Theoretical modeling of in vitro selection of RNAs

In vitro selection is a versatile experimental technology for discovering novel functional RNAs from random-sequence pools. In the last decade, many target-binding and catalytic RNAs have been identified for wide-ranging applications, including RNA-based biosensors, molecular therapeutics, synthetic biology, and nanotechnology.  Thus, theoretical modeling of in vitro selection of RNAs will help advance vital applications.

Current use of random pools for in vitro selection experiments has inherent limitations, including non-exhaustive coverage of sequence space and prevalence of simple topological motifs (e.g., stem-loop, stem-bulge-stem-loop). To improve RNA in vitro selection technology, synthesized RNA pools must possess sufficient sequence and structural complexity to enable discovery of complex RNA molecules (e.g., allosteric ribozymes).

Our aim is to develop computational methods for designing RNA pools with diverse sequences and structures. Recently, we have made progress in analysis and design of sequence pools. We showed quantitatively that random pools are not structurally diverse, confirming results from various in vitro selection experiments. We have also developed an automated algorithm for designing pools with user-specified target structural distribution (e.g., specific topological structures or graphs representing RNA trees). The algorithm optimizes the nucleotide mixing matrix or nucleotide mixing ratios in synthesis ports.  This algorithm has been implemented in a web server RAGPOOLS to allow experimentalists and other researchers to analyze and design RNA pools.

We are continuing development of efficient computational techniques for designing RNA pools and collaborating with experimentalists to test pool design strategies. In particular, we are exploringMonte Carlo strategies for efficient sampling of the sequence and structure space. We are also developing theoretical approaches to directed evolution, an experimental method for refining RNA function via cycles of mutations and function selection. Theoretical modeling of RNA in vitro selection and directed evolution requires close collaboration with experimentalists, a deep understanding of the relation between RNA structure and function, and innovative computational/mathematical techniques to model aspects of the experimental technology (i.e., pool synthesis, RNA selection and evolution).

Computational RNA tertiary folding and design

Current tertiary RNA folding simulations are limited to small systems (e.g., RNA hairpins), and RNA design algorithms are confined to analysis of 2D structures. In contrast, in protein folding and design, emerging computational concepts and technologies such as fragment assembly and 3D-based design have proven successful. To overcome current limitations in RNA structure prediction, we are combining computational technologies for proteins with knowledge of various RNA tertiary interaction motifs to develop effective approaches for predicting RNA tertiary structures. W e are also developing a 3D-based framework for computational RNA engineering to extend the capability and precision of current 2D design algorithms. This framework for molecular engineering, which includes advanced dynamics analysis tools, allows analysis of the functional properties of designed RNAs through computation of tertiary structures, RNA-ligand binding and dynamics. Specifically, we are interested in engineering RNA systems such as allosteric ribozymes, riboswitches and fluorescent aptamers for emerging applications in bioengineering.

Other approaches to RNA structure and function

We are also pursuing other approaches to RNA structure and function. For example, we have used in vitro selected RNAs to find RNA motifs in genomes and employed statistical techniques to estimate the fraction of non-coding RNAs in mammalian transcriptomes (i.e., total expressed transcripts in cells). In addition, we are developing computational approaches to identify novel target sites for antibiotics on bacterial ribosomal RNAs. This work involves assessing the energetics of antibiotic/rRNA binding and relating sequence conservation to phenotypes of rRNA mutations.