Computational modeling of RNA 3D structures, with the aid of experimental restraints

Abstract

In addition to mRNAs whose primary function is transmission of genetic information from DNA to proteins, numerous other classes of RNA molecules exist, which are involved in a variety of functions, such as catalyzing biochemical reactions or performing regulatory roles. In analogy to proteins, the function of RNAs depends on their structure and dynamics, which are largely determined by the ribonucleotide sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that simulate either the physical process of RNA structure formation (“Greek science” approach) or utilize information derived from known structures of other RNA molecules (“Babylonian science” approach). All computational methods suffer from various limitations that make them generally unreliable for structure prediction of long RNA sequences. However, in many cases, the limitations of computational and experimental methods can be overcome by combining these two complementary approaches with each other. In this work, we review computational approaches for RNA structure prediction, with emphasis on implementations (particular programs) that can utilize restraints derived from experimental analyses. We also list experimental approaches, whose results can be relatively easily used by computational methods. Finally, we describe case studies where computational and experimental analyses were successfully combined to determine RNA structures that would remain out of reach for each of these approaches applied separately.

Keywords: :

• RNA structure
• RNA structure prediction
• macromolecular modeling
• bioinformatics
• chemical probing

10.4161/rna.28826

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.

Acknowledgments

The research on the development of methods for RNA 3D structure modeling in the Bujnicki laboratory has been funded from several sources. Boniecki M and in general the development and application of RNA folding methods that use distance restraints from FRET experiments have been supported by the German Science Foundation (DFG) within SPP 1258 (grant no. SE 1195/12-2 coordinated by Claus Seidel). Chojnowski G, Łach G, Magnus M, Matelska D, and Purta E were supported by the Foundation for Polish Science (FNP, grant TEAM/2009-4/2 to Bujncki JM). Bujncki JM and Dunin-Horkawicz S were supported by the European Research Council (ERC, StG grant RNA⁺P = 123D to Bujncki JM). Dawson W was supported by the European Commission (EC; FP7 grant FishMed, 316125). The development of our bioinformatics servers was funded mainly by the Polish Ministry of Science and Higher Education (MNiSW, grant POIG.02.03.00-00-003/09 to Bujncki JM). Bujncki JM was additionally supported by the “Ideas for Poland” fellowship from the FNP. Dunin-Horkawicz S and Chojnowski G were additionally supported by the National Science Centre (NCN, grants 2011/03/D/NZ8/03011 to Dunin-Horkawicz S and 2011/01/D/NZ1/00212 to Chojnowski G). Dunin-Horkawicz S also acknowledges support from the Polish Ministry of Science and Higher Education (MNiSW, fellowship for outstanding young scientists).

We thank Juliusz Stasiewicz, Tomasz Waleń, Irina Tuszyńska, and Anna Philips for their participation in the development of RNA modeling methods in the Bujnicki laboratory. We also thank Eric Westhof, Jan Gorodkin, Claus Seidel, and Stanislav Kalinin for stimulating discussions and helpful advice on various occasions. Bujncki JM thanks Andrzej Sokalski for an inspirational reference to “Greek science” and “Babylonian science” in the context of chemical structures and interactions.