RNA molecules are important cellular components involved in many fundamental biological roles. Because the structural features of RNA are intimately connected to their biological function, there is great interest in predicting RNA structure from sequence. The proposed research addresses both RNA structure prediction - development of a hierarchical modeling approach using graph theory and statistical tools, and RNA design - engineering fluorescent riboswitches that can "sense" transcription termination, offering researches visualization of the process in vivo. The proposed approach requires development of new mathematical and statistical/computer science tools for sampling RNA graph objects efficiently in 3D - to provide an initial, coarse level of sampling - and for developing systematically structure-based statistical approaches to score RNA conformations using data-mining tools. Extensive analysis of RNA junction motifs based on known structures will be used to develop separate local and global statistical potentials to predict both local geometric orientations, as well as global long-range interactions. These RNA models and associated potentials will be combined and carefully tested in three inter-related stages of folding in the following hierarchical design: (1) Explore RNA's structural conformation space coarsely using MC sampling on tree graphs that represent RNA 2D structures embedded in 3D lattices with statistical potentials that select RNA-like conformations;(2) Improve prediction accuracy using a coarse-grained three-bead-per-nucleotide model with a higher-level statistical potential to guide 3D assembly;and (3) Refine the best candidates using dynamics simulations on full atomistic models with force-field potentials. After careful analysis followed by development and testing of the new mathematical tools, each stage of the plan will be refined to finally integrate the components. New design applications for fluorescent riboswitches will be pursued, by marrying known elements of fluorescent aptamers with ligand-based configurational rearrangements of riboswitches that control gene expression.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM100469-03
Application #
8508960
Study Section
Special Emphasis Panel (ZGM1-CBCB-5 (BM))
Program Officer
Preusch, Peter C
Project Start
2011-09-09
Project End
2015-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
3
Fiscal Year
2013
Total Cost
$365,520
Indirect Cost
$117,003
Name
New York University
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
041968306
City
New York
State
NY
Country
United States
Zip Code
10012
Jung, Segun; Schlick, Tamar (2014) Interconversion between parallel and antiparallel conformations of a 4H RNA junction in domain 3 of foot-and-mouth disease virus IRES captured by dynamics simulations. Biophys J 106:447-58
Kim, Namhee; Zheng, Zhe; Elmetwaly, Shereef et al. (2014) RNA graph partitioning for the discovery of RNA modularity: a novel application of graph partition algorithm to biology. PLoS One 9:e106074
Kim, Namhee; Laing, Christian; Elmetwaly, Shereef et al. (2014) Graph-based sampling for approximating global helical topologies of RNA. Proc Natl Acad Sci U S A 111:4079-84
Jung, Segun; Schlick, Tamar (2013) Candidate RNA structures for domain 3 of the foot-and-mouth-disease virus internal ribosome entry site. Nucleic Acids Res 41:1483-95
Laing, Christian; Jung, Segun; Kim, Namhee et al. (2013) Predicting helical topologies in RNA junctions as tree graphs. PLoS One 8:e71947
Laing, Christian; Wen, Dongrong; Wang, Jason T L et al. (2012) Predicting coaxial helical stacking in RNA junctions. Nucleic Acids Res 40:487-98
Quarta, Giulio; Sin, Ken; Schlick, Tamar (2012) Dynamic energy landscapes of riboswitches help interpret conformational rearrangements and function. PLoS Comput Biol 8:e1002368