Virtual Screening through Molecular Docking Analysis to Identify Potential Natural Inhibitor(s) of Lyn Tyrosine Kinase- An In-silico Approach

Abstract

Breast cancer on becoming one of the leading cancer types, emerged as an important barrier in increasing life expectancy of the overall population. In the current study, some compounds were screened based on literature survey for the identification of natural bioactive compounds as potential inhibitors of Lyn tyrosine kinase. Therefore, a multi-step molecular docking was carried out using AutoDock embedded in the MGL Tools. After initial screening, molecules having a higher docking score and binding free energy compared to Tamoxifen were considered for further assessment. Some already known synthetic lyn tyrosine kinase inhibitor have been used for better understanding of the comparative study. Based on in silico Lipinski filter analysis, toxicity prediction, pharmacokinetic analysis, four compounds were proposed to be promising inhibitors of Lyn tyrosine kinase. Furthermore, the binding interactions of all proposed inhibitors of Lyn showed strong ligand efficiency in terms of energy score obtained with the help of molecular modelling analyses. Hence, the proposed compounds out of which three are bioactive compounds might be taken forward as potential next-generation Lyn kinase inhibitors for managing Lyn associated breast cancer after experimental authentication.