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Wang J, Sha CM, Dokholyan NV. Combining Experimental Restraints and RNA 3D Structure Prediction in RNA Nanotechnology. Methods Mol Biol 2023; 2709:51-64. [PMID: 37572272 PMCID: PMC10680996 DOI: 10.1007/978-1-0716-3417-2_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/14/2023]
Abstract
Precise RNA tertiary structure prediction can aid in the design of RNA nanoparticles. However, most existing RNA tertiary structure prediction methods are limited to small RNAs with relatively simple secondary structures. Large RNA molecules usually have complex secondary structures, including multibranched loops and pseudoknots, allowing for highly flexible RNA geometries and multiple stable states. Various experiments and bioinformatics analyses can often provide information about the distance between atoms (or residues) in RNA, which can be used to guide the prediction of RNA tertiary structure. In this chapter, we will introduce a platform, iFoldNMR, that can incorporate non-exchangeable imino protons resonance data from NMR as restraints for RNA 3D structure prediction. We also introduce an algorithm, DVASS, which optimizes distance restraints for better RNA 3D structure prediction.
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Affiliation(s)
- Jian Wang
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Congzhou M Sha
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
- Department of Engineering Science and Mechanics, Penn State University, State College, PA, USA
| | - Nikolay V Dokholyan
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA.
- Department of Engineering Science and Mechanics, Penn State University, State College, PA, USA.
- Department of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, PA, USA.
- Department of Chemistry, Penn State University, State College, PA, USA.
- Department of Biomedical Engineering, Penn State University, State College, PA, USA.
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2
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Zhang C, Pyle AM. CSSR: assignment of secondary structure to coarse-grained RNA tertiary structures. ACTA CRYSTALLOGRAPHICA SECTION D STRUCTURAL BIOLOGY 2022; 78:466-471. [PMID: 35362469 PMCID: PMC8972804 DOI: 10.1107/s2059798322001292] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 02/02/2022] [Indexed: 11/16/2022]
Abstract
CSSR, an algorithm for assigning secondary structures to RNA 3D structures with missing atoms, has been developed. The base-pair assignment accuracy is close to 90% for 3D structures in which only one atom per nucleotide can be empirically identified. RNA secondary-structure (rSS) assignment is one of the most routine forms of analysis of RNA 3D structures. However, traditional rSS assignment programs require full-atomic structures of the individual RNA nucleotides. This prevents their application to the modeling of RNA structures in which base atoms are missing. To address this issue, Coarse-grained Secondary Structure of RNA (CSSR), an algorithm for the assignment of rSS for structures in which nucleobase atomic positions are incomplete, has been developed. Using CSSR, an rSS assignment accuracy of ∼90% is achieved even for RNA structures in which only one backbone atom per nucleotide is known. Thus, CSSR will be useful for the analysis of experimentally determined and computationally predicted RNA 3D structures alike. The source code of CSSR is available at https://github.com/pylelab/CSSR.
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3
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Wang J, Mao K, Zhao Y, Zeng C, Xiang J, Zhang Y, Xiao Y. Optimization of RNA 3D structure prediction using evolutionary restraints of nucleotide-nucleotide interactions from direct coupling analysis. Nucleic Acids Res 2017; 45:6299-6309. [PMID: 28482022 PMCID: PMC5499770 DOI: 10.1093/nar/gkx386] [Citation(s) in RCA: 71] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Accepted: 04/27/2017] [Indexed: 01/01/2023] Open
Abstract
Direct coupling analysis of nucleotide coevolution provides a novel approach to identify which nucleotides in an RNA molecule are likely in direct contact, and this information obtained from sequence only can be used to predict RNA 3D structures with much improved accuracy. Here we present an efficient method that incorporates this information into current RNA 3D structure prediction methods, specifically 3dRNA. Our method makes much more accurate RNA 3D structure prediction than the original 3dRNA as well as other existing prediction methods that used the direct coupling analysis. In particular our method demonstrates a significant improvement in predicting multi-branch junction conformations, a major bottleneck for RNA 3D structure prediction. We also show that our method can be used to optimize the predictions by other methods. These results indicate that optimization of RNA 3D structure prediction using evolutionary restraints of nucleotide-nucleotide interactions from direct coupling analysis offers an efficient way for accurate RNA tertiary structure predictions.
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Affiliation(s)
- Jian Wang
- Institute of Biophysics, School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Kangkun Mao
- Institute of Biophysics, School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Yunjie Zhao
- Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan 430079, China
| | - Chen Zeng
- Department of Physics, The George Washington University, Washington, DC 20052, USA.,School of Life Sciences, Jianghan University, Wuhan 430056, China
| | - Jianjin Xiang
- Institute of Biophysics, School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Yi Zhang
- Institute of Biophysics, School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Yi Xiao
- Institute of Biophysics, School of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
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4
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Cragnolini T, Derreumaux P, Pasquali S. Ab initio RNA folding. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2015; 27:233102. [PMID: 25993396 DOI: 10.1088/0953-8984/27/23/233102] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
RNA molecules are essential cellular machines performing a wide variety of functions for which a specific three-dimensional structure is required. Over the last several years, the experimental determination of RNA structures through x-ray crystallography and NMR seems to have reached a plateau in the number of structures resolved each year, but as more and more RNA sequences are being discovered, the need for structure prediction tools to complement experimental data is strong. Theoretical approaches to RNA folding have been developed since the late nineties, when the first algorithms for secondary structure prediction appeared. Over the last 10 years a number of prediction methods for 3D structures have been developed, first based on bioinformatics and data-mining, and more recently based on a coarse-grained physical representation of the systems. In this review we are going to present the challenges of RNA structure prediction and the main ideas behind bioinformatic approaches and physics-based approaches. We will focus on the description of the more recent physics-based phenomenological models and on how they are built to include the specificity of the interactions of RNA bases, whose role is critical in folding. Through examples from different models, we will point out the strengths of physics-based approaches, which are able not only to predict equilibrium structures, but also to investigate dynamical and thermodynamical behavior, and the open challenges to include more key interactions ruling RNA folding.
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Affiliation(s)
- Tristan Cragnolini
- Laboratoire de Biochimie Théorique UPR 9080 CNRS, Université Paris Diderot, Sorbonne, Paris Cité, IBPC 13 rue Pierre et Marie Curie, 75005 Paris, France
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5
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Miao Z, Adamiak RW, Blanchet MF, Boniecki M, Bujnicki JM, Chen SJ, Cheng C, Chojnowski G, Chou FC, Cordero P, Cruz JA, Ferré-D'Amaré AR, Das R, Ding F, Dokholyan NV, Dunin-Horkawicz S, Kladwang W, Krokhotin A, Lach G, Magnus M, Major F, Mann TH, Masquida B, Matelska D, Meyer M, Peselis A, Popenda M, Purzycka KJ, Serganov A, Stasiewicz J, Szachniuk M, Tandon A, Tian S, Wang J, Xiao Y, Xu X, Zhang J, Zhao P, Zok T, Westhof E. RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures. RNA (NEW YORK, N.Y.) 2015; 21:1066-84. [PMID: 25883046 PMCID: PMC4436661 DOI: 10.1261/rna.049502.114] [Citation(s) in RCA: 134] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2015] [Accepted: 02/12/2015] [Indexed: 05/04/2023]
Abstract
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. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5-3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson-Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/.
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Affiliation(s)
- Zhichao Miao
- Architecture et Réactivité de l'ARN, Université de Strasbourg, Institut de biologie moléculaire et cellulaire du CNRS, 67000 Strasbourg, France
| | - Ryszard W Adamiak
- Department of Structural Chemistry and Biology of Nucleic Acids, Structural Chemistry of Nucleic Acids Laboratory, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
| | - Marc-Frédérick Blanchet
- Institute for Research in Immunology and Cancer (IRIC), Department of Computer Science and Operations Research, Université de Montréal, Montréal, Québec, Canada H3C 3J7
| | - Michal Boniecki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Janusz M Bujnicki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland Laboratory of Bioinformatics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland
| | - Shi-Jie Chen
- Department of Physics and Astronomy, Department of Biochemistry, and Informatics Institute, University of Missouri-Columbia, Columbia, Missouri 65211, USA
| | - Clarence Cheng
- Department of Physics, Stanford University, Stanford, California 94305, USA
| | - Grzegorz Chojnowski
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Fang-Chieh Chou
- Department of Physics, Stanford University, Stanford, California 94305, USA
| | - Pablo Cordero
- Department of Physics, Stanford University, Stanford, California 94305, USA
| | - José Almeida Cruz
- Architecture et Réactivité de l'ARN, Université de Strasbourg, Institut de biologie moléculaire et cellulaire du CNRS, 67000 Strasbourg, France
| | | | - Rhiju Das
- Department of Physics, Stanford University, Stanford, California 94305, USA
| | - Feng Ding
- Department of Physics and Astronomy, College of Engineering and Science, Clemson University, Clemson, South Carolina 29634, USA
| | - Nikolay V Dokholyan
- Department of Biochemistry and Biophysics, University of North Carolina, School of Medicine, Chapel Hill, North Carolina 27599, USA
| | - Stanislaw Dunin-Horkawicz
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Wipapat Kladwang
- Department of Physics, Stanford University, Stanford, California 94305, USA
| | - Andrey Krokhotin
- Department of Biochemistry and Biophysics, University of North Carolina, School of Medicine, Chapel Hill, North Carolina 27599, USA
| | - Grzegorz Lach
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Marcin Magnus
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - François Major
- Institute for Research in Immunology and Cancer (IRIC), Department of Computer Science and Operations Research, Université de Montréal, Montréal, Québec, Canada H3C 3J7
| | - Thomas H Mann
- Department of Physics, Stanford University, Stanford, California 94305, USA
| | - Benoît Masquida
- Génétique Moléculaire Génomique Microbiologie, Institut de physiologie et de la chimie biologique, 67084 Strasbourg, France
| | - Dorota Matelska
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Mélanie Meyer
- Institut de génétique et de biologie moléculaire et cellulaire, 67400 Strasbourg, France
| | - Alla Peselis
- Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, New York 10016, USA
| | - Mariusz Popenda
- Department of Structural Chemistry and Biology of Nucleic Acids, Structural Chemistry of Nucleic Acids Laboratory, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
| | - Katarzyna J Purzycka
- Department of Structural Chemistry and Biology of Nucleic Acids, Structural Chemistry of Nucleic Acids Laboratory, Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
| | - Alexander Serganov
- Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, New York 10016, USA
| | - Juliusz Stasiewicz
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Marta Szachniuk
- Poznan University of Technology, Institute of Computing Science, 60-965 Poznan, Poland
| | - Arpit Tandon
- Department of Biochemistry and Biophysics, University of North Carolina, School of Medicine, Chapel Hill, North Carolina 27599, USA
| | - Siqi Tian
- Department of Physics, Stanford University, Stanford, California 94305, USA
| | - Jian Wang
- Department of Physics, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Yi Xiao
- Department of Physics, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Xiaojun Xu
- Department of Physics and Astronomy, Department of Biochemistry, and Informatics Institute, University of Missouri-Columbia, Columbia, Missouri 65211, USA
| | - Jinwei Zhang
- National Heart, Lung and Blood Institute, Bethesda, Maryland 20892-8012, USA
| | - Peinan Zhao
- Department of Physics and Astronomy, Department of Biochemistry, and Informatics Institute, University of Missouri-Columbia, Columbia, Missouri 65211, USA
| | - Tomasz Zok
- Poznan University of Technology, Institute of Computing Science, 60-965 Poznan, Poland
| | - Eric Westhof
- Architecture et Réactivité de l'ARN, Université de Strasbourg, Institut de biologie moléculaire et cellulaire du CNRS, 67000 Strasbourg, France
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6
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Tuszynska I, Magnus M, Jonak K, Dawson W, Bujnicki JM. NPDock: a web server for protein-nucleic acid docking. Nucleic Acids Res 2015; 43:W425-30. [PMID: 25977296 PMCID: PMC4489298 DOI: 10.1093/nar/gkv493] [Citation(s) in RCA: 151] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2015] [Accepted: 05/02/2015] [Indexed: 01/03/2023] Open
Abstract
Protein–RNA and protein–DNA interactions play fundamental roles in many biological processes. A detailed understanding of these interactions requires knowledge about protein–nucleic acid complex structures. Because the experimental determination of these complexes is time-consuming and perhaps futile in some instances, we have focused on computational docking methods starting from the separate structures. Docking methods are widely employed to study protein–protein interactions; however, only a few methods have been made available to model protein–nucleic acid complexes. Here, we describe NPDock (Nucleic acid–Protein Docking); a novel web server for predicting complexes of protein–nucleic acid structures which implements a computational workflow that includes docking, scoring of poses, clustering of the best-scored models and refinement of the most promising solutions. The NPDock server provides a user-friendly interface and 3D visualization of the results. The smallest set of input data consists of a protein structure and a DNA or RNA structure in PDB format. Advanced options are available to control specific details of the docking process and obtain intermediate results. The web server is available at http://genesilico.pl/NPDock.
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Affiliation(s)
- Irina Tuszynska
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland Institute of Informatics, University of Warsaw, Banacha 2, PL-02-097 Warsaw, Poland
| | - Marcin Magnus
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland
| | - Katarzyna Jonak
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland
| | - Wayne Dawson
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland
| | - Janusz M Bujnicki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland Bioinformatics Laboratory, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, ul. Umultowska 89, PL-61-614 Poznan, Poland
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7
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Chojnowski G, Walen T, Bujnicki JM. RNA Bricks--a database of RNA 3D motifs and their interactions. Nucleic Acids Res 2013; 42:D123-31. [PMID: 24220091 PMCID: PMC3965019 DOI: 10.1093/nar/gkt1084] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
The RNA Bricks database (http://iimcb.genesilico.pl/rnabricks), stores information about recurrent RNA 3D motifs and their interactions, found in experimentally determined RNA structures and in RNA–protein complexes. In contrast to other similar tools (RNA 3D Motif Atlas, RNA Frabase, Rloom) RNA motifs, i.e. ‘RNA bricks’ are presented in the molecular environment, in which they were determined, including RNA, protein, metal ions, water molecules and ligands. All nucleotide residues in RNA bricks are annotated with structural quality scores that describe real-space correlation coefficients with the electron density data (if available), backbone geometry and possible steric conflicts, which can be used to identify poorly modeled residues. The database is also equipped with an algorithm for 3D motif search and comparison. The algorithm compares spatial positions of backbone atoms of the user-provided query structure and of stored RNA motifs, without relying on sequence or secondary structure information. This enables the identification of local structural similarities among evolutionarily related and unrelated RNA molecules. Besides, the search utility enables searching ‘RNA bricks’ according to sequence similarity, and makes it possible to identify motifs with modified ribonucleotide residues at specific positions.
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Affiliation(s)
- Grzegorz Chojnowski
- International Institute of Molecular and Cell Biology, Trojdena 4, 02-109 Warsaw, Poland, Faculty of Mathematics, Informatics, and Mechanics, University of Warsaw, Banacha 2, 02-097 Warsaw, Poland and Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Umultowska 89, 61-614 Poznan, Poland
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8
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Matelska D, Purta E, Panek S, Boniecki MJ, Bujnicki JM, Dunin-Horkawicz S. S6:S18 ribosomal protein complex interacts with a structural motif present in its own mRNA. RNA (NEW YORK, N.Y.) 2013; 19:1341-8. [PMID: 23980204 PMCID: PMC3854524 DOI: 10.1261/rna.038794.113] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2013] [Accepted: 07/05/2013] [Indexed: 05/24/2023]
Abstract
Prokaryotic ribosomal protein genes are typically grouped within highly conserved operons. In many cases, one or more of the encoded proteins not only bind to a specific site in the ribosomal RNA, but also to a motif localized within their own mRNA, and thereby regulate expression of the operon. In this study, we computationally predicted an RNA motif present in many bacterial phyla within the 5' untranslated region of operons encoding ribosomal proteins S6 and S18. We demonstrated that the S6:S18 complex binds to this motif, which we hereafter refer to as the S6:S18 complex-binding motif (S6S18CBM). This motif is a conserved CCG sequence presented in a bulge flanked by a stem and a hairpin structure. A similar structure containing a CCG trinucleotide forms the S6:S18 complex binding site in 16S ribosomal RNA. We have constructed a 3D structural model of a S6:S18 complex with S6S18CBM, which suggests that the CCG trinucleotide in a specific structural context may be specifically recognized by the S18 protein. This prediction was supported by site-directed mutagenesis of both RNA and protein components. These results provide a molecular basis for understanding protein-RNA recognition and suggest that the S6S18CBM is involved in an auto-regulatory mechanism.
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MESH Headings
- 5' Untranslated Regions/genetics
- Bacterial Proteins/chemistry
- Bacterial Proteins/genetics
- Bacterial Proteins/metabolism
- Base Pairing
- Base Sequence
- Binding Sites
- Electrophoretic Mobility Shift Assay
- Escherichia coli/genetics
- Escherichia coli/metabolism
- Models, Molecular
- Molecular Sequence Data
- Nucleic Acid Conformation
- Operon/genetics
- Protein Binding
- Protein Structure, Tertiary
- RNA, Bacterial/chemistry
- RNA, Bacterial/genetics
- RNA, Bacterial/metabolism
- RNA, Messenger/chemistry
- RNA, Messenger/genetics
- RNA, Messenger/metabolism
- RNA, Ribosomal/chemistry
- RNA, Ribosomal/genetics
- RNA, Ribosomal/metabolism
- Ribosomal Protein S6/chemistry
- Ribosomal Protein S6/genetics
- Ribosomal Protein S6/metabolism
- Ribosomal Proteins/chemistry
- Ribosomal Proteins/genetics
- Ribosomal Proteins/metabolism
- Ribosomes/chemistry
- Ribosomes/genetics
- Ribosomes/metabolism
- Sequence Homology, Nucleic Acid
- Thermus thermophilus/genetics
- Thermus thermophilus/metabolism
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Affiliation(s)
- Dorota Matelska
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, Warsaw, 02-109, Poland
| | - Elzbieta Purta
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, Warsaw, 02-109, Poland
| | - Sylwia Panek
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, Warsaw, 02-109, Poland
| | - Michal J. Boniecki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, Warsaw, 02-109, Poland
| | - Janusz M. Bujnicki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, Warsaw, 02-109, Poland
- Bioinformatics Laboratory, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Poznań, 61-614, Poland
| | - Stanislaw Dunin-Horkawicz
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, Warsaw, 02-109, Poland
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9
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Cruz JA, Blanchet MF, Boniecki M, Bujnicki JM, Chen SJ, Cao S, Das R, Ding F, Dokholyan NV, Flores SC, Huang L, Lavender CA, Lisi V, Major F, Mikolajczak K, Patel DJ, Philips A, Puton T, Santalucia J, Sijenyi F, Hermann T, Rother K, Rother M, Serganov A, Skorupski M, Soltysinski T, Sripakdeevong P, Tuszynska I, Weeks KM, Waldsich C, Wildauer M, Leontis NB, Westhof E. RNA-Puzzles: a CASP-like evaluation of RNA three-dimensional structure prediction. RNA (NEW YORK, N.Y.) 2012; 18:610-25. [PMID: 22361291 PMCID: PMC3312550 DOI: 10.1261/rna.031054.111] [Citation(s) in RCA: 189] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises.
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Affiliation(s)
- José Almeida Cruz
- Architecture et Réactivité de l'ARN, Université de Strasbourg, IBMC-CNRS, F-67084 Strasbourg, France
| | - Marc-Frédérick Blanchet
- Institute for Research in Immunology and Cancer (IRIC), Department of Computer Science and Operations Research, Université de Montréal, Montréal, Québec H3C 3J7, Canada
| | - Michal Boniecki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Janusz M. Bujnicki
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
- Laboratory of Bioinformatics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland
| | - Shi-Jie Chen
- Department of Physics and Department of Biochemistry, University of Missouri, Columbia, Missouri 65211, USA
| | - Song Cao
- Department of Physics and Department of Biochemistry, University of Missouri, Columbia, Missouri 65211, USA
| | - Rhiju Das
- Department of Biochemistry
- Department of Physics, Stanford University, Stanford, California 94305, USA
| | - Feng Ding
- Department of Biochemistry and Biophysics, University of North Carolina, School of Medicine, Chapel Hill, North Carolina 27599, USA
| | - Nikolay V. Dokholyan
- Department of Biochemistry and Biophysics, University of North Carolina, School of Medicine, Chapel Hill, North Carolina 27599, USA
| | - Samuel Coulbourn Flores
- Computational & Systems Biology Program, Institute for Cell and Molecular Biology, Uppsala University, 751 05 Uppsala, Sweden
| | - Lili Huang
- Structural Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA
| | - Christopher A. Lavender
- Department of Chemistry, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - Véronique Lisi
- Institute for Research in Immunology and Cancer (IRIC), Department of Computer Science and Operations Research, Université de Montréal, Montréal, Québec H3C 3J7, Canada
| | - François Major
- Institute for Research in Immunology and Cancer (IRIC), Department of Computer Science and Operations Research, Université de Montréal, Montréal, Québec H3C 3J7, Canada
| | - Katarzyna Mikolajczak
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Dinshaw J. Patel
- Structural Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA
| | - Anna Philips
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
- Laboratory of Bioinformatics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland
| | - Tomasz Puton
- Laboratory of Bioinformatics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland
| | - John Santalucia
- Department of Chemistry, Wayne State University, Detroit, Michigan 48202, USA
- DNA Software, Ann Arbor, Michigan 48104, USA
| | | | - Thomas Hermann
- Department of Chemistry and Biochemistry, University of California at San Diego, La Jolla, California 92093, USA
| | - Kristian Rother
- Laboratory of Bioinformatics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland
| | - Magdalena Rother
- Laboratory of Bioinformatics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland
| | - Alexander Serganov
- Structural Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA
| | - Marcin Skorupski
- Laboratory of Bioinformatics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland
| | - Tomasz Soltysinski
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Parin Sripakdeevong
- Department of Biochemistry
- Department of Physics, Stanford University, Stanford, California 94305, USA
| | - Irina Tuszynska
- Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, 02-109 Warsaw, Poland
| | - Kevin M. Weeks
- Department of Chemistry, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - Christina Waldsich
- Max F. Perutz Laboratories, Department of Biochemistry, University of Vienna, Vienna 1030, Austria
| | - Michael Wildauer
- Max F. Perutz Laboratories, Department of Biochemistry, University of Vienna, Vienna 1030, Austria
| | - Neocles B. Leontis
- Department of Chemistry and Center for Biomolecular Sciences, Bowling Green State University, Bowling Green, Ohio 43403, USA
| | - Eric Westhof
- Architecture et Réactivité de l'ARN, Université de Strasbourg, IBMC-CNRS, F-67084 Strasbourg, France
- Corresponding author.E-mail .
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