The Mathews lab studies the computational biology of RNA. We predict RNA structure at secondary structure resolution, i.e. base pairing, and at tertiary structure resolution, i.e. 3-D structure. We also work to understand how structure changes and fluctuates over time, i.e. dynamics.
For RNA secondary structure prediction, we tackle three big challenges. The first is prediction of pseudoknotted pairs (1). The second is the prediction of the structure conserved in a set of homologous sequences (2,3). The third is using experimental data to constrain or restrain structure prediction to improve accuracy. We collaborate with Gaurav Sharma, Department of Electrical & Computer Engineering, on prediction of conserved structures; Kevin Weeks, Department of Chemistry, University of North Carolina, Chapel Hill, on using SHAPE data to restrain structure prediction (4); Anne Condon, Department of Computer Science, University of British Columbia, on using known structures to refine the free energy rules (5); and Doug Turner, Department of Chemistry, on using experimental data to refine the free energy rules (6,7). We develop and distribute RNAstructure, a software package for secondary structure prediction and analysis. We also develop the NNDB, which provides and explains the nearest neighbor rules for prediction the stability of an RNA secondary structure.
For tertiary structure prediction, we model structure using low resolution data that are available from comparative sequence analysis, coaxial stacking prediction, and cross-linking data, when available (8). These data provide enough information to construct models that are able to demonstrate most of the base-base contact features in structures determined by x-ray crystallography.
We use the AMBER package to study RNA dynamics. We have been predicting free energy changes for conformational changes in small systems that can be compared to experiment. We actively collaborate with Ross Walker, San Diego Supercomputer Center.
We also work on practical applications of our tools. We developed methods for siRNA design and for the discovery of RNA-coding genes in genomes (9,10). We collaborate with Beatrix Suess, Institut für Molekulare Biowissenschaften, University of Frankfurt, and Todd Lowe, Biomolecular Engineering, University of California, Santa Cruz, on the discovery of RNA-coding genes in genomes. In collaboration with Robert Bambara, Department of Biochemistry & Biophysics, we discovered a tRNA-like gene embedded in HIV (11).
The Mathews lab trains graduate students in Biophysics, Structural & Computational Biology, Biochemistry & Molecular Biology, Chemistry, and Physics.
Selected References: (A complete list of Mathews lab publications can be found here.)
1. Bellaousov, S. and Mathews, D.H. (2010) ProbKnot: Fast prediction of RNA secondary structure including pseudoknots. RNA, 16, 1870-1880.
2. Xu, Z. and Mathews, D.H. (2011) Multilign: an algorithm to predict secondary structures conserved in multiple RNA sequences. Bioinformatics, 27, 626-632.
3. Harmanci, A.O., Sharma, G. and Mathews, D.H. (2011) TurboFold: Iterative probabilistic estimation of secondary structures for multiple RNA sequences. BMC Bioinformatics, 12, 108.
4. Deigan, K.E., Li, T.W., Mathews, D.H. and Weeks, K.M. (2009) Accurate SHAPE-directed RNA structure determination. Proc. Natl. Acad. Sci. U.S.A., 106, 97-102.
5. Andronescu, M., Condon, A., Hoos, H.H., Mathews, D.H. and Murphy, K.P. (2010) Computational approaches for RNA energy parameter estimation. RNA, 16, 2304-2318.
6. Liu, B., Diamond, J.M., Mathews, D.H. and Turner, D.H. (2011) Fluorescence Competition and Optical Melting Measurements of RNA Three-Way Multibranch Loops Provide a Revised Model for Thermodynamic Parameters. Biochemistry, 50, 640-653.
7. Turner, D.H. and Mathews, D.H. (2010) NNDB: the nearest neighbor parameter database for predicting stability of nucleic acid secondary structure. Nucleic Acids Res., 38, D280-282.
8. Seetin, M.G. and Mathews, D.H. (2011) Automated RNA tertiary structure prediction from secondary structure and low-resolution restraints. J. Comput. Chem., 32, 2232-2244.
9. Lu, Z.J. and Mathews, D.H. (2007) Efficient siRNA Selection Using Hybridization Thermodynamics. Nucleic Acids Res., 36, 640-647.
10. Uzilov, A.V., Keegan, J.M. and Mathews, D.H. (2006) Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change. BMC Bioinformatics, 7, 173.
11. Piekna-Przybylska, D., DiChiacchio, L., Mathews, D.H. and Bambara, R.A. (2009) A sequence similar to tRNA3Lys gene is embedded in HIV-1 U3/R and promotes minus strand transfer Nature Structural & Molecular Biology, 17, 83-89.