In-silico identification of new inhibitors for Low-density lipoprotein receptor-related protein6 (LRP6)

Abstract

Low-density lipoprotein receptor-related protein 6 (LRP6) is an important therapeutic target for diseases such as osteoporosis, Alzheimer, cancer, and neurodegenerative disease. Computational methods such as ligand-based and structure-based virtual screening have been introduced as an extremely efficient and accurate tool for finding new drug targets and candidates. In this study, we aimed to screen the National Cancer Institute (NCI) Diversity Set II and parts of the ZINC database by virtual screening to identify potential and safe compounds that can inhibit the LRP6 protein. By utilizing various screening methods such as rigid and flexible molecular docking and Lipinski’s rule of five, we identified 10 potential compounds. Then, their validity was further tested by molecular dynamics simulation and MMPBSA binding free energy calculations. Eventually, it was concluded that ZINC03954520, ZINC01729523, ZINC03898665, ZINC13152226, ZINC26730911 and ZINC01069082 compounds can be potential drug compounds for inhibiting LRP6 protein. These compounds in complex with β-propeller domains of LRP6 showed that they are capable of altering the backbone of these domains and interfere with their structural dynamics which may lead to the inhibition of the signal transmission. Communicated by Ramaswamy H. Sarma