Computational screening and in silico docking analysis of non-selective beta-blockers over beta-3 adrenergic receptors

Abstract

Background: Beta-blockers with additional beneficial activity such as beta-2 agonist and alpha-1 blocking activity are developed and available as the third-generation beta-blockers for effective management of hypertension with comorbid conditions. Hypertension associated with obesity is one such common condition seen among majority of population. Aims and Objectives: This study attempts to screen the existing beta-blockers currently in use for hypertension for additional beta-3 agonist activity by in silico prediction methods. Materials and Methods: The approved non-selective beta-blockers, carvedilol, celiprolol, nebivolol, nadolol, carteolol, pindolol, propranolol, timolol, oxprenolol, sotalol, penbutolol, and labetalol, are selected to screen by three-dimensional (3D) quantitative structure–activity relationship analysis, molecular docking and dynamics were carried out in CentOS Linux platform version 5.0 installed in HPZ 800 workstation using Schrodinger LLC, New York. Results: Among screened 12 non-selective beta-blockers, carvedilol has high free binding scores of −63.186 followed by celiprolol with −53.225 and nebivolol with −53.054. Conclusion: The current research by in silico screening of 12 3D chemical structures of non-selective beta-blockers that effectively docked over beta 3 receptors are Carvedilol, celiprolol and nebivilol. Further studies can be carried on beta 3 cell lines followed by obesity animal models to validate our study finding.