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":null,"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":4.7000,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Molecular Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1016/j.jmb.2025.169014","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Journal of Molecular Biology (JMB) provides high quality, comprehensive and broad coverage in all areas of molecular biology. The journal publishes original scientific research papers that provide mechanistic and functional insights and report a significant advance to the field. The journal encourages the submission of multidisciplinary studies that use complementary experimental and computational approaches to address challenging biological questions.
Research areas include but are not limited to: Biomolecular interactions, signaling networks, systems biology; Cell cycle, cell growth, cell differentiation; Cell death, autophagy; Cell signaling and regulation; Chemical biology; Computational biology, in combination with experimental studies; DNA replication, repair, and recombination; Development, regenerative biology, mechanistic and functional studies of stem cells; Epigenetics, chromatin structure and function; Gene expression; Membrane processes, cell surface proteins and cell-cell interactions; Methodological advances, both experimental and theoretical, including databases; Microbiology, virology, and interactions with the host or environment; Microbiota mechanistic and functional studies; Nuclear organization; Post-translational modifications, proteomics; Processing and function of biologically important macromolecules and complexes; Molecular basis of disease; RNA processing, structure and functions of non-coding RNAs, transcription; Sorting, spatiotemporal organization, trafficking; Structural biology; Synthetic biology; Translation, protein folding, chaperones, protein degradation and quality control.