Introduction
RAG-3D, is a web-based search tool that allows the user to search for structural similarities of a query RNA within a dataset of non-redundant RNA structures. This RNA structural search approach exploits RNA graph theory largely used in our lab, specifically subgraphs isomorphism, to efficiently search for structural similarities in our database. The existence of smaller topologies within larger RNA structures was previously investigated in our lab at the 2D structural level using RNA-As-Graphs (RAG) database.
RAG-3D allows for the automatic search of similar fragments within the RNA 3D structures and substructures available in this database. The user provides a file in a PDB format or a PDB ID, and receives as output a list of structures or substructures found in our 3D-RAG database with lowest RMSD value with the query structure or substructure. The function of the matching structure is provided and gives a good indicator of the possible function of the query RNA.
Input of RAG-3D
RAG-3D provides an intuitive user interface. The user can choose to load a structure from the PDBs ID listed, enter a PDB ID, or upload a PDB file, as described below:
- Choose an example from the PDB list (1), enter a PDB ID (2), or upload a file in the PDB format (3) to be queried.
- Click on « Search RAG-3D » to search for similarities
Output of RAG-3D
RAG-3D returns:
- The query files and information
- Topology information and detailed analysis of the secondary structure motifs according to RAG definitions
- List of the matching RNA fragments found in our database, and their corresponding 3D-graph coordinates
- All-atom coordinates
- Functions
The hits found are listed according to their RMSD value to the query RNA.
References
- Mai Zahran, Cigdem Sevim Bayrak, Shereef Elmetwaly, and Tamar Schlick, "RAG-3D: A Search Tool for RNA 3D Substructures", Submitted, (2015).
- Namhee Kim, Christian Laing, Shereef Elmetwaly, Segun Jung, Jeremy Curuksu, and Tamar Schlick. Graph-based sampling for approximating global helical topologies of RNA. PNAS, 111(11):4079-84 (2014).
- Christian Laing, Segun Jung, Namhee Kim, Shereef Elmetwaly, Mai Zahran, and Tamar Schlick. Predicting Helical Topologies in RNA Junctions as Tree Graphs. PLoS ONE, 8(8): e71947, DOI:10.1371/journal.pone.0071947 (2013).
- Joseph Izzo, Namhee Kim, Shereef Elmetwaly, and Tamar Schlick. RAG: An Update to the RNA-As-Graphs Resource. BMC Bioinformatics, 12: 219 (2011).
- Hin Hark Gan, Daniela Fera, Julie Zorn, Nahum Shiffeldrim, Michael Tang, Uri Laserson, Namhee Kim, and Tamar Schlick. RAG: RNA-As-Graphs Database - Concepts, Analysis, and Features. Bioinformatics, 20(8):1285-91 (2004).
- Hin Hark Gan, Samuela Pasquali, and Tamar Schlick. Exploring the repertoire of RNA secondary motifs using graph theory with implications for RNA design. Nucleic Acids Res., 31, 2926-2943 (2003).
Acknwlegements
RAG3D makes use of:
- RCSB Protein Data Bank
- RNAVIEW: Yang, H., Jossinet, F., Leontis, N., Chen, L., Westbrook, J., Berman, H.M., Westhof, E. (2003). Tools for the automatic identification and classification of RNA base pairs. Nucleic Acids Research 31.13: 3450-3460
- K2N: Sandra Smit, Kristian Rother, Jaap Heringa, and Rob Knight. From knotted to nested RNA structures: a variety of computational methods for pseudoknot removal. RNA (2008) 14(3):410-416
- Jmol: An open-source Java viewer for chemical structures in 3D
Notes & Limitations
- Users need to enable java applet for the Jmol to work. Instructions
- Results are available online for 7 days using the same link
- Substructure matching is limited to 10 vertices (or approx. 300 nucleotides)
- Colors of the graph topologies (Red, Blue, or Black) are done according to the RAG 2D original definitions and as a result of the current clustering technique