Determination of potent antisense oligonucleotides in vitro by semiempirical rules

Integrating Machine Learning-Based Approaches into the Design of ASO Therapies

Rare diseases impose a significant burden on affected individuals, caregivers, and healthcare systems worldwide. Developing effective therapeutics for these small patient populations presents substantial challenges. Antisense oligonucleotides (ASOs) have emerged as a promising therapeutic approach that targets the underlying genetic cause of disease at the RNA level. Several ASOs have gained FDA approval for the treatment of genetic conditions, including use in personalized N-of-1 trials. However, despite their potential, ASOs often exhibit limited clinical efficacy, and optimizing their design is a complex process influenced by numerous factors. Machine learning-based platforms, including eSkip-Finder and ASOptimizer, have been developed to address these challenges by predicting optimal ASO sequences and chemical modifications to enhance efficacy. eSkip-Finder focuses on exon-skipping applications, while ASOptimizer aims to optimize ASOs for RNA degradation. Preliminary in vitro results have demonstrated the promising predictive power of these platforms. However, limitations remain, including their generalizability to alternative targets and gaps in their consideration of all factors influencing ASO efficacy and safety. Continued advancements in machine learning models, alongside efforts to incorporate additional features affecting ASO efficacy and safety, hold significant promise for the field. These platforms have the potential to streamline ASO development, reduce associated costs, and improve clinical outcomes, positioning machine learning as a key tool in the future of ASO therapeutics.

Real time monitoring of endogenous cytoplasmic mRNA using linear antisense 2'-O-methyl RNA probes in living cells

Visualization and monitoring of endogenous mRNA in the cytoplasm of living cells promises a significant comprehension of refined post-transcriptional regulation. Fluorescently labeled linear antisense oligonucleotides can bind to natural mRNA in a sequence-specific way and, therefore, provide a powerful tool in probing endogenous mRNA. Here, we investigated the feasibility of using linear antisense probes to monitor the variable and dynamic expression of endogenous cytoplasmic mRNAs. Two linear antisense 2'-O-methyl RNA probes, which have different interactive fluorophores at the 5'-end of one probe and at the 3'-end of the other, were used to allow fluorescence resonance energy transfer (FRET) upon hybridization to the target mRNA. By characterizing the formation of the probe-mRNA hybrids in living cells, we found that the probe composition and concentration are crucial parameters in the visualization of endogenous mRNA with high specificity. Furthermore, rapid hybridization (within 1 min) of the linear antisense probe enabled us to visualize dynamic processes of endogenous c-fos mRNA, such as fast elevation of levels after gene induction and the localization of c-fos mRNA in stress granules in response to cellular stress. Thus, our approach provides a basis for real time monitoring of endogenous cytoplasmic mRNA in living cells.