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.

Software for predicting the 3D structure of RNA molecules

“…Given the limitation of space for this review, here we have very briefly introduced a limited number of software packages for each of the categories for RNA structure prediction. The readers are encouraged to read the references to those programs or acquire further knowledge in several reviews that cover each category in greater deepness …”

Modeling, Simulations, and Bioinformatics at the Service of RNA Structure

“…Again, involvement of the experimental community would seem necessary in the development of more reliable tools. Methods based on the hierarchical folding hypothesis can use as building blocks either secondary structures 123 (experimentally known or predicted 125,126 ) or local mini-motifs (<4 nt) whose geometries are arranged in space to minimize some scoring function. 127,128 Such functions are generally statistical potentials based on pairwise interactions either at atomic or coarse-grained levels and focus on an ever-evolving play-off between computational efficacy and accurate energetic description.…”

“…We are far from being able to predict the structure of complex RNA motifs, but recent theoretical methods, either alone or coupled with experimental restraints, are providing very encouraging results, 125 visible in the latest rounds of the RNA-Puzzles competition (Figure 4). 151 For example, Pyle's group 152 recently modeled domains D2 and D3 of RepA (long non-coding RNA of 1,600 nt) with a variety of experimental restraints using RNAComposer and came up with reasonable results, and Bujnicki's group (the developers of ModeRNA 121 ) extracted structural fragments corresponding to evolutionarily conserved regions and successfully used this information to constrain the geometry of conserved residues when folding large RNA constructs.…”

Progress and Current Challenges in Modeling Large RNAs

“…In addition, strategies such as mutate and map [102] can inform on tertiary contacts. As reviewed recently [103] and discussed above, several tools can readily incorporate experimental data to obtain a modeled RNA structure. Integrating the experimental data has shown to achieve reasonable accuracies (RMSD ~10 Å) for mid-sized RNAs (~150 nts) [101].…”