In silico analysis of nsSNPs in ABCB1 gene affecting breast cancer associated protein P-glycoprotein (P-gp)

Abstract

Breast cancer is one of the most common cancers among women and increased expression of some polymorphic genes, which is rare within families, enhances the risk of breast cancer incidence. The correct identification of the functional SNPs of such genes is important for characterizing the functional aspect of these SNPs which can be assessed by evaluating their significant influence on the structure and function of proteins. Since the presence of SNPs in these genes affects the quality of life of a breast cancer patient, thus, the associated diagnostic markers have a reliable potential for assessing the prognosis of breast cancer. ATP-binding cassette (ABC) genes have been shown to obstruct the treatment of breast cancer by providing resistance to malignant cells from anti-cancer drugs. Some allelic variants of ABCG2 and ABCB1 are also associated with occurrence of skin toxicity during the treatment of breast cancer with anti-cancer drugs. The present study has incorporated comprehensive bioinformatics analysis to explore the possible disease-associated mutations of ABCB1 gene, a gene that resulted from gene-environment interaction study, and understand their consequential effect on the structural and functional behavior of P-glycoprotein. Two gene variants (R538S and M701R) of P-glycoprotein were selected as potentially detrimental point mutations, and these variants were modeled. Molecular dynamic simulation (MDS) studies unraveled the atomic interactions and motion trajectories of the native as well as the two mutant (R538S and M701R) structures and were predicted to have a deleterious effect on breast cancer associated P-gp. Thus, the present study may broaden the way to design novel potent drugs for overcoming the problems associated with multidrug resistance (MDR) resulting from a change in protein conformation due to a mutation in ABCB1 gene.

Keywords: ABCB1 gene; Breast cancer; Gene-environment interaction (GEI); Molecular dynamic simulation (MDS); Multidrug resistance (MDR); Non-synonymous SNPs (nsSNPs); P-glycoprotein.