis shows that flDPnn3 produces results between 3 and 8 times faster than similarly accurate disorder predictors and can be used to produce predictions at the whole-proteome scale. Additionally, flDPnn3 achieves 100% coverage by predicting all proteins, while some other accurate tools fail to predict some proteins. The CAID3 results also demonstrate that flDPnn3 is significantly more accurate than its previous versions, flDPnn and flDPnn2, which were among the top-ranked methods in CAID1 and CAID2, respectively. The flDPnn3's web server supports batch predictions, provides interactive visualization of results, offers a tutorial page, and is available at https://biomine.cs.vcu.edu/servers/flDPnn3/.
{"title":"flDPnn3: Fast and Accurate Prediction of Intrinsic Disorder in Protein Sequences.","authors":"Kui Wang, Gang Hu, Sushmita Basu, Lukasz Kurgan","doi":"10.1016/j.jmb.2026.169629","DOIUrl":"10.1016/j.jmb.2026.169629","url":null,"abstract":"<p><p>flDPnn3 provides fast and highly accurate predictions of intrinsic disorder. Compared to its earlier versions, it uses a more sophisticated sequence-derived profile as input, covering a modern protein language model and additional predicted disorder functions, while maintaining a similarly small computational footprint. flDPnn3 and over 70 other disorder predictors were independently evaluated on the Disorder-NOX dataset by assessors in CAID3 (3rd Critical Assessment of protein Intrinsic Disorder prediction). A side-by-side comparison in CAID3, including low-sequence-similarity subsets of the CAID3 test data, reveals that our method matches the predictive quality of the best disorder predictors. The runtime analysis shows that flDPnn3 produces results between 3 and 8 times faster than similarly accurate disorder predictors and can be used to produce predictions at the whole-proteome scale. Additionally, flDPnn3 achieves 100% coverage by predicting all proteins, while some other accurate tools fail to predict some proteins. The CAID3 results also demonstrate that flDPnn3 is significantly more accurate than its previous versions, flDPnn and flDPnn2, which were among the top-ranked methods in CAID1 and CAID2, respectively. The flDPnn3's web server supports batch predictions, provides interactive visualization of results, offers a tutorial page, and is available at https://biomine.cs.vcu.edu/servers/flDPnn3/.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169629"},"PeriodicalIF":4.5,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145916533","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}
Antiviral peptides (AVPs) offer promising therapeutic potential due to their diverse antiviral mechanisms and favorable toxicity profile. We present DRAVP 2.0, a significantly expanded and carefully curated database comprising 3499 new entries, making a total of 5688 records, representing a 159% increase compared to the previous version. The update incorporates sequences from peer-reviewed literature, patent records, clinical trials, and introduces stapled antiviral peptides, synthetically stabilized molecules with enhanced pharmacokinetic properties. DRAVP 2.0 features rich, multidimensional annotations, including genomic origin data (gene identifiers, chromosomal locations), structural information from UniProt and the Protein Data Bank, physicochemical properties, and experimental validation status. This comprehensive annotation framework enables detailed biological contextualization and supports cross-disciplinary studies across virology, structural biology, and genomics. The platform also offers improved usability with advanced search modes, hierarchical browsing by virus family, and an integrated BLAST tool. Regular biweekly updates and rigorous quality control ensure the database remains accurate and current. Compared to existing resources, DRAVP 2.0 provides broader coverage, enhanced functional annotation, and emphasizes experimentally validated peptides. This robust and user-friendly platform accelerates antiviral peptide discovery and therapeutic development, addressing critical needs posed by emerging and drug-resistant viral pathogens. DRAVP is available online at https://dravp.cpu-bioinfor.org/.
{"title":"DRAVP 2.0: A Curated and Genomically Annotated Database of Antiviral Peptides and Proteins.","authors":"Maryam Nawaz, Huiyuan Yao, Hongyu Liu, Fahad Akhtar, Tianyue Ma, Yunhao Chen, Zichun Hua, Heng Zheng","doi":"10.1016/j.jmb.2026.169628","DOIUrl":"10.1016/j.jmb.2026.169628","url":null,"abstract":"<p><p>Antiviral peptides (AVPs) offer promising therapeutic potential due to their diverse antiviral mechanisms and favorable toxicity profile. We present DRAVP 2.0, a significantly expanded and carefully curated database comprising 3499 new entries, making a total of 5688 records, representing a 159% increase compared to the previous version. The update incorporates sequences from peer-reviewed literature, patent records, clinical trials, and introduces stapled antiviral peptides, synthetically stabilized molecules with enhanced pharmacokinetic properties. DRAVP 2.0 features rich, multidimensional annotations, including genomic origin data (gene identifiers, chromosomal locations), structural information from UniProt and the Protein Data Bank, physicochemical properties, and experimental validation status. This comprehensive annotation framework enables detailed biological contextualization and supports cross-disciplinary studies across virology, structural biology, and genomics. The platform also offers improved usability with advanced search modes, hierarchical browsing by virus family, and an integrated BLAST tool. Regular biweekly updates and rigorous quality control ensure the database remains accurate and current. Compared to existing resources, DRAVP 2.0 provides broader coverage, enhanced functional annotation, and emphasizes experimentally validated peptides. This robust and user-friendly platform accelerates antiviral peptide discovery and therapeutic development, addressing critical needs posed by emerging and drug-resistant viral pathogens. DRAVP is available online at https://dravp.cpu-bioinfor.org/.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169628"},"PeriodicalIF":4.5,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145916539","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}
LIMK1 and LIMK2, key regulators of cytoskeleton dynamics, are notoriously difficult to produce and purify in quantities sufficient for conventional biochemical studies, yet they are promising therapeutic targets due to their role in actin filament turnover and microtubule remodeling. To overcome these limitations, we developed a microscale thermophoresis (MST)-based thermodynamic assay as a proof-of-concept to study LIMK–inhibitor interactions directly in HEK293 cell lysates overexpressing fluorescent miRFP670-LIMK fusion proteins, completely bypassing protein purification.
Dissociation constants (Kd) were measured across multiple temperatures and analyzed by van’t Hoff plots, yielding highly linear correlations (r2 = 0.958–0.999). LIMK1 and its kinase domain (Kin1) showed comparable binding behavior to TH-257 and LX7101 (ΔG37°C = –10.3 ± 0.4 kcal mol−1), whereas LIMK2 interactions were significantly weaker (ΔG37°C lower by ∼1.5 kcal mol−1). Binding was enthalpy-driven, with entropy opposing complex formation, highlighting opportunities for rational optimization of inhibitors.
This work establishes MST as a user-friendly, purification-free platform for deriving protein–ligand thermodynamics directly in cell lysates, providing a versatile proof-of-concept approach for studying challenging targets and guiding the development of therapeutically relevant inhibitors.
{"title":"Microscale Thermophoresis for Thermodynamic Analysis: A Proof-of-Concept Study on LIMK Inhibitors","authors":"Solweig Chartier , Bérengère Claude , Rouba Nasreddine , Pierre Soule , Alexandra Launay , Mélanie Rapeto , Elodie Villalonga-Rosso , Béatrice Vallée , Muriel Sebban , Gaël Coadou , Reine Nehmé","doi":"10.1016/j.jmb.2025.169621","DOIUrl":"10.1016/j.jmb.2025.169621","url":null,"abstract":"<div><div>LIMK1 and LIMK2, key regulators of cytoskeleton dynamics, are notoriously difficult to produce and purify in quantities sufficient for conventional biochemical studies, yet they are promising therapeutic targets due to their role in actin filament turnover and microtubule remodeling. To overcome these limitations, we developed a microscale thermophoresis (MST)-based thermodynamic assay as a proof-of-concept to study LIMK–inhibitor interactions directly in HEK293 cell lysates overexpressing fluorescent miRFP670-LIMK fusion proteins, completely bypassing protein purification.</div><div>Dissociation constants (<em>K<sub>d</sub></em>) were measured across multiple temperatures and analyzed by van’t Hoff plots, yielding highly linear correlations (<em>r</em><sup>2</sup> = 0.958–0.999). LIMK1 and its kinase domain (Kin1) showed comparable binding behavior to TH-257 and LX7101 (Δ<em>G</em><sub>37°C</sub> = –10.3 ± 0.4 kcal mol<sup>−1</sup>), whereas LIMK2 interactions were significantly weaker (Δ<em>G</em><sub>37°C</sub> lower by ∼1.5 kcal mol<sup>−1</sup>). Binding was enthalpy-driven, with entropy opposing complex formation, highlighting opportunities for rational optimization of inhibitors.</div><div>This work establishes MST as a user-friendly, purification-free platform for deriving protein–ligand thermodynamics directly in cell lysates, providing a versatile proof-of-concept approach for studying challenging targets and guiding the development of therapeutically relevant inhibitors.</div></div>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":"438 5","pages":"Article 169621"},"PeriodicalIF":4.5,"publicationDate":"2026-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145909854","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}
Pub Date : 2026-01-02DOI: 10.1016/j.jmb.2025.169618
Dali Li
As a professor of biomedicine in the School of Life Sciences at East China Normal University (ECNU), I am dedicated to developing advanced genome editing technologies for disease modeling and precise gene therapy. My foundational training at Hunan Normal University and Texas A&M University cultivated a deep interest in using engineered cellular and animal models to understand human diseases. Since 2013, my laboratory at ECNU has pioneered the use of TALEN and CRISPR/Cas9 for the rapid generation of knockout mouse and rat models for disease studies. Once stepped in genome editing field, I shifted my focus to advancing editing tools and developing gene therapy strategies for genetic disorders and cancer. My team has developed a suite of high-performance base editors for nuclear DNA, mitochondrial DNA, and RNA, broadening editing capabilities while enhancing precision and safety. Leveraging these technologies, we have designed several therapeutic strategies that have shown efficacy in cellular and animal models of genetic diseases. Through collaborative efforts, we have successfully translated genome editing into clinical applications, contributing to the treatment of patients with β-thalassemia. Additionally, we have developed a non-viral, site-specific CAR-T platform for lymphoma therapy. Looking forward, I aim to develop the next generation of long-fragment, site-specific integration technologies and accelerate clinical translation to bring transformative cures to more patients.
{"title":"Rising Star Engineering the Genome for Curative Futures","authors":"Dali Li","doi":"10.1016/j.jmb.2025.169618","DOIUrl":"10.1016/j.jmb.2025.169618","url":null,"abstract":"<div><div>As a professor of biomedicine in the School of Life Sciences at East China Normal University (ECNU), I am dedicated to developing advanced genome editing technologies for disease modeling and precise gene therapy. My foundational training at Hunan Normal University and Texas A&M University cultivated a deep interest in using engineered cellular and animal models to understand human diseases. Since 2013, my laboratory at ECNU has pioneered the use of TALEN and CRISPR/Cas9 for the rapid generation of knockout mouse and rat models for disease studies. Once stepped in genome editing field, I shifted my focus to advancing editing tools and developing gene therapy strategies for genetic disorders and cancer. My team has developed a suite of high-performance base editors for nuclear DNA, mitochondrial DNA, and RNA, broadening editing capabilities while enhancing precision and safety. Leveraging these technologies, we have designed several therapeutic strategies that have shown efficacy in cellular and animal models of genetic diseases. Through collaborative efforts, we have successfully translated genome editing into clinical applications, contributing to the treatment of patients with <em>β</em>-thalassemia. Additionally, we have developed a non-viral, site-specific CAR-T platform for lymphoma therapy. Looking forward, I aim to develop the next generation of long-fragment, site-specific integration technologies and accelerate clinical translation to bring transformative cures to more patients.</div></div>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":"438 5","pages":"Article 169618"},"PeriodicalIF":4.5,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145899115","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}
Goadsporin is one of linear azole-containing peptides (LAPs) that form a subgroup within ribosomally synthesized and post-translationally modified peptides (RiPPs). It contains two dehydroalanine residues formed through the action of two enzymes, GodF and GodG, in a two-step process involving serine O-glutamylation followed by elimination. Here, we report the X-ray crystal structure of GodF, which catalyzes the tRNA-dependent glutamylation of target serine residues, resolved at a 2.34-Å resolution. Although GodF exhibits low homology at the primary sequence level, its overall structure closely resembles that of TbtB, a tRNAGlu-dependent enzyme involved in thiopeptide biosynthesis, as well as the O-glutamylation domains of NisB and MibB, which serve as dehydroalanine synthases in lanthipeptide biosynthesis. The residues and structural elements forming the active site are well-aligned among these enzymes, while regions outside the active site are poorly conserved. Like TbtB, GodF features a coiled-coil subdomain at its N-terminus, and AlphaFold3 predicts this region plays a key role in recognizing the substrate tRNAGlu. GodF also contains a typical RiPP recognition element (RRE) motif; however, the spatial arrangement of the secondary structural elements comprising this motif differs notably from those in other O-glutamylating enzymes. These structural characteristics of GodF highlight the diversity of substrate-binding pockets among RiPP-modifying enzymes, reflecting the variability in their substrate peptides and the necessity to accommodate distinct conformational and physicochemical properties.
{"title":"Structural Analysis of GodF, an O-glutamylation Enzyme Involved in Goadsporin Biosynthesis","authors":"Akiko Shimizu-Ibuka , Yoshiki Kato , Shumpei Asamizu , Hiroyasu Onaka","doi":"10.1016/j.jmb.2025.169619","DOIUrl":"10.1016/j.jmb.2025.169619","url":null,"abstract":"<div><div>Goadsporin is one of linear azole-containing peptides (LAPs) that form a subgroup within ribosomally synthesized and post-translationally modified peptides (RiPPs). It contains two dehydroalanine residues formed through the action of two enzymes, GodF and GodG, in a two-step process involving serine <em>O</em>-glutamylation followed by elimination. Here, we report the X-ray crystal structure of GodF, which catalyzes the tRNA-dependent glutamylation of target serine residues, resolved at a 2.34-Å resolution. Although GodF exhibits low homology at the primary sequence level, its overall structure closely resembles that of TbtB, a tRNA<sup>Glu</sup>-dependent enzyme involved in thiopeptide biosynthesis, as well as the <em>O</em>-glutamylation domains of NisB and MibB, which serve as dehydroalanine synthases in lanthipeptide biosynthesis. The residues and structural elements forming the active site are well-aligned among these enzymes, while regions outside the active site are poorly conserved. Like TbtB, GodF features a coiled-coil subdomain at its N-terminus, and AlphaFold3 predicts this region plays a key role in recognizing the substrate tRNA<sup>Glu</sup>. GodF also contains a typical RiPP recognition element (RRE) motif; however, the spatial arrangement of the secondary structural elements comprising this motif differs notably from those in other <em>O</em>-glutamylating enzymes. These structural characteristics of GodF highlight the diversity of substrate-binding pockets among RiPP-modifying enzymes, reflecting the variability in their substrate peptides and the necessity to accommodate distinct conformational and physicochemical properties.</div></div>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":"438 5","pages":"Article 169619"},"PeriodicalIF":4.5,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145888414","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}
Pub Date : 2025-12-30DOI: 10.1016/j.jmb.2025.169620
Anja Conev, Suhail A Islam, Ifigenia Tsitsa, Alessia David, Michael J E Sternberg
UniProt is a central repository of protein sequences and annotations, with entries being updated several times a year as new sequencing evidence is collected. By contrast, protein structure resources often evolve at a different pace. The AlphaFold database remained unchanged for four years, until September 2025, during which time nearly 3% of the associated sequences underwent revisions in UniProt. In a range of bioinformatics tasks, protein structure data is paired with sequence annotations from UniProt. Mapping annotations to outdated structure files can lead to errors in downstream analysis. While this concern has been addressed for experimental structures, efforts for the modeled structures are lacking. 3DSeqCheck is a lightweight web tool that enables quick comparison of the sequence of modeled and experimental structures to the latest UniProt entries. 3DSeqCheck provides an interactive visual panel of the alignment and the comparison of the residue numbering and can be accessed freely at: https://missense3d.bc.ic.ac.uk/3dseqcheck and https://github.ic.ac.uk/ImperialCollegeLondon/check3Dseq.
{"title":"3DSeqCheck: A Web-based Tool for Verifying Sequence Consistency Between a 3D Structure File and the Corresponding UniProt Entry.","authors":"Anja Conev, Suhail A Islam, Ifigenia Tsitsa, Alessia David, Michael J E Sternberg","doi":"10.1016/j.jmb.2025.169620","DOIUrl":"10.1016/j.jmb.2025.169620","url":null,"abstract":"<p><p>UniProt is a central repository of protein sequences and annotations, with entries being updated several times a year as new sequencing evidence is collected. By contrast, protein structure resources often evolve at a different pace. The AlphaFold database remained unchanged for four years, until September 2025, during which time nearly 3% of the associated sequences underwent revisions in UniProt. In a range of bioinformatics tasks, protein structure data is paired with sequence annotations from UniProt. Mapping annotations to outdated structure files can lead to errors in downstream analysis. While this concern has been addressed for experimental structures, efforts for the modeled structures are lacking. 3DSeqCheck is a lightweight web tool that enables quick comparison of the sequence of modeled and experimental structures to the latest UniProt entries. 3DSeqCheck provides an interactive visual panel of the alignment and the comparison of the residue numbering and can be accessed freely at: https://missense3d.bc.ic.ac.uk/3dseqcheck and https://github.ic.ac.uk/ImperialCollegeLondon/check3Dseq.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169620"},"PeriodicalIF":4.5,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145888363","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}
Pub Date : 2025-12-26DOI: 10.1016/j.jmb.2025.169613
Sri Devan Appasamy, Sreenath Nair, Dare Kayode Lawal, Ivanna Pidruchna, Adam Midlik, Grisell Díaz Leines, Balakumaran Balasubramaniyan, Marcelo Querino Lima Afonso, Jennifer Fleming, Sameer Velankar
PDBe-KB Complexes is a set of webpages that aggregate experimentally determined macromolecular assemblies into unique complex-level records within the Protein Data Bank in Europe Knowledge Base framework. Each unique complex identifier unifies equivalent biological assemblies from the PDB that represent the same macromolecular complex, consolidating information on component identity, stoichiometry, symmetry, ligands, and PISA-derived assembly properties within a consistent framework. Relationships between complexes are established by comparing their compositions, capturing both subcomplexes that form part of larger ones with additional components, or higher-order complexes formed by repeating identical subunits. The current release of PDBe-KB Complexes includes over 100,000 unique complex compositions encompassing protein, nucleic acid, and mixed complexes. The SARS-CoV-2 spike protein complex serves as a representative case study, demonstrating how aggregation across hundreds of assemblies from different PDB entries reveals conformational diversity, ligand interactions, and antibody binding beyond traditional PDB entry-centric views. PDBe-KB Complexes provides a comprehensive foundation for comparative and functional analyses of macromolecular complexes across the PDB, supporting fundamental and translational research and education across life sciences. Users can explore PDBe-KB Complexes webpages; for example, the SARS-CoV-2 spike complex can be accessed via any corresponding PDB entries such as 9CXE at https://www.ebi.ac.uk/pdbe/pdbe-kb/complexes/9cxe.
{"title":"PDBe-KB Complexes: Enabling Functional Insight from Macromolecular Complexes in the PDB.","authors":"Sri Devan Appasamy, Sreenath Nair, Dare Kayode Lawal, Ivanna Pidruchna, Adam Midlik, Grisell Díaz Leines, Balakumaran Balasubramaniyan, Marcelo Querino Lima Afonso, Jennifer Fleming, Sameer Velankar","doi":"10.1016/j.jmb.2025.169613","DOIUrl":"10.1016/j.jmb.2025.169613","url":null,"abstract":"<p><p>PDBe-KB Complexes is a set of webpages that aggregate experimentally determined macromolecular assemblies into unique complex-level records within the Protein Data Bank in Europe Knowledge Base framework. Each unique complex identifier unifies equivalent biological assemblies from the PDB that represent the same macromolecular complex, consolidating information on component identity, stoichiometry, symmetry, ligands, and PISA-derived assembly properties within a consistent framework. Relationships between complexes are established by comparing their compositions, capturing both subcomplexes that form part of larger ones with additional components, or higher-order complexes formed by repeating identical subunits. The current release of PDBe-KB Complexes includes over 100,000 unique complex compositions encompassing protein, nucleic acid, and mixed complexes. The SARS-CoV-2 spike protein complex serves as a representative case study, demonstrating how aggregation across hundreds of assemblies from different PDB entries reveals conformational diversity, ligand interactions, and antibody binding beyond traditional PDB entry-centric views. PDBe-KB Complexes provides a comprehensive foundation for comparative and functional analyses of macromolecular complexes across the PDB, supporting fundamental and translational research and education across life sciences. Users can explore PDBe-KB Complexes webpages; for example, the SARS-CoV-2 spike complex can be accessed via any corresponding PDB entries such as 9CXE at https://www.ebi.ac.uk/pdbe/pdbe-kb/complexes/9cxe.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169613"},"PeriodicalIF":4.5,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145848678","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}
Pub Date : 2025-12-24DOI: 10.1016/j.jmb.2025.169615
Evgeny V. Mymrikov , Christophe Wirth , Jonas I. Heinicke , Julian Goll , Bianca A. Kern , Christoph Steck , Anastasiia K. Iaroslavtceva , Tobias Mühlethaler , Anna Köttgen , Carola Hunte
The renal solute carrier URAT1 (SLC22A12) is essential for urate homeostasis, with loss-of-function linked to renal hypouricemia, nephrolithiasis and lower gout risk. URAT1 function depends on binding the multi-PDZ domain scaffold protein PDZK1 (NHERF3), with a similar role suggested for the related NHERF1. The molecular basis of these interactions remains poorly understood. Using fluorescence anisotropy, we show that full-length human PDZK1 binds the C-terminal peptide of URAT1 with high affinity (KD 170 nM), unlike NHERF1 (KD > 70 µM). The PDZ1 domain of PDZK1 alone is sufficient for high-affinity binding (KD 160 nM), while PDZ4 provides a secondary site (KD 1.35 µM), with both interactions characterized by rapid kinetics. Gel filtration shows that PDZK1 can bind two URAT1 peptides. X-ray structures of individual PDZ domains from PDZK1 and NHERF1 complexed with the URAT1 peptide reveal the underlying molecular basis for selectivity and broad affinity range. Murine Pdzk1 and Nherf1 bind Urat1 with high affinity indicating species-specific interactions. These data provide insights into URAT1 regulation by PDZ scaffold proteins with relevance for understanding urate homeostasis regulation and related disorders.
{"title":"Molecular Determinants of Selective and High-affinity Binding of the Scaffold Protein PDZK1 to the Urate Transporter URAT1","authors":"Evgeny V. Mymrikov , Christophe Wirth , Jonas I. Heinicke , Julian Goll , Bianca A. Kern , Christoph Steck , Anastasiia K. Iaroslavtceva , Tobias Mühlethaler , Anna Köttgen , Carola Hunte","doi":"10.1016/j.jmb.2025.169615","DOIUrl":"10.1016/j.jmb.2025.169615","url":null,"abstract":"<div><div>The renal solute carrier URAT1 (SLC22A12) is essential for urate homeostasis, with loss-of-function linked to renal hypouricemia, nephrolithiasis and lower gout risk. URAT1 function depends on binding the multi-PDZ domain scaffold protein PDZK1 (NHERF3), with a similar role suggested for the related NHERF1. The molecular basis of these interactions remains poorly understood. Using fluorescence anisotropy, we show that full-length human PDZK1 binds the C-terminal peptide of URAT1 with high affinity (<em>K</em><sub>D</sub> 170 nM), unlike NHERF1 (<em>K</em><sub>D</sub> > 70 µM). The PDZ1 domain of PDZK1 alone is sufficient for high-affinity binding (<em>K</em><sub>D</sub> 160 nM), while PDZ4 provides a secondary site (<em>K</em><sub>D</sub> 1.35 µM), with both interactions characterized by rapid kinetics. Gel filtration shows that PDZK1 can bind two URAT1 peptides. X-ray structures of individual PDZ domains from PDZK1 and NHERF1 complexed with the URAT1 peptide reveal the underlying molecular basis for selectivity and broad affinity range. Murine Pdzk1 and Nherf1 bind Urat1 with high affinity indicating species-specific interactions. These data provide insights into URAT1 regulation by PDZ scaffold proteins with relevance for understanding urate homeostasis regulation and related disorders.</div></div>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":"438 5","pages":"Article 169615"},"PeriodicalIF":4.5,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145843309","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}
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