Identifying and validating small molecules interacting with RNA (SMIRNAs)

识别和验证与 RNA 相互作用的小分子 (SMIRNA)

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作者:Matthew D Disney, Sai Pradeep Velagapudi, Yue Li, Matthew G Costales, Jessica L Childs-Disney

Abstract

High throughput sequencing has revolutionized our ability to identify aberrant RNA expression and mutations that cause or contribute to disease. These data can be used directly to design oligonucleotide-based modalities using Watson-Crick pairing to target unstructured regions in an RNA. A complementary, although more difficult, strategy to deactivate a malfunctioning RNA is to target highly structured regions with small molecules. Indeed, RNA structures are directly causative of disease. Herein, we discuss emerging strategies to design high affinity, selective, bioactive ligands targeting RNA, or small molecules interacting with RNA (SMIRNAs), and target validation and profiling methods. An experimental foundation is required for a lead identification strategy for RNA structures, constructed from a library-vs.-library screen that probes vast libraries of small molecules for binding RNA three dimensional folds. Dubbed 2-dimensional combinatorial screening (2DCS), the resulting data can be mined against transcriptomes or the composite of RNAs that are produced in an organism to define folded RNA structures that can be targeted. By applying SMIRNAs to cells and using target validation tools such as Chemical Cross-Linking and Isolation by Pull-down (Chem-CLIP) and Small Molecule Nucleic Acid Profiling by Cleavage Applied to RNA (RiboSNAP), all targets engaged in cells can be defined, along with rules for molecular recognition to affect RNA biology. This chapter will describe lessons learned in applying these approaches in vitro, in cells, and in pre-clinical animal models of disease, enabling SMIRNAs to capture opportunities in chemical biology.

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