Prediction of RNA-RNA Interactions by Kinetic Modelling

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The majority of an organism's transcriptome does not consist of protein encoding RNA but represents so called non-coding RNA (ncRNA), most of them acting as regulatory elements. Many of these ncRNA molecules require interactions with protein-coding messenger RNAs or other ncRNAs to fulfill their regulatory functions. A detailed understanding of these RNA-RNA interactions gives insight into the regulatory networks of organisms.Due to the complexity and expense for experimental studies, there is a strong need for computational prediction approaches. Current methods are usually restricted to simple interaction types and show a low prediction accuracy.Within this project we will identify steric and topological features constraining known interactions to increase prediction quality of RNA-RNA interaction prediction models. Furthermore, we will define new models covering more general interaction patterns up to multi-site interactions. Identified features will be integrated both as hard constraints to avoid unrealistic structures and via pseudo energy terms for a better guiding of the applied optimization methods.This will be accompanied with an extensive research of the kinetics of RNA-RNA interactions, since it is able to guide the interaction formation to non-predictable, suboptimal structures. Therefore, new energy landscape models will be defined and implemented that allow for a detailed but still computationally accessible study of the energy landscape based kinetics. This includes the development of new methods for an efficient exploration of large energy landscapes as well as for the computation of transition model and kinetics.These two research fields are joined within new RNA-RNA interaction prediction pipelines that will respect the new structure constraints as well as account for kinetic effects defining the interaction formation. We will apply our new pipelines to investigate interaction networks for ncRNAs, to screen for targets of regulating ncRNAs, and to increase knowledge of the mechanistic details of certain binding pathways.One direction of application will be the investigation of the mechanistic details of anti-sense RNA interactions. Anti-sense RNAs are found in great extent in the transcriptome of pro- and eukaryotes while there is only limited knowledge about their regulatory impact. An especially interesting topic is to determine to what extent anti-sense transcripts actually form duplexes with their respective sense transcripts and what regulatory mechanisms are possible. Our computational studies will be supported by wet-lab experiments.Beside new insights, the project aims at the development of a large tool set to promote further research in this field. The targeted results do not only support RNA-RNA interaction studies but also enable progress for structure prediction of single molecules as well as kinetics studies of large energy landscapes of other systems.