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. 2017 Jul 25;113(2):225-234.
doi: 10.1016/j.bpj.2016.12.037. Epub 2017 Feb 2.

Opportunities and Challenges in RNA Structural Modeling and Design

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Free PMC article

Opportunities and Challenges in RNA Structural Modeling and Design

Tamar Schlick et al. Biophys J. .
Free PMC article

Abstract

We describe opportunities and challenges in RNA structural modeling and design, as recently discussed during the second Telluride Science Research Center workshop organized in June 2016. Topics include fundamental processes of RNA, such as structural assemblies (hierarchical folding, multiple conformational states and their clustering), RNA motifs, and chemical reactivity of RNA, as used for structural prediction and functional inference. We also highlight the software and database issues associated with RNA structures, such as the multiple approaches for motif annotation, the need for frequent database updating, and the importance of quality control of RNA structures. We discuss various modeling approaches for structure prediction, mechanistic analysis of RNA reactions, and RNA design, and the complementary roles that both atomistic and coarse-grained approaches play in such simulations. Collectively, as scientists from varied disciplines become familiar and drawn into these unique challenges, new approaches and collaborative efforts will undoubtedly be catalyzed.

Figures

Figure 1
Figure 1
The structure of a quasi-cyclic duplex RNA molecule with six k-turn motifs (15). To see this figure in color, go online.
Figure 2
Figure 2
RAG elements for RNA motif classification, prediction, partitioning, and design. (A) The RAG approach for RNA representation (42) and design (43, 45) is illustrated as: 1) tree graph of a riboswitch; 2) RAG tree graph catalog segments, organized by the second eigenvalue λ2 of the connectivity matrix (Laplacian) associated with the graph and classified by clustering into three groups: existing (red), RNA-like (blue), and non-RNA-like (black) motifs (see http://www.biomath.nyu.edu/rag/home for more information); 3) graph partitioning for a riboswitch by RAG-3D (44), which suggests modular RNA building blocks, for which PDB structures are available; and 4) fragment assembly of such subgraph fragments using the modular subunits. (B) RAGTOP for 3D structure prediction by a hierarchical MC sampling of tree graphs (46, 48, 49): 1) Initial junction topology prediction; 2) MC sampling of 3D graphs scored by a statistical scoring function with components for bend, twist, and radius-of-gyration; 3) clustering of generated graphs to identify candidate graph; and 4) determination of atomic models from the candidate graph using the fragment assembly based on RAG-3D subgraphs. To see this figure in color, go online.
Figure 2
Figure 2
RAG elements for RNA motif classification, prediction, partitioning, and design. (A) The RAG approach for RNA representation (42) and design (43, 45) is illustrated as: 1) tree graph of a riboswitch; 2) RAG tree graph catalog segments, organized by the second eigenvalue λ2 of the connectivity matrix (Laplacian) associated with the graph and classified by clustering into three groups: existing (red), RNA-like (blue), and non-RNA-like (black) motifs (see http://www.biomath.nyu.edu/rag/home for more information); 3) graph partitioning for a riboswitch by RAG-3D (44), which suggests modular RNA building blocks, for which PDB structures are available; and 4) fragment assembly of such subgraph fragments using the modular subunits. (B) RAGTOP for 3D structure prediction by a hierarchical MC sampling of tree graphs (46, 48, 49): 1) Initial junction topology prediction; 2) MC sampling of 3D graphs scored by a statistical scoring function with components for bend, twist, and radius-of-gyration; 3) clustering of generated graphs to identify candidate graph; and 4) determination of atomic models from the candidate graph using the fragment assembly based on RAG-3D subgraphs. To see this figure in color, go online.
Figure 3
Figure 3
3D model of two subdomains in lncRNA RepA. The two spatially proximal subdomains in lncRNA RepA (shown in purple and yellow) were modeled with RNAComposer using the experimentally identified crosslinks as distance constraints (54). The nucleotides participating in the crosslinks are shown in purple and red. The potential tertiary interactions between the two subdomains are represented with green arrows. To see this figure in color, go online.

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