Journal of Molecular Biology最新文献_第9页

Understanding the role of tRNA modifications in UGA recoding as selenocysteine in eukaryotes. 了解真核生物中 tRNA 修饰在 UGA 重编码为硒半胱氨酸过程中的作用。

IF 4.7 2区生物学

Journal of Molecular Biology Pub Date : 2025-02-21 DOI: 10.1016/j.jmb.2025.169017

Laurent Chavatte, Lukas Lange, Ulrich Schweizer, Théophile Ohlmann

{"title":"Understanding the role of tRNA modifications in UGA recoding as selenocysteine in eukaryotes.","authors":"Laurent Chavatte, Lukas Lange, Ulrich Schweizer, Théophile Ohlmann","doi":"10.1016/j.jmb.2025.169017","DOIUrl":"10.1016/j.jmb.2025.169017","url":null,"abstract":"<p><p>Selenocysteine (Sec), the 21st proteogenic amino acid, is a key component of selenoproteins, where it performs critical roles in redox reactions. Sec incorporation during translation is unique and highly sensitive to selenium levels. Encoded by the UGA codon, typically a termination signal, its insertion necessitates the presence of a selenocysteine insertion sequence (SECIS) within the 3' untranslated region (UTR) of selenoprotein mRNAs. This SECIS element orchestrates the recruitment of specialized molecular factors, including SECISBP2, the unique tRNA<sup>[Ser]Sec</sup>, and its dedicated elongation factor, EEFSEC. The extended variable arm of tRNA<sup>[Ser]Sec</sup> permits its specific recognition by EEFSEC. While the structure of the ribosome-bound complex is known, the precise mechanism by which EEFSEC-tRNA<sup>[Ser]Sec</sup> recodes UGA in the presence of SECIS and SECISBP2 remains unclear. tRNA<sup>[Ser]Sec</sup> has relatively few epitranscriptomic modifications, but those at the anticodon loop are crucial. Key modifications include N6-isopentenyladenosine (i6A) at position 37 and two forms of 5-methoxycarbonylmethyluridine (mcm<sup>5</sup>U and mcm<sup>5</sup>U<sub>m</sub>) at position 34. The ratio of these isoforms varies with tissue type and selenium levels, influencing mRNA-specific Sec recoding. A C65G mutation in the acceptor stem, identified in patients, disrupts these modifications at position 34, impairing selenoprotein synthesis. This highlights the essential role of wobble position modifications in anticodon function. tRNA<sup>[Ser]Sec</sup> exemplifies the complex regulation of UGA codon recoding and underscores the interplay of structural and epitranscriptomic factors in selenoprotein translation.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169017"},"PeriodicalIF":4.7,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143481847","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

PUNCH: An Interactive Web Server for Predicting Intrinsically Disordered Regions in Protein Sequences. PUNCH：用于预测蛋白质序列内在无序区域的交互式Web服务器。

IF 4.7 2区生物学

Journal of Molecular Biology Pub Date : 2025-02-21 DOI: 10.1016/j.jmb.2025.169018

Di Meng, Gianluca Pollastri

引用次数: 0

Heligeom: A web resource to generate, analyze, and visualize filament architectures based on pairwise association geometries of biological macromolecules. Heligeom：一个基于生物大分子成对关联几何的生成、分析和可视化纤维结构的网络资源。

IF 4.7 2区生物学

Journal of Molecular Biology Pub Date : 2025-02-19 DOI: 10.1016/j.jmb.2025.169019

Hubert Santuz, Benoist Laurent, Charles H Robert, Chantal Prévost

{"title":"Heligeom: A web resource to generate, analyze, and visualize filament architectures based on pairwise association geometries of biological macromolecules.","authors":"Hubert Santuz, Benoist Laurent, Charles H Robert, Chantal Prévost","doi":"10.1016/j.jmb.2025.169019","DOIUrl":"https://doi.org/10.1016/j.jmb.2025.169019","url":null,"abstract":"<p><p>At the subcellular level, macromolecules self-assemble to form molecular machinery in which the assembly modes play critical roles: the structural integrity of cell walls that allows mechanical growth, the maintenance and repair of the genetic material, membrane flow control, protein chaperoning, and ATP production, to cite just a few examples. As molecular modeling expands its scope to such systems, structural biologists are faced with the difficulty of understanding the structure and dynamics of these supramolecular assemblies. We present Heligeom, a webserver that offers a simple and efficient means for analyzing and constructing oligomeric assemblies based on user-provided structures of two interacting units. The input 3D coordinates may result from structure determination, simulations, docking trials, or deep-learning tools such as AlphaFold. For a given interface, Heligeom outputs the mathematical helical parameters of the corresponding oligomeric form, including axis, pitch, handedness, number of monomers per turn, etc. The server also allows leveraging these parameters to construct oligomers of specified size, visualizing them interactively, and downloading them as PDB files. For subunits (protomers) having multiple interaction geometries, the different interfaces and their global assembly geometry can be visualized and compared. Heligeom thus allows explicitly linking protomer-protomer interfaces to the oligomeric architecture, illuminating possible sources of plasticity in protein filaments such as mutations or thermal, mechanical, or chemical perturbations. Heligeom thus constitutes an intuitive tool to accompany integrative modeling of oligomeric filamentous assemblies. Examples of its application at different structural levels are presented. Heligeom webserver can be accessed at https://heligeom.galaxy.ibpc.fr.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169019"},"PeriodicalIF":4.7,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143708022","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

Biophysical Aspect of Assembly and Regulation of Nuclear Bodies Scaffolded by Architectural RNA 结构RNA支架核体组装和调控的生物物理方面。

IF 4.7 2区生物学

Journal of Molecular Biology Pub Date : 2025-02-18 DOI: 10.1016/j.jmb.2025.169016

Tetsuya Yamamoto , Tomohiro Yamazaki , Kensuke Ninomiya , Shinichi Nakagawa , Tetsuro Hirose

引用次数: 0

Functional Differences Between Neuronal and Non-neuronal Isoforms of Drebrin 神经型和非神经型drebrin的功能差异。

IF 4.7 2区生物学

Journal of Molecular Biology Pub Date : 2025-02-17 DOI: 10.1016/j.jmb.2025.169015

Sargis Srapyan , Mikayel Mkrtchyan , Renaud Berlemont , Elena E. Grintsevich

{"title":"Functional Differences Between Neuronal and Non-neuronal Isoforms of Drebrin","authors":"Sargis Srapyan , Mikayel Mkrtchyan , Renaud Berlemont , Elena E. Grintsevich","doi":"10.1016/j.jmb.2025.169015","DOIUrl":"10.1016/j.jmb.2025.169015","url":null,"abstract":"<div><div>Actin cytoskeleton is vital for neuronal function. Drebrin is a key F-actin binding protein in neurons which is linked to the filaments’ stabilization. As mammalian brain develops, drebrin expression pattern switches from non-neuronal (drebrin E, <u>E</u>mbryonic) to neuron-specific isoform (drebrin A, <u>A</u>dult), but the evolutionary need for such a switch is enigmatic. Prior <em>in cellulo</em> and <em>in vivo</em> work suggested a non-redundant role of drebrin isoforms in neuronal development and function, however, molecular level understanding of it is lacking. Here we used mutagenesis, bulk solution assays, and time-lapse TIRF microscopy to probe for functional differences between drebrin isoforms. We found that drebrin A and E are functionally distinct and differ in their ability to inhibit F-actin depolymerization. We showed that both isoforms act as permissive cappers of the barbed end of actin, however, drebrin A has a significantly stronger capping activity, compared to that of the non-neuronal drebrin E. Probing for the molecular level insights on the observed differences revealed that the adult-specific exon in neuronal drebrin A contains an actin binding interface which enhances its permissive capping activity. Strikingly, F-actin decoration by neuronal drebrin A confers significantly stronger resistance to cofilin-mediated severing compared to that of drebrin E. Our results provide novel molecular level insights on functional differences between drebrin isoforms, which deepen our understanding of cytoskeletal regulation in the neuronal context. Our results also helps interpreting the previously reported data related to the silencing or knockout of the neuronal drebrin isoform.</div></div>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":"437 9","pages":"Article 169015"},"PeriodicalIF":4.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143456375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Stabilizing Mutations Enhance Evolvability of BlaC β-lactamase by Widening the Mutational Landscape 稳定突变通过扩大突变景观增强了BlaC β-内酰胺酶的可进化性。

IF 4.7 2区生物学

Journal of Molecular Biology Pub Date : 2025-02-17 DOI: 10.1016/j.jmb.2025.168999

Marko Radojković, Anouk Bruggeling van Ingen, Monika Timmer, Marcellus Ubbink

{"title":"Stabilizing Mutations Enhance Evolvability of BlaC β-lactamase by Widening the Mutational Landscape","authors":"Marko Radojković, Anouk Bruggeling van Ingen, Monika Timmer, Marcellus Ubbink","doi":"10.1016/j.jmb.2025.168999","DOIUrl":"10.1016/j.jmb.2025.168999","url":null,"abstract":"<div><div>Antimicrobial resistance is fueled by the rapid evolution of β-lactamases. However, a gain of new enzyme activity often comes at the expense of reduced protein stability. This evolutionary constraint is often overcome by the acquisition of stabilizing mutations that compensate for the loss of stability invoked by new function mutations. Here, we report three stabilizing mutations (I105F, H184R, and V263I) in BlaC, a serine β-lactamase from <em>Mycobacterium tuberculosis</em>. Using a severely destabilized variant as a template for random mutagenesis and selection, these three mutations emerged together and were able to fully restore resistance toward the antibiotic carbenicillin. <em>In vitro</em> characterization shows that all three mutations increase chemical and thermal stability, which leads to elevated protein levels in the periplasm of <em>Escherichia coli</em>. We demonstrate that the introduction of stabilizing mutations substantially enhances the evolvability of the enzyme. These findings illustrate the important role of stabilizing mutations in enzyme evolution by alleviating function-stability trade-offs and broadening the accessible evolutionary landscape.</div></div>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":"437 9","pages":"Article 168999"},"PeriodicalIF":4.7,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143456377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CAZyme3D: A Database of 3D Structures for Carbohydrate-active Enzymes. CAZyme3D：碳水化合物活性酶的三维结构数据库。

IF 4.7 2区生物学

Journal of Molecular Biology Pub Date : 2025-02-16 DOI: 10.1016/j.jmb.2025.169001

N R Siva Shanmugam, Yanbin Yin

{"title":"CAZyme3D: A Database of 3D Structures for Carbohydrate-active Enzymes.","authors":"N R Siva Shanmugam, Yanbin Yin","doi":"10.1016/j.jmb.2025.169001","DOIUrl":"10.1016/j.jmb.2025.169001","url":null,"abstract":"<p><p>CAZymes (Carbohydrate Active EnZymes) degrade, synthesize, and modify all complex carbohydrates on Earth. CAZymes are extremely important to research in human health, nutrition, gut microbiome, bioenergy, plant disease, and global carbon recycling. Current CAZyme annotation tools are all based on sequence similarity. A more powerful approach is to detect protein structural similarity between query proteins and known CAZymes indicative of distant homology. Here, we developed CAZyme3D (https://pro.unl.edu/CAZyme3D/) to fill the research gap that no dedicated 3D structure databases are currently available for CAZymes. CAZyme3D contains a total of 870,740 AlphaFold predicted 3D structures (named Whole dataset). A subset of CAZymes 3D structures from 188,574 nonredundant sequences (named ID50 dataset) were subject to structural similarity-based clustering analyses. Such clustering allowed us to organize all CAZyme structures using a hierarchical classification, which includes existing levels defined by the CAZy database (class, clan, family, subfamily) and newly defined levels (subclasses, structural cluster [SC] groups, and SCs). The inter-family structural clustering successfully grouped CAZy families and clans with the same structural folds in the same subclasses. The intra-family structural clustering classified structurally similar CAZymes into SCs, which were further classified into SC groups. SCs and SC groups differed from sequence similarity-based CAZy subfamilies. With CAZyme structures as the search database, we created job submission pages, where users can submit query protein sequences or PDB structures for a structural similarity search. CAZyme3D will be a useful new tool to assist the discovery of novel CAZymes by providing a comprehensive database of CAZyme 3D structures.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169001"},"PeriodicalIF":4.7,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143439666","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

Dockground: The Resource Expands to Protein-RNA Interactome. 背景：资源扩展到蛋白质- rna相互作用组。

IF 4.7 2区生物学

Journal of Molecular Biology Pub Date : 2025-02-15 DOI: 10.1016/j.jmb.2025.169014

Keeley W Collins, Matthew M Copeland, Petras J Kundrotas, Ilya A Vakser

{"title":"Dockground: The Resource Expands to Protein-RNA Interactome.","authors":"Keeley W Collins, Matthew M Copeland, Petras J Kundrotas, Ilya A Vakser","doi":"10.1016/j.jmb.2025.169014","DOIUrl":"10.1016/j.jmb.2025.169014","url":null,"abstract":"<p><p>RNA is a master regulator of cellular processes and will bind to many different proteins throughout its life cycle. Dysregulation of RNA and RNA-binding proteins can lead to various diseases, including cancer. To better understand molecular mechanisms of the cellular processes, it is important to characterize protein-RNA interactions at the structural level. There is a lack of experimental structures available for protein-RNA complexes due to the RNA inherent flexibility, which complicates the experimental structure determination. The scarcity of structures can be made up for with computational modeling. Dockground is a resource for development and benchmarking of structure-based modeling of protein interactions. It contains datasets focusing on different aspects of protein recognition. The foundation of all the datasets is the database of experimentally determined protein complexes, which previously contained only protein-protein assemblies. To further expand the utility of the Dockground resource, we extended the database to protein-RNA interactions. The new functionalities are available on the Dockground website at https://dockground.compbio.ku.edu/. The database can be searched using a number of criteria, including removal of redundancies at various sequence and structure similarity thresholds. The database updates with new structures from the Protein Data Bank on a weekly basis.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"169014"},"PeriodicalIF":4.7,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431986","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

Identifying RNA-small Molecule Binding Sites Using Geometric Deep Learning with Language Models 使用语言模型的几何深度学习识别rna -小分子结合位点。

IF 4.7 2区生物学

Journal of Molecular Biology Pub Date : 2025-02-15 DOI: 10.1016/j.jmb.2025.169010

Weimin Zhu, Xiaohan Ding, Hong-Bin Shen, Xiaoyong Pan

{"title":"Identifying RNA-small Molecule Binding Sites Using Geometric Deep Learning with Language Models","authors":"Weimin Zhu, Xiaohan Ding, Hong-Bin Shen, Xiaoyong Pan","doi":"10.1016/j.jmb.2025.169010","DOIUrl":"10.1016/j.jmb.2025.169010","url":null,"abstract":"<div><div>RNAs are emerging as promising therapeutic targets, yet identifying small molecules that bind to them remains a significant challenge in drug discovery. This underscores the crucial role of computational modeling in predicting RNA-small molecule binding sites. However, accurate and efficient computational methods for identifying these interactions are still lacking. Recently, advances in large language models (LLMs), previously successful in DNA and protein research, have spurred the development of RNA-specific LLMs. These models leverage vast unlabeled RNA sequences to autonomously learn semantic representations with the goal of enhancing downstream tasks, particularly those constrained by limited annotated data. Here, we develop RNABind, an embedding-informed geometric deep learning framework to detect RNA-small molecule binding sites from RNA structures. RNABind integrates RNA LLMs into advanced geometric deep learning networks, which encodes both RNA sequence and structure information. To evaluate RNABind, we first compile the largest RNA-small molecule interaction dataset from the entire multi-chain complex structure instead of single-chain RNAs. Extensive experiments demonstrate that RNABind outperforms existing state-of-the-art methods. Besides, we conduct an extensive experimental evaluation of eight pre-trained RNA LLMs, assessing their performance on the binding site prediction task within a unified experimental protocol. In summary, RNABind provides a powerful tool on exploring RNA-small molecule binding site prediction, which paves the way for future innovations in the RNA-targeted drug discovery.</div></div>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":"437 8","pages":"Article 169010"},"PeriodicalIF":4.7,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143439670","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

RNA-modification by Base Exchange: Structure, Function and Application of tRNA-guanine Transglycosylases. 碱基交换修饰rna: trna -鸟嘌呤转糖基酶的结构、功能及应用。

IF 4.7 2区生物学

Journal of Molecular Biology Pub Date : 2025-02-15 DOI: 10.1016/j.jmb.2025.168980

Klaus Reuter, Ralf Ficner

{"title":"RNA-modification by Base Exchange: Structure, Function and Application of tRNA-guanine Transglycosylases.","authors":"Klaus Reuter, Ralf Ficner","doi":"10.1016/j.jmb.2025.168980","DOIUrl":"https://doi.org/10.1016/j.jmb.2025.168980","url":null,"abstract":"<p><p>tRNA-guanine transglycosylases (TGT) occur in all domains of life. They are unique among RNA-modifying enzymes as they exchange a guanine base in the primary RNA transcript by various 7-substituted 7-deazaguanines leading to the modified nucleosides queuosine and archaeosine. Archaeosine is found in the D-loop of archaeal tRNAs, queuosine in the anticodon of bacterial and eukaryotic tRNAs specific for Asp, Asn, His and Tyr. Structural and functional studies revealed a common base-exchange mechanism for all TGTs. Nonetheless, there are also significant differences between TGTs, which will be discussed here. It concerns the specificity for different 7-deazaguanine substrates as well as the recognition of substrate tRNAs. For queuosine TGT an anticodon stem-loop containing the UGU recognition motif is a minimal substrate sufficient for binding to the active site, however, full-length tRNA is bound with higher affinity due to multiple interactions with the dimeric enzyme. Archaeal TGT also binds tRNAs as homodimer, even though the interaction pattern is very different and results in a large change of tRNA conformation. Interestingly, a closely related enzyme, DpdA, exchanges guanine by 7-cyano-7-deazguanine (preQ<sub>0</sub>) in double stranded DNA of several bacteria. Bacterial TGT is a target for structure-based drug design, as the virulence of Shigella depends on TGT activity, and mammalian TGT has been used for the treatment of murine experimental autoimmune encephalomyelitis, a model for chronic multiple sclerosis. Furthermore, TGT has become a valuable tool in nucleic acid chemistry, as it facilitates the incorporation of non-natural bases in tRNA molecules, e.g. for labelling or cross-linking purposes.</p>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":" ","pages":"168980"},"PeriodicalIF":4.7,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431999","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