Exploring pathogenic SNPs and estrogen receptor alpha interactions in breast cancer: An in silico approach

Abstract

The estrogen receptor 1 gene (ESR1) plays a crucial role in breast and mammary development in humans. Alterations such as gene amplification, genomic rearrangements, and missense mutations in the ESR1 gene are reported to increase the risk of breast cancer in humans. The purpose of this study is to analyze the missense mutations and molecular modeling of ESR1, focusing on the pathogenic SNP H516N, for a better understanding of disease risk and future benefits for therapeutic benefits. This SNP was selected based on its location in the binding pocket of ESR1 and its predicted impact on drug binding. The in silico analysis was performed by applying various computational approaches to identify highly pathogenic SNPs in the binding pocket of ESR1. The effect of the SNP was explored through docking and intra-molecular interaction studies. All SNPs in ESR1 were identified followed by the identification of the highly pathogenic variant located in the binding pocket of ESR1. The mutant model of the pathogenic SNP H516N was generated, and hydroxytamoxifen was docked with the wild-type and the mutant model. The mutant model lost the formation of stable hydrogen bonds with the active site residues and hydroxytamoxifen, which may result in reduced binding affinity and therefore, will predict the patient's response to estrogenic inhibitors.

Keywords

• Single nucleotide polymorphism
• Mutation
• Molecular docking
• Breast cancer
• Intra-molecular interaction