Identifying and avoiding off-target effects of RNase H-dependent antisense oligonucleotides in mice.

Antisense oligonucleotides that are dependent on RNase H for cleavage and subsequent degradation of complementary RNA are being developed as therapeutics. Besides the intended RNA target, such oligonucleotides may also cause degradation of unintended RNA off-targets by binding to partially complementary target sites. Here, we characterized the global effects on the mouse liver transcriptome of four oligonucleotides designed as gapmers, two targeting Apob and two targeting Pcsk9, all in different regions on their respective intended targets. This study design allowed separation of intended- and off-target effects on the transcriptome for each gapmer. Next, we used sequence analysis to identify possible partially complementary binding sites among the potential off-targets, and validated these by measurements of melting temperature and RNase H-cleavage rates. Generally, our observations were as expected in that fewer mismatches or bulges in the gapmer/transcript duplexes resulted in a higher chance of those duplexes being effective substrates for RNase H. Follow-up experiments in mice and cells show, that off-target effects can be mitigated by ensuring that gapmers have minimal sequence complementarity to any RNA besides the intended target, and that they do not have exaggerated binding affinity to the intended target.

Chemical Diversity of Locked Nucleic Acid-Modified Antisense Oligonucleotides Allows Optimization of Pharmaceutical Properties.

The identification of molecules that can modulate RNA or protein function and the subsequent chemical and structural optimization to refine such molecules into drugs is a key activity in drug discovery. Here, we explored the extent to which chemical and structural differences in antisense oligonucleotides, designed as gapmers and capable of recruiting RNase H for target RNA cleavage, can affect their functional properties. To facilitate structure-activity learning, we analyzed two sets of iso-sequential locked nucleic acid (LNA)-modified gapmers, where we systematically varied the number and positions of LNA modifications in the flanks. In total, we evaluated 768 different and architecturally diverse gapmers in HeLa cells for target knockdown activity and cytotoxic potential and found widespread differences in both of these properties. Binding affinity between gapmer and RNA target, as well as the presence of certain short sequence motifs in the gap region, can explain these differences, and we propose statistical and machine-learning models that can be used to predict region-specific, optimal LNA-modification architectures. Once accessible regions in the target of interest have been identified, our results show how to refine and optimize LNA gapmers with improved pharmacological profiles targeting such regions.