Small Activation RNA Designer
Small Activation RNA Designer
Overview
The Advanced saRNA Designer is a robust, client-side computational pipeline engineered for the rational design and thermodynamic profiling of small activating RNAs (saRNAs). Designed specifically to target gene promoter regions, this tool facilitates RNA activation (RNAa) research by streamlining sequence optimization, calculating duplex stability, and conducting rigorous in silico off-target mitigation.
Core Algorithm & Thermodynamic Modeling
To ensure the selection of highly functional guide strands, the pipeline applies strict sequence biogenesis and Argonaute (AGO2) loading rules. The algorithm filters candidates based on:
Asymmetry & Loading Bias: Enforcement of 5' G/C and 3' A/T requirements, alongside customizable 3' end A/T richness filters, to promote thermodynamic asymmetry and ensure proper guide strand selection by the RISC complex.
Structural Stability: Optimal GC content thresholding (default 35-65%) and homopolymer exclusion (avoiding ≥ 4 consecutive identical nucleotides) to prevent off-target protein binding and unwanted immune stimulation.
Nearest-Neighbor Thermodynamics: Duplex free energy (ΔG) is calculated using standard Turner nearest-neighbor parameters. The model algorithmically integrates helix initiation penalties (+3.4 kcal/mol) and terminal A/U penalties (+0.5 kcal/mol) to provide high-fidelity thermodynamic predictions that align with industry-standard folding algorithms.
Integrated Off-Target Mapping (NCBI BLASTN)
A critical challenge in RNA therapeutics is avoiding unintended gene silencing or activation. The Advanced saRNA Designer addresses this through a seamlessly integrated, asynchronous NCBI BLASTN module.
Sequential Homology Search: Candidates are automatically queried against the human nt database (txid9606) to evaluate off-target potential.
Automated Classification: Results are dynamically parsed and categorized by sequence type, distinguishing between curated mRNAs (NM_), non-coding RNAs (NR_), genomic scaffolds, and predicted transcripts.
E-value Distribution: Hits are visually mapped across interactive charts based on Expect (E) values, allowing researchers to rapidly assess the statistical significance of off-target alignments.
Reproducibility & Export
Built with open-science principles, the framework requires no backend server, ensuring complete data privacy for proprietary sequences. Researchers can export detailed Off-Target Maps and thermodynamic profiles in publication-ready formats, including high-resolution PNG, dynamically generated PDF reports, and CSV datasets for downstream analysis.