Scientists have developed a solution-based high-throughput screening (HTS) technology that is capable of probing millions of different RNA-small molecule interactions to identify the best druggable RNA motifs and compounds that they interact with. The technology, reported by researchers at the University of Buffalo and Scripps Research Institute, combines solution-based HTS with microarray-based selection of the binding RNA motifs.
The work builds on a multidimensional combinatorial (MDCS, or library-versus-library screening) technology devised previously by the investigators, which could identify optimal RNA motifs from a library of secondary structures that bind small molecules. This approach, called 2DCS, involved hybridizing a small molecule microarray with a library of RNA motifs, such as internal loops, and then isolating the bound motifs and amplifying them before cloning and sequencing.
This technique, however, isn’t suitable for more traditional small molecule screens, which may be carried out in solution phase, explain Scripps researcher Matthew D. Disney, Ph.D., and Buffalo grad student Tuan Tran. To overcome this drawback, the new approach reported by Disney and Tran marries more conventional high-throughput solution-based screens with microarray-based selection. This method can be used to determine the features in RNA motifs such as hairpins, internal loops and bulges, as well as the features in small molecules, which determine high affinity, selective binding. Key to the technology is a solution-based dye-displacement screening assay that identifies the small molecules binding to RNA motif libraries. These binding molecules can then be subjected to microarray-based MDCS selection.
Interestingly, when Dr. Disney and Tran used the technology to probe a small molecule library biased for RNA binding against over 70,000 unique RNA motifs, they found that there was a significant bias for binding to RNA hairpin loops over thousands of other structures, including internal loops, bulges and base pairs. “For the first time we have been able to probe what types of small molecules would be good lead drugs to target RNA by probing millions of RNA-ligand combinations,” professor Disney comments. “In a viral genome, for example, RNA folds such as hairpin loops contribute to disease, but we don’t know which hairpin loops we should focus on. In the study, we were able to define those RNA motifs, including hairpin loops, that bind to small molecules and the types of small molecules that bind to RNA.”
Reporting in Nature Communications, the authors say they plan to use the platform to screen much larger, more chemically diverse small molecule libraries. Their published paper is titled “Identifying the preferred RNA motifs and chemotypes that interact by probing millions of combinations.”