Publications by authors named "Janusz M Bujnicki"

Article Synopsis
  • - RNA-Puzzles is a collaborative project focused on improving the prediction of RNA three-dimensional structures, with predictions made by modeling groups before experimental structures are published.
  • - A significant set of predictions was made by 18 groups for 23 different RNA structures, including various elements like ribozymes and aptamers.
  • - The study highlights key challenges in RNA modeling, such as identifying helix pairs and ensuring proper stacking, and notes that some top-performing groups also excelled in a separate competition (CASP15).
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We present Sci-ModoM, the first next-generation RNome database offering a holistic view of the epitranscriptomic landscape. Sci-ModoM has a simple yet powerful interface, underpinned by FAIR data principles, a standardized nomenclature, and interoperable formats, fostering the use of common standards within the epitranscriptomics community. Sci-ModoM provides quantitative measurements per site and dataset, enabling users to assess confidence levels based on score, coverage, and stoichiometry.

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Advancements in genome-wide sequence analysis have led to the discovery of numerous novel bacterial non-coding RNAs (ncRNAs). These ncRNAs have been categorized into various RNA families and classes based on their size, structure, function, and evolutionary relationships. One such ncRNA family, raiA, is notably abundant in the bacterial phyla Firmicutes and Actinobacteria and is remarkably well-conserved across many Gram-positive bacteria.

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The Nucleic Acid InfraRed Data Bank (NAIRDB) serves as a comprehensive public repository dedicated to the archival and free distribution of Fourier transform infrared (FTIR) spectral data specific to nucleic acids. This database encompasses a collection of FTIR spectra covering diverse nucleic acid molecules, including DNA, RNA, DNA/RNA hybrids and their various derivatives. NAIRDB covers details of the experimental conditions for FTIR measurements, literature links, primary sequence data, information about experimentally determined structures for related nucleic acid molecules and/or computationally modeled 3D structures.

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Article Synopsis
  • * A study analyzed nearly 10,000 cancer samples spanning 31 different tumor types and identified that changes in expression of certain mA core factors, particularly YTHDF1, YTHDF2, YTHDF3, and VIRMA, are the most frequently altered and show significant links to cancer progression.
  • * The research suggests focusing on non-enzymatic mA factors like YTHDF and VIRMA for cancer studies and treatment over METTL3, which did not show strong
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Article Synopsis
  • - Recent advancements in RNA structure prediction using AI and machine learning have greatly enhanced our understanding of RNA's role in cellular functions and its potential for therapeutic applications.
  • - The integration of experimental techniques like cryo-EM and high-throughput sequencing has significantly improved RNA modeling accuracy and efficiency.
  • - The review covers the effectiveness of RNA-Puzzles and CASP challenges in evaluating prediction methods and discusses future implications for drug discovery and RNA-targeted therapies.
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Non-coding RNAs play a major role in diverse processes in living cells with their sequence and spatial structure serving as the principal determinants of their function. Superposition of RNA 3D structures is the most accurate method for comparative analysis of RNA molecules and for inferring structure-based sequence alignments. Topology-independent superposition is particularly relevant, as evidenced by structurally similar RNAs with sequence permutations such as tRNA and Y RNA.

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We have been aware of the existence of knotted proteins for over 30 years-but it is hard to predict what is the most complicated knot that can be formed in proteins. Here, we show new and the most complex knotted topologies recorded to date-double trefoil knots (3 3). We found five domain arrangements (architectures) that result in a doubly knotted structure in almost a thousand proteins.

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Research on ribonucleic acid (RNA) structures and functions benefits from easy-to-use tools for computational prediction and analyses of RNA three-dimensional (3D) structure. The SimRNAweb server version 2.0 offers an enhanced, user-friendly platform for RNA 3D structure prediction and analysis of RNA folding trajectories based on the SimRNA method.

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E3 ubiquitin ligases recognize substrates through their short linear motifs termed degrons. While degron-signaling has been a subject of extensive study, resources for its systematic screening are limited. To bridge this gap, we developed DEGRONOPEDIA, a web server that searches for degrons and maps them to nearby residues that can undergo ubiquitination and disordered regions, which may act as protein unfolding seeds.

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Betacoronaviruses are a genus within the Coronaviridae family of RNA viruses. They are capable of infecting vertebrates and causing epidemics as well as global pandemics in humans. Mitigating the threat posed by Betacoronaviruses requires an understanding of their molecular diversity.

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Knots are very common in polymers, including DNA and protein molecules. Yet, no genuine knot has been identified in natural RNA molecules to date. Upon re-examining experimentally determined RNA 3D structures, we discovered a trefoil knot 3, the most basic non-trivial knot, in the RydC RNA.

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The MODOMICS database was updated with recent data and now includes new data types related to RNA modifications. Changes to the database include an expanded modification catalog, encompassing both natural and synthetic residues identified in RNA structures. This addition aids in representing RNA sequences from the RCSB PDB database more effectively.

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Summary: Structure determination is a key step in the functional characterization of many non-coding RNA molecules. High-resolution RNA 3D structure determination efforts, however, are not keeping up with the pace of discovery of new non-coding RNA sequences. This increases the importance of computational approaches and low-resolution experimental data, such as from the small-angle X-ray scattering experiments.

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Ribonucleic acid (RNA) molecules serve as master regulators of cells by encoding their biological function in the ribonucleotide sequence, particularly their ability to interact with other molecules. To understand how RNA molecules perform their biological tasks and to design new sequences with specific functions, it is of great benefit to be able to computationally predict how RNA folds and interacts in the cellular environment. Our workflow for computational modeling of the 3D structures of RNA and its interactions with other molecules uses a set of methods developed in our laboratory, including MeSSPredRNA for predicting canonical and non-canonical base pairs, PARNASSUS for detecting remote homology based on comparisons of sequences and secondary structures, ModeRNA for comparative modeling, the SimRNA family of programs for modeling RNA 3D structure and its complexes with other molecules, and QRNAS for model refinement.

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Understanding the 3D structure of RNA is key to understanding RNA function. RNA 3D structure is modular and can be seen as a composition of building blocks of various sizes called tertiary motifs. Currently, long-range motifs formed between distant loops and helical regions are largely less studied than the local motifs determined by the RNA secondary structure.

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The first RNA category of the Critical Assessment of Techniques for Structure Prediction competition was only made possible because of the scientists who provided experimental structures to challenge the predictors. In this article, these scientists offer a unique and valuable analysis of both the successes and areas for improvement in the predicted models. All 10 RNA-only targets yielded predictions topologically similar to experimentally determined structures.

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Ribonucleic acids (RNAs) play crucial roles in living organisms and some of them, such as bacterial ribosomes and precursor messenger RNA, are targets of small molecule drugs, whereas others, e.g. bacterial riboswitches or viral RNA motifs are considered as potential therapeutic targets.

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The biologically relevant structures of proteins and nucleic acids and their complexes are dynamic. They include a combination of regions ranging from rigid structural segments to structural switches to regions that are almost always disordered, which interact with each other in various ways. Comparing conformational changes and variation in contacts between different conformational states is essential to understand the biological functions of proteins, nucleic acids, and their complexes.

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RNA is a unique biomolecule that is involved in a variety of fundamental biological functions, all of which depend solely on its structure and dynamics. Since the experimental determination of crystal RNA structures is laborious, computational 3D structure prediction methods are experiencing an ongoing and thriving development. Such methods can lead to many models; thus, it is necessary to build comparisons and extract common structural motifs for further medical or biological studies.

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Computational methods play a pivotal role in drug discovery and are widely applied in virtual screening, structure optimization, and compound activity profiling. Over the last decades, almost all the attention in medicinal chemistry has been directed to protein-ligand binding, and computational tools have been created with this target in mind. With novel discoveries of functional RNAs and their possible applications, RNAs have gained considerable attention as potential drug targets.

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The TRIM-NHL protein Meiotic P26 (Mei-P26) acts as a regulator of cell fate in Its activity is critical for ovarian germline stem cell maintenance, differentiation of oocytes, and spermatogenesis. Mei-P26 functions as a post-transcriptional regulator of gene expression; however, the molecular details of how its NHL domain selectively recognizes and regulates its mRNA targets have remained elusive. Here, we present the crystal structure of the Mei-P26 NHL domain at 1.

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Nucleic acid cleaving DNAzymes are versatile and robust catalysts that outcompete ribozymes and protein enzymes in terms of chemical stability, affordability and ease to synthesize. In spite of their attractiveness, the choice of which DNAzyme should be used to cleave a given substrate is far from obvious, and requires expert knowledge as well as in-depth literature scrutiny. DNAzymeBuilder enables fast and automatic assembly of DNAzymes for the first time, superseding the manual design of DNAzymes.

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The MODOMICS database has been, since 2006, a manually curated and centralized resource, storing and distributing comprehensive information about modified ribonucleosides. Originally, it only contained data on the chemical structures of modified ribonucleosides, their biosynthetic pathways, the location of modified residues in RNA sequences, and RNA-modifying enzymes. Over the years, prompted by the accumulation of new knowledge and new types of data, it has been updated with new information and functionalities.

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