In silico siRNA design for SNPs in HER family receptors: A potential cure for cancer

    Published on:23rd July 2015
    Journal of Young pharmacists, 2015; 7(4s):432-437
    Original Article | doi:10.5530/jyp.2015.4s.4

    Ravindra Babu Potti*, Jayasree Ganugapati, Aishwarya Mandava, Pranusha Reddy Mallepalli and Dharani Matha

    Department of Biotechnology, Sreenidhi Institute of Science and Technology, Yamnampet, Ghatkesar, Hyderabad-501301, India.


    Background: Silencing of a specific mRNA using double stranded RNA oligo nucleotides represents novel technologies for suppressing a specific gene product. Small interfering RNA (siRNA) are 21 nucleotides long, double stranded RNA fragments that interferes with the expression of specific genes with complementary nucleotide sequences. siRNA functions by breaking down mRNA after transcription, resulting in no translation. HER/ErbB is a family of receptors that has HER1, HER2, HER3 and HER4 as its members. Certain mutations in these receptors leads to its over expression. Amplification or over expression of these receptors has shown to play an important role in the development and progression of certain aggressive types of breast cancer, colon and gastric cancers. The SNPs in Her1 receptor were observed at first position, in HER2 at eighth position, in HER3 at first position and in HER4 at third position. Methods: siDirect is a software that enables In silico siRNA design. The parameters like GC Content and Thermodymics were considered for designing the siRNA sequences against selected mRNA sequences of HER family. The phylogram was also analyzed by constructing the mulpitle sequence alignment using Clustalw to assess the similarity between the siRNA target sequences. Results: The SNPs identified in HER1 , HER2 , HER3 , HER4 family of receptors are missense mutations, any change in nucleotide level are altering the protein sequence structure and function. The mRNA sequences with SNPs positions were submitted to the siRNA Direct 2.0. Set of possible siRNA sequences with 21 nucleotides and the positions where they are targeted. The best possible siRNA sequences were validated using online tools. Conclusion: The siRNA sequences that were identified are considered to be the best suitable for controlling the overexpression of the target mRNA sequences thereby minimizing the development of cancer.

    Key words: Breast cancer, Gene silencing, HER1, HER2, HER3, HER4, siRNA.

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