Determination of deleterious SNPs of PIK3CA gene and their impacts on the structure of PI3K

Introduction & Objectives: PIK3CA mutations are common activating mutations in breast cancer occurring in 20–30% of all cases. These mutations are potent predictive markers for responses to PI3K inhibitors in breast cancer. Also, they could have a negative impact on patient survival. The gene encodes the p110α catalytic subunit of PI3K. This protein plays a key role in PI3K/AKT/mTOR signaling pathway. Single nucleotide polymorphism presents in coding region of proteins (nsSNPs) has the potential to alter structure and function of the protein. Hence, it is necessary to differentiate the potential harmful nsSNPs from the neutral ones.Methods: In the present study, using NCBI dbSNP database, 26 nsSNPs were retrieved and functionally deleterious nsSNPs predicted by two different in silico tools including SIFT and Poly-Phen-2. The I-Mutant 2.0 server was used to predict the change of protein stability due to mutations. Degree of conservation of mutations among the populations was determined using MEGA 7 software. The Secondary structure of protein was predicted by PSIPRED. In order to further analyze the effect of the deleterious mutation on the protein structure, the complete PI3K protein structure was modelled by SWISS-MODEL and analyzed using PyMOL.Results: 6 nsSNPs including V344M, I112N, V356I, E135K, G914R, and E545V were predicted as highly deleterious and thus subjected to further analyses, such as conservation, stability, 2D and 3D structure. Results showed that these nsSNPs are highly conserved and can decrease protein stability. In addition, they change secondary structure including beta sheets and coils in mutant proteins. Hydrogen bond formation is altered due to mutations as analyzed by PyMOL.Conclusion: Our data suggest that structure and function of PI3K can be disturbed by various nsSNPs and this in silico analysis will be of great help while considering large scale gene studies and also in developing drugs.

کلیدواژه ها:

PIK3CA ، nsSNP ، in silico tools ، Mutation ، Breast cancer