Computational Engineering of siRNA Molecules to Silence SphK1 mRNA for Therapeutic Intervention in Triple-Negative Breast Cancer

Abstract Triple-negative breast cancer (TNBC) is an aggressive and treatment-resistant subtype of breast cancer that contributes significantly to cancer-related mortality in women. Characterized by the absence of estrogen, progesterone, and HER2 receptors, TNBC does not respond to standard hormonal or HER2-targeted therapies. Its high metastatic potential and poor prognosis highlight the urgent need for novel targeted strategies. Overexpression of sphingosine kinase 1 (SphK1), a key regulator of the bioactive sphingolipid metabolite sphingosine-1-phosphate (S1P), has been linked to tumor progression, metastasis, and therapy resistance in TNBC. In this study, we employed integrative bioinformatics approaches to design and evaluate small interfering RNA (siRNA) molecules aimed at silencing SphK1 expression. Computational tools including Schrödinger, siDirect v2.0, i-Score Designer, and HDOCK were used to screen and validate siRNA candidates with minimal off-target effects, high mRNA binding affinity, and stable secondary structures. Among the designed candidates, g6 siRNA demonstrated the strongest predicted binding and stable interaction with Argonaute 2 (Ago2), a critical component of the RNA-induced silencing complex. These in silico results highlight the value of computational strategies in rational siRNA design and provide a strong basis for future experimental studies to develop targeted gene-silencing therapeutics for TNBC.