Top - lead identification using ensemble based virtual screening and pharmacophore drug design for breast cancer metastatic beta arrestin 2

Abstract

Recent studies has given out the evidences of positive correlation between β-Arrestin 2 and cancer cell progression, especially breast cancer, which is the most common cancer in women worldwide. The expression of β-Arrestin 2 in breast tumor cell was proved to play important role in cancer cell invasion and metastasis via regulation of many key signaling pathways by interacting with several extracellular receptors such as CXCR-4, PAR-2, ERK1/2 and LPA… Therefore, having drugs that can specifically bind to β-Arrestin 2 and then can prevent breast cancer metastasis by blocking its interaction with those receptors above is promisingly a great method to assist patients with their breast cancer treatment. However, studying about inhibitors design for β-Arrestin 2 is relatively new and problematic. Hence, the aim of this study is to investigate β-Arrestin 2 on the rational drug design and to suggest its potential inhibitors. In this study, bioinformatics tools were used in combination with three main steps: building β-Arrestin 2 model, ensemble based docking to identify top-leads, and pharmacophore drug design. At the results, this study have pointed out top three compounds from Drugbank used to treat other disease can specifically bind to β-Arrestin 2 model. The results also suggested two new drug-like molecules as β-Arrestin 2 highly potential inhibitors since their predicted Ki are lower than 10 μM. From those initial results, further studies on β-Arrestin 2 inhibitors should be conducted experimentally to develop drugs that assist treatments for breast cancer. Keywords: Breast cancer β-Arrestin 2 Novel drug design Inhibitors Bioinformatics