Swellix: a computational tool to explore RNA conformational space

Advances in RNA 3D Structure Modeling Using Experimental Data

RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific three-dimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data. We also demonstrate how computational modeling can help the experimental determination of RNA structure. We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data.

Unveiling the druggable RNA targets and small molecule therapeutics

The increasing appreciation for the crucial roles of RNAs in infectious and non-infectious human diseases makes them attractive therapeutic targets. Coding and non-coding RNAs frequently fold into complex conformations which, if effectively targeted, offer opportunities to therapeutically modulate numerous cellular processes, including those linked to undruggable protein targets. Despite the considerable skepticism as to whether RNAs can be targeted with small molecule therapeutics, overwhelming evidence suggests the challenges we are currently facing are not outside the realm of possibility. In this review, we highlight the most recent advances in molecular techniques that have sparked a revolution in understanding the RNA structure-to-function relationship. We bring attention to the application of these modern techniques to identify druggable RNA targets and to assess small molecule binding specificity. Finally, we discuss novel screening methodologies that support RNA drug discovery and present examples of therapeutically valuable RNA targets.

Challenges and approaches to predicting RNA with multiple functional structures

The revolution in sequencing technology demands new tools to interpret the genetic code. As in vivo transcriptome-wide chemical probing techniques advance, new challenges emerge in the RNA folding problem. The emphasis on one sequence folding into a single minimum free energy structure is fading as a new focus develops on generating RNA structural ensembles and identifying functional structural features in ensembles. This review describes an efficient combinatorially complete method and three free energy minimization approaches to predicting RNA structures with more than one functional fold, as well as two methods for analysis of a thermodynamics-based Boltzmann ensemble of structures. The review then highlights two examples of viral RNA 3'-UTR regions that fold into more than one conformation and have been characterized by single molecule fluorescence energy resonance transfer or NMR spectroscopy. These examples highlight the different approaches and challenges in predicting structure and function from sequence for RNA with multiple biological roles and folds. More well-defined examples and new metrics for measuring differences in RNA structures will guide future improvements in prediction of RNA structure and function from sequence.