Bioinformatic Design and Computational Validation of siRNA Targeting the MYC Proto-Oncogene

Abstract

Background: RNA-based therapeutics are rapidly advancing in clinical trials for the treatment of various diseases, particularly cancer, through the use of nucleic acid–based drugs that directly regulate gene expression at the molecular level and suppress transcription by degrading target RNA via small interfering RNAs (siRNAs). Genetic studies have shown that overexpression of the MYC proto-oncogene, caused by genomic amplification, is observed in up to 70% of hepatocellular carcinoma cases associated with viral infections and alcohol-related liver disease. The MYC proto-oncogene influences key signaling pathways such as PI3K/Akt/mTOR, Wnt/β-catenin, and MAPK/ERK in hepatocellular carcinoma, thereby enhancing protein synthesis required for tumor cell growth, increasing transcriptional activity, promoting tumor progression, and enabling immune evasion. Consequently, the concept of inhibiting the MYC oncogene has gained increasing attention. Aim: To design multi-transcript–specific siRNAs targeting the MYC proto-oncogene using bioinformatics approaches and to investigate their effects on hepatocellular carcinoma cells. Materials and Methods: Using an in silico experimental design, 15 transcript candidates encoding a specific protein of the MYC proto-oncogene were retrieved from Ensembl and aligned to identify the most conserved regions across all transcripts, which were then used for subsequent siRNA prediction. Selected coding sequence (CDS) variants were analyzed using siDirect 2.1, and three candidate variants were further validated based on the following criteria: siExplorer ≥ 60, OligoWalk ≥ 0.7, and siPRED ≥ 70%. The GC content of the siRNA duplexes, the presence of palindromic sequences in both antisense and sense strands, and the specificity of binding to the target mRNA sites were predicted. Additionally, the three-dimensional structure of the protein was modeled. Results: By aligning transcript candidates encoding a specific protein of the MYC proto-oncogene and identifying the most conserved regions, three potential candidate variants (s1, s2, s3) were predicted and further validated: s1 (siExplorer ≥ 79.9, OligoWalk ≥ 0.9, siPRED ≥ 85.5%), s2 (siExplorer ≥ 64.2, OligoWalk ≥ 0.87, siPRED ≥ 91.9%), s3 (siExplorer ≥ 67.7, OligoWalk ≥ 0.81, siPRED ≥ 91.6%). The siRNA sequences exhibited recommended GC content and showed no off-target binding. When modeling the three-dimensional structure by incorporating the predicted antisense siRNA strand into the spatial structure of Ago2, the siRNA was positioned in a biologically compatible manner within the PAZ–MID domain region, and the siRNA–Ago2 complex remained stable in its final conformation. Conclusion: In this study, three multi-transcript–specific siRNAs targeting MYC proto-oncogene mRNA were successfully designed as potential therapeutic candidates against hepatocellular carcinoma. The selected siRNAs demonstrated strong binding afÏnity to Ago2. Further validation through in vitro and in vivo studies is required.