Publications by authors named "Ryszard W Adamiak"

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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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 to predict RNA 3D structure have more and more practical applications in molecular biology and medicine. Therefore, it is crucial to intensify efforts to improve the accuracy and quality of predicted three-dimensional structures. A significant role in this is played by the RNA-Puzzles initiative that collects, evaluates, and shares RNAs built computationally within currently nearly 30 challenges.

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RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA 3D structure prediction. With agreement from crystallographers, the RNA structures are predicted by various groups before the publication of the crystal structures. We now report the prediction of 3D structures for six RNA sequences: four nucleolytic ribozymes and two riboswitches.

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Background: Computational RNA 3D structure prediction and modeling are rising as complementary approaches to high-resolution experimental techniques for structure determination. They often apply to substitute or complement them. Recently, researchers' interests have directed towards in silico methods to fit, remodel and refine RNA tertiary structure models.

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In the field of RNA structural biology and bioinformatics, an access to correctly annotated RNA structure is of crucial importance, especially in the secondary and 3D structure predictions. RNApdbee webserver, introduced in 2014, primarily aimed to address the problem of RNA secondary structure extraction from the PDB files. Its new version, RNApdbee 2.

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Motivation: Understanding the formation, architecture and roles of pseudoknots in RNA structures are one of the most difficult challenges in RNA computational biology and structural bioinformatics. Methods predicting pseudoknots typically perform this with poor accuracy, often despite experimental data incorporation. Existing bioinformatic approaches differ in terms of pseudoknots' recognition and revealing their nature.

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Matrix metalloproteinase 9 (MMP-9) has recently emerged as a molecule that contributes to pathological synaptic plasticity in schizophrenia, but explanation of the underlying mechanisms has been missing. In the present study, we performed a phenotype-based genetic association study (PGAS) in > 1,000 schizophrenia patients from the Göttingen Research Association for Schizophrenia (GRAS) data collection and found an association between the rs20544 C/T single-nucleotide polymorphism (SNP) located in the 3'untranslated region (UTR) and the severity of a chronic delusional syndrome. In cultured neurons, the rs20544 SNP influenced synaptic MMP-9 activity and the morphology of dendritic spines.

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RNA-Puzzles is a collective experiment in blind 3D RNA structure prediction. We report here a third round of RNA-Puzzles. Five puzzles, 4, 8, 12, 13, 14, all structures of riboswitch aptamers and puzzle 7, a ribozyme structure, are included in this round of the experiment.

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RNAComposer is a fully automated, web-interfaced system for RNA 3D structure prediction, freely available at http://rnacomposer.cs.put.

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RNAs adopt specific structures to perform their activities and these are critical to virtually all RNA-mediated processes. Because of difficulties in experimentally assessing structures of large RNAs using NMR, X-ray crystallography, or cryo-microscopy, there is currently great demand for new high-resolution 3D structure prediction methods. Recently we reported on RNAComposer, a knowledge-based method for the fully automated RNA 3D structure prediction from a user-defined secondary structure.

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RNAs adopt specific, stable tertiary architectures to perform their activities. Knowledge of RNA tertiary structure is fundamental to understand RNA functions beginning with transcription and ending with turnover. Contrary to advanced RNA secondary structure prediction algorithms, which allow good accuracy when experimental data are integrated into the prediction, tertiary structure prediction of large RNAs still remains a significant challenge.

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Background: The Gag polyprotein is a multifunctional regulator of retroviral replication and major structural component of immature virions. The nucleic acid chaperone (NAC) activity is considered necessary to retroviral Gag functions, but so far, NAC activity has only been confirmed for HIV-1 and RSV Gag polyproteins. The nucleocapsid (NC) domain of Gag is proposed to be crucial for interactions with nucleic acids and NAC activity.

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Nowadays, various methodologies can be applied to model RNA 3D structure. Thus, the plausible quality assessment of 3D models has a fundamental impact on the progress of structural bioinformatics. Here, we present RNAssess server, a novel tool dedicated to visual evaluation of RNA 3D models in the context of the known reference structure for a wide range of accuracy levels (from atomic to the whole molecule perspective).

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This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement.

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In RNA structural biology and bioinformatics an access to correct RNA secondary structure and its proper representation is of crucial importance. This is true especially in the field of secondary and 3D RNA structure prediction. Here, we introduce RNApdbee-a new tool that allows to extract RNA secondary structure from the pdb file, and presents it in both textual and graphical form.

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PDB format is most commonly applied by various programs to define three-dimensional structure of biomolecules. However, the programs often use different versions of the format. Thus far, no comprehensive solution for unifying the PDB formats has been developed.

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The continuously increasing amount of RNA sequence and experimentally determined 3D structure data drives the development of computational methods supporting exploration of these data. Contemporary functional analysis of RNA molecules, such as ribozymes or riboswitches, covers various issues, among which tertiary structure modeling becomes more and more important. A growing number of tools to model and predict RNA structure calls for an evaluation of these tools and the quality of outcomes their produce.

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Understanding the numerous functions that RNAs play in living cells depends critically on knowledge of their three-dimensional structure. Due to the difficulties in experimentally assessing structures of large RNAs, there is currently great demand for new high-resolution structure prediction methods. We present the novel method for the fully automated prediction of RNA 3D structures from a user-defined secondary structure.

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RNA dimerization is an essential step in the retroviral life cycle. Dimerization and encapsidation signals, closely linked in HIV-2, are located in the leader RNA region. The SL1 motif and nucleocapsid protein are considered important for both processes.

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Background: Recent discoveries concerning novel functions of RNA, such as RNA interference, have contributed towards the growing importance of the field. In this respect, a deeper knowledge of complex three-dimensional RNA structures is essential to understand their new biological functions. A number of bioinformatic tools have been proposed to explore two major structural databases (PDB, NDB) in order to analyze various aspects of RNA tertiary structures.

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Recently, it has been reported that HIV-1 TAR RNA element releases functionally competent miRNAs upon processing by Dicer enzyme. Here, we extend the analysis of miRNA viral-encoding potential to the TAR RNA of the HIV-2. Using in vitro Dicer cleavages and computer-aided analysis we have found that the 124-mer TAR RNA domain, present at the 5' end of HIV-2 mRNAs, putatively encodes pre-miRNAs.

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The structures of two crystal forms of the RNA 16-mer with the sequence GUGGUCUGAUGAGGCC, grown in the presence of a high concentration of sulphate ions, have been determined using synchrotron radiation at 1.4- and 2.0-A resolution.

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The RNA single bulge motif is an unpaired residue within a strand of several complementary base pairs. To gain insight into structural changes induced by the presence of the adenosine bulge on RNA duplex, the solution structures of RNA duplex containing a single adenine bulge (5'-GCAGAAGAGCG-3'/5'-CGCUCUCUGC-3') and a reference duplex with all Watson-Crick base pairs (5'-GCAGAGAGCG-3'/5'-CGCUCUCUGC-3') have been determined by NMR spectroscopy. The reference duplex structure is a regular right-handed helix with all of the attributes of an A-type helix.

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The RNA FRABASE is a web-accessible engine with a relational database, which allows for the automatic search of user-defined, 3D RNA fragments within a set of RNA structures. This is a new tool to search and analyse RNA structures, directed at the 3D structure modelling. The user needs to input either RNA sequence(s) and/or secondary structure(s) given in a 'dot-bracket' notation.

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