Novel Computational Approaches to Developing Potential STAT4 Silencing siRNAs for Immunomodulation of Atherosclerosis

Abstract

Background: Small interfering RNAs (siRNAs) are known as commonly used targeting mRNAs tools for suppressing gene expression. Since Signal Transducer and Activator of Transcription 4 (STAT4) is considered as a significant transcription factor for generation and differentiation of Th1 cells during vascular dysfunction and atherosclerosis, suppressing STAT4 could represent novel immunomodulatory therapies against atherosclerosis. Objective: Therefore, the current study was conducted to design efficient siRNAs specific for STAT4 and to evaluate different criteria affecting their functionality. Methods: In the present study, all related sequences of STAT4 gene were retrieved from Gen Bank database. Multiple sequence alignment was carried out to recognize Open Reading Frame (ORF) and conserved region. Then, siDirect 2.0 server was applied for the development of candidate siRNA molecules and confirmation of predicted molecules was performed using Dharma siRNA technology and GeneScript siRNA targetfinder. In addition, BLAST tool was used against whole Genebank databases to identify potential off-target genes. DNA/RNA GC content calculator and mfold server were used to calculate GC content and secondary structure prediction of designed siRNA, respectively. Finally, IntaRNA program was used to study the thermodynamics of interaction between predicted siRNA and target gene. Results: Based on the obtained results, three efficient siRNA molecules were designed and validated for STAT4 gene silencing using computational methods, which may result in suppressing STAT4 gene expression. Conclusion: According to our results, this study shows that siRNA targeting STAT4 can be considered as a therapeutic agent in many Th1-mediated pathologic conditions specially atherosclerosis.