Geometric nomenclature and classification of RNA base pairs

Leontis, Neocles B.; Westhof, Éric

doi:10.1017/s1355838201002515

Cited by 951 publications

(983 citation statements)

References 29 publications

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“…Basepairs are classified according to the geometric categories introduced by Leontis and Westhof [32]. We illustrate by describing the classification of AA basepairs.…”

Section: Preparatory Analysismentioning

confidence: 99%

“…These elements appear in RNA secondary structures as single-stranded hairpin, internal, and multi-helix (junction) "loops," but in fact most of their nucleotides form non-Watson-Crick basepairs that stack in characteristic ways to form modular motifs. RNA bases can pair in 12 geometrically distinct ways, depending on which of their three edges interact (Watson-Crick, Hoogsteen, or Sugar) and the relative orientations of their glycosidic bonds (cis or trans) [32]. The Watson-Crick basepairs belong to the cis Watson-Crick/Watson-Crick geometric family.…”

Section: Introductionmentioning

confidence: 99%

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FR3D: finding local and composite recurrent structural motifs in RNA 3D structures

et al. 2007

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New methods are described for finding recurrent three-dimensional (3D) motifs in RNA atomicresolution structures. Recurrent RNA 3D motifs are sets of RNA nucleotides with similar spatial arrangements. They can be local or composite. Local motifs comprise nucleotides that occur in the same hairpin or internal loop. Composite motifs comprise nucleotides belonging to three or more different RNA strand segments or molecules. We use a base-centered approach to construct efficient, yet exhaustive search procedures using geometric, symbolic, or mixed representations of RNA structure that we implement in a suite of MATLAB programs, "Find RNA 3D" (FR3D). The first modules of FR3D preprocess structure files to classify base-pair and -stacking interactions. Each base is represented geometrically by the position of its glycosidic nitrogen in 3D space and by the rotation matrix that describes its orientation with respect to a common frame. Base-pairing and basestacking interactions are calculated from the base geometries and are represented symbolically according to the Leontis/Westhof basepairing classification, extended to include base-stacking. These data are stored and used to organize motif searches. For geometric searches, the user supplies the 3D structure of a query motif which FR3D uses to find and score geometrically similar candidate motifs, without regard to the sequential position of their nucleotides in the RNA chain or the identity of their bases. To score and rank candidate motifs, FR3D calculates a geometric discrepancy by rigidly rotating candidates to align optimally with the query motif and then comparing the relative orientations of the corresponding bases in the query and candidate motifs. Given the growing size of the RNA structure database, it is impossible to explicitly compute the discrepancy for all conceivable candidate motifs, even for motifs with less than ten nucleotides. The screening algorithm that we describe finds all candidate motifs whose geometric discrepancy with respect to the query motif falls below a user-specified cutoff discrepancy. This technique can be applied to NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript RMSD searches. Candidate motifs identified geometrically may be further screened symbolically to identify those that contain particular basepair types or base-stacking arrangements or that conform to sequence continuity or nucleotide identity constraints. Purely symbolic searches for motifs containing user-defined sequence, continuity and interaction constraints have also been implemented. We demonstrate that FR3D finds all occurrences, both local and composite and with nucleotide substitutions, of sarcin/ricin and kink-turn motifs in the 23S and 5S ribosomal RNA 3D structures of the H. marismortui 50S ribosomal subunit and assigns the lowest discrepancy scores to bona fide examples of these motifs. The search algorithms have been optimized for speed to allow users to search the non-redundant RNA 3D structure database on a personal compute...

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“…Basepairs are classified according to the geometric categories introduced by Leontis and Westhof [32]. We illustrate by describing the classification of AA basepairs.…”

Section: Preparatory Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

FR3D: finding local and composite recurrent structural motifs in RNA 3D structures

et al. 2007

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“…Fully paired and stacked internal loops of up to eight non-canonical pairs have been structurally observed (Vallurupalli & Moore, 2003) (loop E). Fully paired internal loops can be well described using a standardized base-pairing nomenclature such as that developed by Leontis & Westhof (2001). Such nomenclature classification and isostericity relationships are useful for prediction of these types of motifs from sequence and secondary structure .…”

Section: Internal Loopsmentioning

confidence: 99%

RNA structural motifs: building blocks of a modular biomolecule

Hendrix

Brenner

Holbrook

2005

Quart. Rev. Biophys.

199

141

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Abstract. RNAs are modular biomolecules, composed largely of conserved structural subunits, or motifs. These structural motifs comprise the secondary structure of RNA and are knit together via tertiary interactions into a compact, functional, three-dimensional structure and are to be distinguished from motifs defined by sequence or function. A relatively small number of structural motifs are found repeatedly in RNA hairpin and internal loops, and are observed to be composed of a limited number of common 'structural elements '. In addition to secondary and tertiary structure motifs, there are functional motifs specific for certain biological roles and binding motifs that serve to complex metals or other ligands. Research is continuing into the identification and classification of RNA structural motifs and is being initiated to predict motifs from sequence, to trace their phylogenetic relationships and to use them as building blocks in RNA engineering.

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“…The arm is composed of a kink-turn, reverse motif, switch-loop, and lever arm extension. Right and bottom: detailed diagram of the reverse motif 32 using Leontis-Westhof (LW) notation 36 . A tetraloop (GAAA) binds the 11 nucleotide loop receptor 32 , stabilizing the orientation of the lever arm extension.…”

Section: Figurementioning

confidence: 99%

Controllable molecular motors engineered from myosin and RNA

et al. 2017

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Engineering biomolecular motors can provide direct tests of structure-function relationships and customized components for controlling molecular transport in artificial systems1 or in living cells2. Previously, synthetic nucleic acid motors3–5 and modified natural protein motors6–10 have been developed in separate complementary strategies for achieving tunable and controllable motor function. Integrating protein and nucleic acid components to form engineered nucleoprotein motors may enable additional sophisticated functionalities. However, this potential has only begun to be explored in pioneering work harnessing DNA scaffolds to dictate the spacing, number, and composition of tethered protein motors11–15. Here, we describe myosin motors that incorporate RNA lever arms, forming hybrid assemblies in which conformational changes in the protein motor domain are amplified and redirected by nucleic acid structures. The RNA lever arm geometry determines the speed and direction of motor transport, and can be dynamically controlled using programmed transitions in lever arm structure7,9. We have characterized the hybrid motors using in vitro motility assays, single-molecule tracking, cryo-electron microscopy, and structural probing16. Our designs include nucleoprotein motors that reversibly change direction in response to oligonucleotides that drive strand-displacement17 reactions. In multimeric assemblies, the controllable motors walk processively along actin filaments at speeds of 10–20 nm s−1. Finally, to illustrate the potential for multiplexed addressable control, we demonstrate sequence-specific responses of RNA variants to oligonucleotide signals.

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Geometric nomenclature and classification of RNA base pairs

Cited by 951 publications

References 29 publications

FR3D: finding local and composite recurrent structural motifs in RNA 3D structures

FR3D: finding local and composite recurrent structural motifs in RNA 3D structures

RNA structural motifs: building blocks of a modular biomolecule

Controllable molecular motors engineered from myosin and RNA

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